U.S. patent application number 11/317634 was filed with the patent office on 2007-06-28 for surveillance network system.
Invention is credited to Arun Ayyagari, Rick Blair, David E. Corman, Michael S. Foster, Kevin Y. Ung.
Application Number | 20070150565 11/317634 |
Document ID | / |
Family ID | 37964794 |
Filed Date | 2007-06-28 |
United States Patent
Application |
20070150565 |
Kind Code |
A1 |
Ayyagari; Arun ; et
al. |
June 28, 2007 |
Surveillance network system
Abstract
Embodiments of a sensor network system provide surveillance
capabilities in multiple contexts/environments (e.g., military,
commercial, scientific, civic, urban, wilderness, etc.). Network
nodes may include devices such as sensors, network routers, network
controllers, etc. Network sensors may be configured so that power
management objectives are maximized. Network sensors (both
individually and as a group) may be capable of intelligent and
cooperative information gathering, so that the output of the sensor
network does not contain high levels of irrelevant information. The
network nodes may communicate among one another via one or more
communication links, and in some cases, multiple routes between any
two network nodes may be available. The sensor network may include
aspects of both high data rate and low data rate network features.
One or more network controllers may provide various network
management capabilities, including management of network routing,
information collection, information exportation, network
configuration, etc.
Inventors: |
Ayyagari; Arun; (Seattle,
WA) ; Ung; Kevin Y.; (Bellevue, WA) ; Blair;
Rick; (Kent, WA) ; Foster; Michael S.;
(Federal Way, WA) ; Corman; David E.; (Creve
Coeur, MO) |
Correspondence
Address: |
PERKINS COIE, LLP
P.O. BOX 1247
PATENT - SEA
SEATT;E
WA
98111-1247
US
|
Family ID: |
37964794 |
Appl. No.: |
11/317634 |
Filed: |
December 22, 2005 |
Current U.S.
Class: |
709/223 |
Current CPC
Class: |
H04L 67/12 20130101;
H04L 2209/805 20130101; H04L 63/08 20130101; H04W 84/18 20130101;
H04W 40/30 20130101 |
Class at
Publication: |
709/223 |
International
Class: |
G06F 15/173 20060101
G06F015/173 |
Claims
1. A surveillance network comprising multiple network nodes: a
first set of network nodes configured to communicate within the
surveillance network using a first type of communications link; a
second set of network nodes configured to communicate within the
surveillance network using both the first type of communication
link and a second type of communication link; and at least one
controller that is directly or indirectly linked to each of the
multiple network nodes, the controller being capable of
establishing whether each of the multiple network nodes is a member
of the first set or the second set.
2. The surveillance network of claim 1 wherein the second set of
network nodes includes reduced function devices.
3. The surveillance network of claim 1 wherein the first set of
network nodes includes endpoint devices, including one or more
sensors.
4. The surveillance network of claim 1 wherein the first set of
network nodes includes full function devices.
5. The surveillance network of claim 1 wherein at least some of the
multiple nodes communicate via a gateway node that functions as a
communication hub, and wherein the gateway node is the
controller.
6. The surveillance network of claim 1 wherein at least some of the
multiple nodes communicate via a gateway node that functions as a
communication hub, and wherein the gateway node is a network
router.
7. The surveillance network of claim 1 wherein the first type of
communications link is associated with a bandwidth allowing low
data rate information transfer over a specified range of
distances.
8. The surveillance network of claim 1 wherein the second type of
communications link is associated with a bandwidth allowing high
data rate information transfer over a specified range of
distances.
9. A system for conducting surveillance in a physical environment,
the system comprising: multiple network nodes including endpoint
devices and one or more network gateways, the endpoint devices
having sensors for detecting environmental conditions, and the one
or more network gateways functioning as communication hubs for one
or more of the multiple network nodes; means for employing, with
respect to a first group of network nodes from the multiple network
nodes, a first communication technique associated with a first type
of information; and means for employing, with respect to a second
group of network nodes from the multiple network nodes, a second
communication technique associated with the first type information
and a second type of information.
10. The system of claim 9 wherein the second communication
technique is configured for high bandwidth, short-range
connectivity for transferring data-dense information, and are
implemented using supporting applications that allow for on-demand
imaging and video capture and transmission to computing devices
performing information and decision support processing, wherein the
first communication technique includes information transfer from
sensors to computing devices performing information and decision
support processing are configured for low bandwidth, long range
connectivity for transferring low-density information and may be
used to monitor and control aspects of the communication of nodes
in both the first group and the second group.
11. The system of claim 9 wherein the first communication technique
is configured for high bandwidth, short-range connectivity for
transferring data-dense information.
12. The system of claim 9 wherein the first communication technique
is configured for low bandwidth, long range connectivity for
transferring low-density information and facilitate monitoring and
controlling aspects of the communication of nodes in both the first
group and the second group.
13. The system of claim 9 wherein the second communication
technique is associated with standards from the IEEE 802.11 family
and wherein the first communication technique is associated with
standards from the IEEE 802.15 family.
14. The system of claim 9 wherein the first communication technique
facilitates information transfer from sensors to computing devices
performing information and decision support processing.
15. A method for communication in an information gathering network
which gathers information from a physical environment, the system
comprising: designating a first set of nodes in the information
gathering network; designating a second set of nodes in the
information gathering network; assigning a first communication link
type to the first set of nodes to allow nodes from the first set of
nodes to communicate with other nodes in the information gathering
network; and assigning the first communication link type and a
second communication link type to the second set of nodes to allow
nodes from the second set to communicate with other nodes in the
information gathering network.
16. The method of claim 15 wherein assigning the first
communication link type to the first set of nodes and assigning the
first communication link type and the second communication link
type to the second set of nodes is based on characteristics of
information to be communicated within the information gathering
network.
17. The method of claim 15 wherein the assigning is further based
on power usage requirements of the network node.
18. The method of claim 15 wherein assigning is further based on
power usage requirements of a network component sending information
to the network node.
19. The method of claim 15 assigning is further based on a distance
to a network component which is to receive information from the
network node via the selected communication link type.
20. The method of claim 15 wherein first communication link type is
associated with low data rate, low bandwidth data transmission that
employs link and physical layer protocols in accordance with the
IEEE 802.15.4 standard.
21. The method of claim 15 wherein the first communication link
type is associated with a low data rate low bandwidth communication
link type that includes means for transferring reference signals to
one or more network nodes in a carrier sense multiple access with
collision avoidance (CSMA/CA) mode.
22. The method of claim 15 wherein the first communication link
type is associated with low data rate low bandwidth data
transmission that includes means for employing a time division
multiple access (TDMA) beacon structure.
23. The method of claim 15 wherein the second communication link
type is associated with high data rate high bandwidth data
transmission that employs link and physical layer protocols in
accordance with the IEEE 802.11 family of standards.
24. The method of claim 15 wherein the first communication link
type is associated with low data rate low bandwidth data
transmission that employs means to define a super-frame and timing
reference transferring information using the second communication
link type.
25. The method of claim 15 wherein the second communication link
type is associated with high data rate high bandwidth data
transmission, and wherein the second communication link type is
configured for transferring information among full functioning
devices within the information gathering network.
26. A surveillance network comprising: a controller; a plurality of
sensors being capable of communicating with the controller, each of
the plurality of sensors being capable of collecting information
from its environment and sending the collected information to the
controller; the controller being responsive to the communication
from each of the plurality of sensors to authenticate a given
sensor and compare its collected information to the collected
information from a set of sensors located in the vicinity of the
given sensor.
27. The surveillance network of claim 26 wherein the controller
further accepts the collected information if the collected
information is in a given tolerances range of the information
collected from the set of sensors located in the vicinity of the
given sensor and rejects the collected information if the collected
information is substantially outside of a tolerance range of the
information collected from the set of sensors located in the
vicinity of the sensor.
28. The surveillance network of claim 26 wherein the controller
further disconnects the communication link to the given sensor if
the collected information is substantially outside of a tolerance
range of the information collected from the set of sensors located
in the vicinity of the sensor.
29. The surveillance network of claim 26 wherein the controller
further disconnects the communication link to the given sensor if
the collected information is substantially outside of a tolerance
range of the information collected from the set of sensors located
in the vicinity of the sensor.
30. The surveillance network of claim 26 wherein the controller
further disconnects the communication link to the given sensor if
the collected information is substantially outside of a tolerance
range of the information collected from the set of sensors located
in the vicinity of the sensor.
31. The surveillance network of claim 26 wherein the set of sensors
is from the plurality of sensors.
32. The surveillance network of claim 26, wherein the controller
authenticates the given sensor based on its RF signature.
33. The surveillance network of claim 26 wherein the controller
authenticates the given sensor based on its security key.
34. The surveillance network of claim 33 wherein the security pin
is field programmed.
35. The surveillance network of claim 26 wherein the controller
authenticates each sensor based on its RF signature and security
key.
36. The surveillance network of claim 33 wherein the security pin
is field programmed.
37. A surveillance method comprising: collecting information from
one or more network nodes within an environment, the collected
information relating to a given factor or set of factors; comparing
the collected information to information received from at least two
other network nodes in the same environment, wherein the at least
two other network nodes are responsible for collecting information
that relates to the given factor or set of factors; accepting the
collected information if a variance range between the collected
information and the information received from the at least one
other network node satisfies a specified threshold; and rejecting
the collected information if the variance range between the
collected information and the information received from the at
least one other network node does not satisfy a specified
threshold.
38. The method of claim 37 wherein the one or more network nodes
include multiple sensors operating in at least partial
cooperation.
39. The method of claim 37 wherein the one or more network nodes
include at least one primary sensor, wherein the at least one
primary sensor is configured to sense a designated stimulus and
send an activation signal to at least one secondary sensor in its
vicinity based on sensing the designated stimulus.
40. A sensor network system comprising: multiple network nodes
configured to perform surveillance activities within a physical
environment; and at least one network controller configured to
monitor individual states of the multiple network nodes over time
and further configured to detect an inconsistency in a behavior of
the at least one network node, determine whether the detected
inconsistency requires an action, if the detected inconsistency
requires an action, generate instructions relating to the action;
and deploy the generated instructions to a subset of the multiple
network nodes that includes one or more network nodes affected by
the inconsistency.
41. The system of claim 40 wherein detecting an inconsistency in a
behavior of the at least one network node includes receiving a
broadcasted message from the at least one network node concerning
the state of the at least one network node, wherein the monitored
individual states include RF signal strength, power consumption,
power state, response time, latency, and/or thermal condition;
wherein the inconsistency is detected by a non-linear change in
behavior or state and results from the at least one network node
malfunctioning; and wherein the action includes conducting further
diagnostics of the at least one network node and either terminating
network participation of the at least one network node or
reconfiguring the at least one network node.
42. The system of claim 40 wherein the inconsistency is detected by
observing a non-linear change in behavior.
43. The system of claim 40 wherein the action includes terminating
network participation of the at least one network node.
44. The system of claim 40 wherein the inconsistency results from
the at least one network node malfunctioning.
45. The system of claim 40 wherein the action includes conducting
further diagnostics of the at least one network node.
46. The system of claim 40 wherein the action includes
reconfiguring the at least one network node.
47. The system of claim 40 wherein the action includes facilitating
an automatic software update for the at least one autonomous
network node.
48. The system of claim 40 wherein the action includes generating a
work order for repair of the at least one autonomous network
node.
49. The system of claim 40 wherein the action includes deploying a
new replacement node or set of replacement nodes.
50. The system of claim 40 wherein automatically detecting an
inconsistency in a behavior of the at least one network node
includes receiving a broadcasted message from the at least one
network node concerning the state of the at least one network
node.
51. The system of claim 40 wherein the at least one network node is
a newly deployed network node that requires self-configuration
instructions.
52. The system of claim 40 wherein the monitored individual states
include at least one of RF signal strength, power consumption,
power state, response time, latency, and/or thermal condition.
53. A reconfigurable surveillance network comprising: a controller
for receiving a mission plan; a plurality of sensors being capable
of communicating with the controller; and the controller being
responsive to the mission plan to create a network of sensors by
generating a communication link with a first set of the multiple
sensors based on requirements of the mission.
54. The reconfigurable surveillance network of claim 53 wherein the
controller receives an updated mission plan and accordingly
disconnects a select number of existing communication links and
generates communication links with a second set of the plurality of
sensors.
55. The reconfigurable surveillance network of claim 54 wherein the
select number is in the range of one to the maximum number of
sensors with existing communication links.
56. The reconfigurable surveillance network of claim 53 wherein the
controller receives an updated mission plan and accordingly
generates communication links with a second set of the multiple
sensors.
57. The reconfigurable surveillance network of claim 53 wherein the
controller disconnects the communication link of a sensor when a
quality of a performance of the sensor falls below a given level
and generates a communication link with one of the multiple sensors
to replace the sensor with the disconnected communication link.
58. The reconfigurable surveillance network of claim 53 wherein the
generated communication link is based on a gateway to sensor and
sensor to gateway communication model.
59. The reconfigurable surveillance network of claim 53 wherein the
multiple sensors include a first sensor and a second sensor, and
wherein information collected by the first sensor and the second
sensor is integrated into a single information set based on
instructions provided by the controller.
60. The reconfigurable surveillance network of claim 53 wherein the
multiple sensors include at least one sensor that lacks processing
capabilities and at least one sensor configured for image or
acoustical processing.
61. The reconfigurable surveillance network of claim 53 wherein the
controller is configured for deployment in a military
environment.
62. The reconfigurable surveillance network of claim 53 wherein the
controller provides routing information for at least some of the
multiple sensors, and wherein the routing information determines
how information is routed among the multiple sensors in the
information gathering system.
63. A method for self-configuration of a surveillance network with
multiple network nodes, the method comprising: receiving, at a
network node, an indication of a new mission, activity, or task to
be performed by the surveillance network; identifying one or more
network nodes being capable of performing the new mission,
activity, or task; and enabling each of the identified one or more
network nodes to perform the mission.
64. The method of claim 63 wherein the enabling includes generating
an operation specification for each of the identified one or more
network nodes, wherein the disseminated information enables
automatic re-configuration and/or re-organization of the identified
one or more network nodes so that the new mission, activity, or
task can be performed.
65. The method of claim 63 wherein the generated operation
specification for each of the identified one or more network nodes
includes software reconfiguration codes.
66. The method of claim 63 wherein enabling each of the identified
one or more network nodes to perform the mission includes
designating communication links between select network nodes within
the surveillance network.
67. A method of self-configuration a surveillance network having
multiple network nodes, the method comprising: receiving an
indication of a recently deployed network node; determining a role
or operation specification for the recently deployed network node
based, at least in part, on the relative location of the recently
deployed network node and the capabilities of the recently deployed
network node; and providing information for dissemination within
the surveillance network, the provided information including an
indication of a role or operation specification for the recently
deployed network node and enabling automatic integration of the
recently deployed network node into the surveillance network.
68. The method of claim 67 wherein received indication is a
broadcast signal sent from the recently deployed network node, and
wherein the received indication includes an indication of the
actual location of the recently deployed network node and an
indication of the capabilities of the recently deployed network
node; wherein determining the role or operation specification is
based, at least in part, on an application of network operation
rules locally accessible to the network controller; and wherein the
provided information includes configuration instructions for the
recently deployed network node and communication instructions for
sensor nodes that are to be in at least intermittent communication
with the recently deployed network node during operation of the
surveillance network.
69. The method of claim 67 wherein the provided information
includes configuration instructions for the recently deployed
network node.
70. The method of claim 67 wherein the received indication includes
an indication of the actual location of the recently deployed
network node.
71. The method of claim 67 wherein the received indication includes
an indication of the capabilities of the recently deployed network
node.
72. The method of claim 67 wherein determining the role or
operation specification is based, at least in part, on an
application of network operation rules locally accessible to the
network controller.
73. The method of claim 67 the received indication is a broadcast
signal sent from the recently deployed network node.
74. The method of claim 67 wherein the received indication is a
message received from a network node other than the recently
deployed network node, the message being passed based on a
multi-hop framework.
75. The method of claim 67 wherein the recently deployed node is
configured to broadcast a signal conveying its presence to network
nodes in its vicinity, and wherein one or more of the network nodes
in its vicinity is configured to generate the received indication
based on the broadcast signal.
76. The method of claim 67 wherein the role or operation
specification for the recently deployed node is not known until
after the recently deployed node is deployed.
77. The method of claim 67 wherein the role or operation
specification for the recently deployed node is at least partially
known by the network controller before the recently deployed node
is deployed.
Description
TECHNICAL FIELD
[0001] The present invention relates generally to surveillance
using networks, such as in a military, scientific, civic, or
commercial context.
BACKGROUND
[0002] Many commercial, civic, scientific, and military operations
have the need to remotely conduct surveillance of an environment.
For example, military groups may have a need to conduct
surveillance on a battlefield or in an urban area. Scientists may
need to conduct surveillance of a forest or wetland area. Likewise,
examples of surveillance activities in a commercial setting include
warehouse surveillance, surveillance of large retail
establishments, etc.
[0003] Currently, surveillance systems may use one or more deployed
sensor devices that are capable of passing on collected information
to users and/or user devices. For example, users may be able to go
into the field and collect such information directly from field
devices. More advanced surveillance systems may use some form of
remote connection to automatically send collected information back
to a data collection system (or the like), so that the collected
information can be analyzed, stored and tracked over time, etc.
However, these current systems have limitations, including those
related to limited energy supply for field devices, sensor
deployment and placement issues, remote information storage and
retrieval issues, satellite issues, network bandwidth issues,
disruption issues, obstruction issues, etc. In addition, with
respect to large surveillance systems (e.g., those having many
sensors), information multiplication problems may exist, which may
overload human users of the information. For example, current
surveillance systems may produce only a small amount of relevant
information and a relatively large amount of irrelevant
information, which users must then filter through.
SUMMARY
[0004] The following summary is provided for the benefit of the
reader only, and is not intended to limit in any way the invention
as set forth by the claims. Aspects of a sensor network system for
surveillance of an environment are described herein. Embodiments of
the sensor network system may be used in commercial operations,
civic operations, scientific operations, military operations, etc.
Once deployed (e.g., via an aerial and/or terrestrial deployment
strategy), the sensor network system may operate intelligently
using an autonomous framework. For example, each node in the
network system may operate as an individual device with its own job
and purpose. For some designated network nodes (e.g., "full
function devices"), this job/purpose may require that the network
node act intelligently. In such cases, the network node is equipped
with some level of processing/decision-making capabilities.
Examples of such capabilities include image processing
capabilities, decision fusing capabilities, etc. For other network
nodes, this job/purpose may require little, if any, processing
capabilities. In such cases, the network node is configured only
for simple and/or limited-purpose operation (e.g., configured for
sensing and performing basic RF communications). In either case,
communication with other nodes in the network allows each node to
play an autonomous yet active role in the sensor network system.
Accordingly, the sensor network system can efficiently react to an
array of conditions, fuse relevant data in an intelligent way, and,
to varying extents, self-organize and self-manage.
[0005] In an illustrative example, a group of sensors that form
part of the sensor network system is deployed on a bridge to
monitor traffic for enemy presence in a military context. This
group of sensors includes various primary sensors that, in this
case, are sensitive to vibrations, as well as secondary sensors
that, in this case, are image sensors (which include some basic
image processing capabilities) and acoustical sensors (which
include some basic sound processing capabilities). Some of the
secondary sensors in the sensor network system include information
fusing capabilities. That is, these sensors have the ability to
aggregate information collected by different sensors/nodes to
produce more useful information.
[0006] To conserve energy used by the sensor network system, all
the sensors in the bridge example are configured to remain in a
"sleep mode" with the exception of the primary vibration sensors.
If there is activity on the bridge, the vibration sensors will
detect it and initiate a process that "wakes" the secondary image
sensors and acoustical sensors, which in turn, gather any necessary
information. Because some of the image/acoustical sensors in this
example are "smart" devices, they can tell whether the traffic on
the bridge may be something that human users of the network are
interested in. If so, they can activate additional sensors/devices.
For example, by employing time/space based local reasoning (e.g.,
using feature vectors tied to automated exploitation methods),
sensors in the network system may be able to determine the best
sensor viewpoints for event data. Using their data-fusing
capabilities, select intelligent sensors fuse data together,
including data received from other endpoints/sensors.
[0007] In the bridge example, the sensors and network nodes then
transmit aspects of the collected information to a network
controller (e.g., through a set of one or more network routers).
The network controller then passes the information on to the
appropriate system/external network for user consumption and/or
additional processing. In this context, the network controller can
act as a primary host for application services that allow
interchange between nodes of the sensor network and entities within
one or more external networks/systems. In some embodiments,
interactions between the network controllers and the one or more
external networks/systems may be based on, for example, a
publisher/subscriber model. This configuration reduces the amount
of information that human users filter through, conserves energy
expenditures at the network nodes (because nodes that are not
currently needed can sleep) and allows network resources to be used
in an efficient way.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 is a system diagram showing an example of a
configuration of a sensor network system in an embodiment.
[0009] FIG. 2 is a system diagram showing and example of one or
more network controllers forming a hierarchical network controller
system in an embodiment.
[0010] FIG. 3 is a block diagram showing an embodiment of a sensor
network system with features of both a high data rate network and a
low data rate network.
[0011] FIG. 4 is a diagram showing examples of deploying a sensor
network system in some embodiments.
[0012] FIG. 5 is a flow diagram showing an example of a routine for
disseminating information to nodes in a sensor network in an
embodiment.
[0013] FIG. 6 is a flow diagram showing an example of a routine for
exporting information from nodes in a sensor network.
[0014] FIG. 7 is a system diagram showing an example of a sensor
network configuration based on mission phases in an embodiment.
DETAILED DESCRIPTION
[0015] Certain specific details are set forth in the following
description and in FIGS. 1-5 to provide a thorough understanding of
various embodiments of the invention. Well-known structures,
systems and methods often associated with network environments have
not been shown or described in detail to avoid unnecessarily
obscuring the description of the various embodiments of the
invention. Those of ordinary skill in the relevant art will
understand that additional embodiments of the present invention may
be practiced without several of the details described below.
[0016] Many embodiments of the invention described below may take
the form of computer-executable instructions, including routines
executed by programmable network nodes and computers. Those skilled
in the relevant art will appreciate that the invention can be
practiced with other computer system and network configurations as
well. Aspects of embodiments of the invention can be embodied in a
special-purpose computer or data processor that is specifically
programmed, configured, or constructed to perform one or more of
the computer-executable instructions described below. Accordingly,
the term "computer" as generally used herein refers to any data
processor and includes Internet appliances, hand-held devices
(including palm-top computers, wearable computers, cellular or
mobile phones, multi-processor systems, processor-based or
programmable consumer electronics, network computers, minicomputers
and the like).
[0017] Aspects of embodiments of the invention can also be
practiced in distributed computing environments, where tasks or
modules are performed by remote processing devices that are linked
through a communications network. In a distributed computing
environment, program modules or subroutines may be located in both
local and remote memory storage devices. Aspects of the invention
described below may be stored or distributed on computer-readable
media, including magnetic and optically readable and removable
computer disks, as well as distributed electronically over
networks. Data structures and transmissions of data particular to
aspects of the invention are also encompassed within the scope of
the invention.
[0018] FIG. 1 shows an example of a configuration of a sensor
network system 100 in an embodiment. The sensor network system 100
may provide various capabilities including self-configuration
capabilities, self-healing capabilities, and intelligent
cooperative sensing. Other capabilities of the sensor network
system 100 may include data storage and retrieval functionality,
autonomous decision making capabilities, store and forward
capabilities, and resource-aware sensing capabilities.
[0019] The sensor network system 100 may include at least three
classes of devices, including full function devices, reduced
function devices, and non-intelligent end devices. More
specifically, the full functional and reduced function devices of
the sensor network system 100 may include network controllers 105
(full-function devices), network routers 110 (full or reduced
function devices), and network-capable end devices 115 (full or
reduced function devices) including smart sensors (e.g., sensors
with image processing capabilities), each having some level of
network capabilities and some possibly functioning as gateways with
respect to other network nodes. In some embodiments, the full
function devices 105 are knowledgeable about the sensor network
topology and are aware of alternate multi-path routes to reach the
network controller. The non-intelligent end devices may include a
variety of active and/or passive sensors 120. Examples of types of
sensors may include audio/acoustic sensors, imaging sensors, video
sensors, infrared sensors, RF sensors, vibration/seismic sensors,
magnetic sensors, chemical sensors, etc. For example, in some
embodiments, at least some of the sensors may be low energy and
self-contained and provide basic sensor functionality, data
dissemination and/or command/control execution. Because they may
lack their own network capabilities, for such active and or passive
sensors/devices 120 to function as part of the network, they may be
used in conjunction with network capable end devices 115.
[0020] As needed, the sensors may be small (e.g., to prevent
detection or remain unobtrusive) and/or come with a casing/shield
that protects them against harsh environmental conditions. In some
embodiments, the sensor devices may be self-powered (e.g., contain
long-life batteries, operate on heat or solar energy, etc.) and
consume low amounts of energy (e.g., by being energy efficient and
having stand-by or inactive modes). For example, in some
embodiments, image sensors may employ power-aware image compression
and storage and power adaptation methods that are tailored to
extended low level computation within the sensor.
[0021] The network connection components of the sensor network
system 100 may include both high speed links 125 and low speed
links (130 and 135). For example, as shown in FIG. 1, using
multiple low speed star links 135, groups of one or more sensors
and/or end devices may be linked to a network router 110 in a
"star" configuration. In turn, the respective network router 110
(which provides both data routing and network management
functionalities) may be linked to one or more other network routers
110 (e.g. using either high speed mesh links 125 or low speed mesh
links 130), forming a mesh of network routers 110 that are,
in-turn, linked to one or more network controllers 105.
[0022] Various types of wireless technologies may be used to
implement wireless aspects of the sensor network system. For
example, aspects of some embodiments of the sensor network system
may include use of wireless personal area network (WPAN) technology
and/or wireless local area network (WLAN) technology. Various IEEE
standards may be used to implement such wireless network
technology, including standards from the IEEE 802.15 family (e.g.,
802.15.1, 802.15.2, 802.15.3, 802.15.3a, 802.15.4, etc.) for WPAN
and standards from the IEEE 802.11 family (e.g., 802.11a, 802.11b,
802.11g, etc.) for WLAN. In general, however, almost any type of
data link mechanism may be used including satellite, Bluetooth,
and/or infrared/optical techniques, cellular or digital wireless
communications, wired or wireless local area network, use of
existing network infrastructure, etc., and any combination of such
data link mechanisms. Where possible, intermittent data link
mechanisms, such as bundled custodial-based network communications,
may also be used to conserve resources, including bandwidth.
[0023] As shown in FIG. 2, in some embodiments, one or more network
controllers 105 may form a hierarchical network controller system
200 that manages overall sensor network configuration and
operations, performs gateway/proxy functions, and provides access
to external networks. In general, each network controller 105 in
the network controller system 200 may be configured to accept,
remove, and configure devices in the network (e.g., assign
addresses and provide routing tables to enable efficient and
effective communication of network nodes). The network controllers
may also support both dynamic and periodic network synchronization,
as well as support peer-to-peer communication among network nodes.
In addition, the network controllers 105 may issue command and
control information to end sensors (described in more detail with
respect to FIG. 5) and receive data from sensors so that such data
may be forwarded to external networks. Thus, the network
controllers 105 may serve as the primary interface between the
external networks and the end device sensors.
[0024] The network controllers may also support both dynamic and
periodic network synchronization and support. For example, network
controllers 105 may configure router nodes to perform repeater
function to extend the range of the sensor network and perform
"frequency management" including implementing spatial reuse plans
for the sensor network. To enable the above functionality, the
network controllers 105 may each maintain location and operational
state information for devices/nodes within the sensor network.
[0025] In some embodiments, the one or more network controllers may
be linked to a management subsystem 205 that provides both system
management to the sensor networks and information management
services to external networks. System management may include
planning, deployment, monitoring, and network management.
Information management services may include storage, discovery,
data transformation, messaging, security, and enterprise service
management.
I. Combining High Data Rate and Low Data Network Features
[0026] Due to the variability in the communication ranges and the
amount/type of data to be interchanged, the sensor network system
(which may consist of many nodes dispersed over a potentially wide
geographical area) may employ a combination approach for data
interchange consisting of low data rate links capable of
information transfer over longer ranges and high data rate links
capable of large information transfers over relatively shorter
ranges. This type of approach solves problems associated with power
consumption and resource conservation in a sensor network system
having diverse energy consumption needs (which may be limited
and/or fixed) and complex and dynamic communication needs.
[0027] As described above with respect to FIGS. 1 and 2 the
computing and communication resources of each sensor node within
the sensor network system can vary, (i.e., some sensor nodes have
greater computing and communication capabilities than others).
While it is true that sensor network systems may function in an ad
hoc manner, in some embodiments, communication to and from a
particular sensor node is more akin to a client-server interaction.
For example, each sensor node may interface with another network
node (e.g., a network controller 105 or network router 110 of FIG.
1) that functions as a gateway, dynamically establishing a
communication link between the nodes that allows for information
within the network to be gathered and directed for remote
processing in an environment where computing and communication
resources are less constrained. This implies that the sensor
network system can be envisioned as a hierarchical tree structure,
such as directional acyclic graph (DAG), with the root node of the
hierarchical tree being the gateway node and sensor nodes forming
various tiers of child/leaf nodes, as roughly depicted in FIG.
1.
[0028] In some embodiments, this hierarchical tree data
model/framework results in sensor nodes closer to the gateway node
performing more in-transit forwarding between its higher and lower
tier level sensor nodes. To conserve computing and communication
resources (thereby conserving power and extending sensor node
life), it is sometimes desirable to minimize the number of hops
taken by the data flow from the child/leaf sensor nodes to the
gateway node. In some sensor network systems, this type of
conservation is especially desirable for intermediate in-transit
forwarding nodes. Accordingly, in some embodiments the sensor
network is configured so that at least some of the child/leaf
sensor nodes are each able to communicate directly with the gateway
node via low data rate links. In contrast, data-intensive
information interchanges between a given child/leaf sensor node and
a gateway node may involve multiple intermediary in-transit hops
using high data rate links, which have shorter ranges. In some
embodiments, this combination approach facilitates implementation
of a link power budget and/or frequency/spectrum reuse plan.
[0029] The communication requirements of the sensor network system
may differ based on varying levels of network capacity and power
needs, as well as mission requirements. For example, many sensor
network nodes are sensitive to power consumption, with less capable
nodes most likely using less bandwidth and more capable nodes using
more bandwidth, since bandwidth is proportional to power
consumption (the communication component is typically the highest
power drain of any sensor node element). In addition to power
consumption, generally, more capable nodes have more data to
transmit, are larger, and likely have more capacity for power
storage. Less capable nodes are likely to be smaller and need less
network bandwidth.
[0030] As shown in FIG. 3, a sensor network system 300 in
accordance with some embodiments may combine features of a high
data rate network 305 with features of a low data rate network 310.
To conserve energy, the sensor network system 300 illustrated in
FIG. 3 utilizes low data rate communications for the dissemination
of, for example, command and control-type information (used in
sensor and network management) and the transfer of information
among sensor nodes having simple primary transducers and uses high
data rate communications for sensor nodes experiencing larger
information and data streaming interchanges. For each node, the
determination of whether to employ either the high data rate 305 or
the low data rate network features 310 may be based on a number of
factors such as, capability of the node, capabilities of the
surrounding nodes, criticality and latency constraints of the data,
amount of data to be transferred, physical and logical state of the
sensor nodes involved in the interchange, energy use
requirements/limits, geographical location, frequency/spectrum
reuse plans, etc. This determination may be variable (e.g., it may
change from mission to mission, as new resources become available,
or even transaction by transaction, as some nodes are configured to
use both types of network features).
[0031] For example, the high data rate network features 305 may
provide high bandwidth, short-range connectivity for transferring
data-dense information within the network 300 (e.g., by supporting
applications that allow for on-demand imaging and video capture and
transmission to computing devices performing information and
decision support processing). To further illustrate, information
from array sensor nodes, such as image capture sensors, benefit
from the movement of larger amounts of data with stringent latency
controls favoring high data rate/bandwidth transfer. In addition,
data movement for the array sensor nodes is likely bursty in
nature, event driven, thus favoring high data rate network
features, and involves high power requirements. An example of a
high data transfer rates may be in the range of gigabits/second or
higher (or high megabits), while an example of a low data transfer
rates may be in the range of megabits/second or lower.
[0032] In contrast, the low data rate network features 310 may
provide lower bandwidth, long range connectivity for transferring
less dense information within the network (e.g., allowing
information transfer from sensors to computing devices performing
information and decision support processing) and may be used to
monitor and control aspects of both the high data rate network
features and the low data rate network features. For example, in
some embodiments, the dissemination of command and control type
information is ubiquitous across the network and occurs more or
less continuously. Command and control type messaging typically
involves small messages (which use less bandwidth). Similarly,
messages from sensor nodes supporting simple primary transducers,
such as vibration and acoustic signatures, tend to be small and
have low bandwidth requirements. For example, a discrete sensor
detects an event, wakes up from its sleep state, gathers data for a
pre-determined period and prepares to send the gathered data to an
upper layer fusion node. Since this is a low level sensor with
minimal capability and is designed to maximize its lifetime through
minimum power consumption, it is configured to send data at a
minimal data rate. In general, discrete sensor data movement across
the network is typically bursty in nature and the messages are
likely small to medium in size, which again is facilitated by the
use of low to medium bandwidth. Latency may be tightly specified,
thus impacting capacity (bandwidth) requirements.
[0033] In some cases, particular sensor nodes (e.g., those with
intermediate or high capabilities) may be configured for
communication using both high data rate network features and low
data rate network features. For example, a sleeping video sensor is
triggered into operation via a command from the fusion node in
response to the data received from a discrete sensor (via a low
data rate network features). In response, the video sensor begins
operation and in-turn streaming real-time video over the network
(via high data rate features). Along similar lines, more capable
sensor nodes may perform data aggregation and computation functions
on behalf of the less capable sensor nodes. As a result, more
capable nodes can either work as an end device with high data rate
mode or as an intermediary node to connect the less capable nodes
to the controller. The intermediary nodes typically have both the
high data rate and the low data rate. For this type of node, the
decision on which data rate to use is made at the application level
of the node that runs on the operating system of the sensor
node.
[0034] Generally, routing for low data rate network features 310
may be based on hierarchical routing protocols with table-driven
optimizations, while routing for high data rate network features
305 may be based on table-driven routing from source to network
controller. This type of configuration may permit multiple paths
between a given device and network controller for both low and high
data rate networks.
[0035] The following text describes the low data rate network
features 310 and the high data rate network features 305 in the
context of a protocol stack (e.g., application layer, transport
layer, network layer, link layer, physical layer, etc.). With
respect to low data rate sensor network features 310, IEEE 802.15.4
may be used as a starting point for link and physical layer
protocols. In some embodiments, access to communication channels
may be implemented via carrier sense multiple access with collision
avoidance (CSMA/CA). This allows devices accessing the
communication channels to maintain low duty cycle, while at the
same time supporting a large number of devices. When operating
under such circumstances, a network controller may use low data
rate network features 310 to transmit reference signals to various
network nodes/devices, thereby announcing its presence and making
the network controller detectable to such network nodes/devices.
Some embodiments may also employ a time division multiple access
(TDMA) beacon structure for implementing low data rate network
features, which is useful in cases where dedicated bandwidth and
low latency is desirable. For example, while operating in a beacon
mode, a network controller may transmit beacons at periodic
intervals defining a super-frame structure and timing
reference.
[0036] With respect to high data rate sensor network features 305,
IEEE 802.11 may be used as a starting point for link and physical
layer protocols. In some embodiments, access to communication
channels may be implemented using a TDMA virtual beacon structure.
Aspects of the low data rate network features 310 may be used to
define the super-frame and timing reference for the high data rate
network TDMA structure. The sensor network high data rate network
features 305 may also employ a CSMA/CA mechanism as a backup (e.g.,
when connectivity via low data rate network system is
disrupted).
[0037] Because of complexities associated with high data rate
transmission (e.g., complexities relating to enhanced storage
requirements, power requirements, computing requirements, and
communication requirements), the high data rate network features
305 may be limited to interactions among full function devices.
Scheduling of network access by such devices may be performed in
coordination with a network controller, which allows for
information transfer from non-intelligent sensors to reduced
functional and/or full function devices performing information and
decision support processing. Using the low data rate network
features 310, each device may request time references from the
network controller to maintain dynamic synchronization is
maintained by requesting timing reference from the network
controller via the out-of-band low data rate network features prior
to the scheduled communication. Accordingly, both endpoint devices
(e.g., sensors) and intermediary communication devices (routers and
other network nodes) may be aware of the route to reach the network
controller, which manages the dissemination of the routes.
II. Monitoring Network Nodes Based on State (Node Profiling)
[0038] In some embodiments, the sensor network system may be
configured as a "smart network" that provides appropriate agile
connectivity and bandwidth through awareness of network nodes,
including monitoring their health, states, and conditions. In such
a smart network, network controllers, or the like, can be used to
monitor the health and/or state of network nodes within the network
over time. One of the problems this solves is related to the fact
that sensor nodes within the sensor network that are not tethered
have finite life due to various conditions such as power storage
capacity, adverse environmental conditions, or being disabled by
external entities such as the enemy. In addition, the sensor nodes
may be tampered with by external entities to signal erroneous
information as a means of denial of service (DoS) attack. For these
reasons and others, it is beneficial that backend sensor network
management components (such as the management subsystem 205 of FIG.
2), or the like, monitor the health status of the sensor nodes to
determine the affectivity of each sensor node to determine whether
such sensor nodes are capable of performing at or above threshold
performance levels.
[0039] Monitoring the health and/or status of network nodes also
enables the management subsystem to determine the validity of the
information received from the particular node. For example, the
management subsystem may perform authentication (directly and/or
indirectly) to verify a node's identity and, thereby, validate the
information received from the particular node. In some cases, a
sensor node may be factory programmed with a unique serial number.
Prior to deployment, such sensor nodes may also be programmed in
the field with unique pre-placed security keys that further
facilitate authentication. The management subsystem may then
authenticate the sensor node based on its serial number and
security keys using challenge/response mechanisms. One advantage of
this type of authentication scheme includes eliminating the need to
perform authentication based on Public Key Infrastructure (PKI),
which ordinarily requires nodes to have more advanced computing and
communication capabilities.
[0040] Another that the sensor network system can facilitate
authentication is through the use of alternate mechanisms, such as
challenge/response and RF emission signature comparison. For
example, prior research has shown that each wireless transmitter
has a unique RF emission signature. Thus, in some embodiments, the
RF emission signature of a given sensor node can be compared
against the RF emission signature profile stored in the management
subsystem to verify it's identify.
[0041] Once the physical identity of a given sensor node has been
established, its health status and performance are monitored and
profiled by the management subsystem. For example, state conditions
that can be monitored include RF signal strength, power
consumption, power state, response time, latency, thermal
condition, etc. In this way, inconsistencies in the state of a
network node (e.g., the occurrence of non-linear changes in the
network node's behavior) can signal action by the network. Such
action may include terminating the problematic node's participation
in the network (e.g., in the case of a node that is not capable of
operating correctly or has otherwise been compromised); restricting
the node's participation in the network; conducting further
diagnostics on the node; reconfiguring the node (e.g., by
facilitating a software update); generating a work order for repair
of the node, deploying a new replacement node or set of replacement
nodes, etc. The monitoring or profiling of network node may be
implemented using one or more techniques including
advertising/broadcasting by nodes (ranging from dumb devices to
reduced function and full function devices) and/or querying by
network controllers. Similar techniques may be used for accepting
newly deployed nodes into the network.
[0042] The sensor network system may have multiple sensor nodes
collecting data about similar/related environmental parameters.
This implies that data gathered from a particular sensor node will
very likely be consistent with other sensor nodes within its
proximity. In this context, nodes within the same vicinity may be
those located within a specified threshold distance and/or those
positioned geographically in such a way that they can
(theoretically) measure the same factor in the environment and
provide results within a tolerance range where the mission plan
defines the tolerance range. Accordingly, the management subsystem
may analyze data received from various sensor nodes and establish
the inter-relationships between the data gathered from peer sensor
nodes within the same geographical region. For example, if there
are temperature sensor nodes within close proximity, then the
management system may assume that the temperature measurements
received from each of these sensor nodes should, theoretically, be
within a specified range. Measurements from sensor nodes that are
beyond the expected range may then be consider suspect by the
management subsystem. Once data is received from a particular
sensor node is deemed questionable, the management subsystem can
attempt to re-authenticate the sensor and query it for its
performance state information. If the management subsystem
determines that the integrity of the data from a given sensor node
cannot be established, it can appropriately account for it by
ignoring data received from the problematic node possibly disabling
it. In addition, measurements that fall outside a specified
tolerance range may be rejected.
[0043] The management subsystem may expect data received from a
given sensor node within a given temporal period to be within
certain bounds based on the dynamics of one or more sensed
parameters. For example, multiple data samples from a vibration
sensor node within a short period can be expected to follow an
estimated trajectory without sudden large deviation. The management
subsystem may profile the data received from the given sensor node
to ensure that the node is functioning appropriately. Should the
received data not meet the specifications, the management subsystem
may perform re-authentication and diagnostics and, if need be,
ignore data received from and possible disable the particular
sensor node if it does not meet the desired performance
profile.
III. Node Deployment, Self-Configuration, Self-Organization, and
Self-Healing
[0044] In some embodiments, the sensor network system may be
configured for self-deployment, self-configuration,
self-organization, and/or self-healing. This allows for the network
to be initialized and successfully maintained across wide (and
sometimes difficult to access) geographic areas with little or no
manual intervention for multiple missions. For example, in many
cases, it is simply not viable to expect manual configuration of
the sensor network in the field, especially in hostile
environments. After nodes are physically deployed, the sensor
network incorporates various self-organization, self-configuration,
and self-healing techniques that allow network nodes to be
effectively configured, organized, and managed within the sensor
network system on an ongoing basis, while eliminating or minimizing
the need for human intervention in this regard.
[0045] As shown in FIG. 4, in some embodiments, deployment of nodes
comprising the sensor network system may involve various
terrestrial and/or aerial deployment strategies, e.g., so that
wireless sensor nodes can be seeded in the field, potentially
across wide geographical areas. Deployment may involve dispersal of
sensor network devices by persons, robots, unmanned air vehicles
(UAVs), ground platforms, etc. For example, in a military/combat
environment, troops or robots may deploy network nodes on the
ground using a breadcrumb approach, where devices are dispensed as
needed on a path as a person or robot progresses in a surveillance
network. To avoid problems with obstructions that may block network
communication, sensors may be placed at locations so that every
sensor/network node is in communication with at least one other
network node. Aerial deployment (e.g., by UAV) (also illustrated in
FIG. 4) is also a possibility in high risk areas, or areas that are
difficult to reach from the ground (e.g., active battle zones or
wilderness areas). However, aerial deployment may result in rougher
placement of sensors.
[0046] A number of prior publications assume that sensor networks
operate as ad hoc networks with a high degree of peer-to-peer
communication. While it is true that sensor networks function in an
ad hoc manner, communication to and from a particular sensor node
is often more akin to a client-server interaction. For example, in
some embodiments, each of the sensor nodes within the sensor
network system interfaces with a gateway node (e.g., a full
functional device or a network controller) that allows for
information to be gathered and directed for processing at a remote
location (e.g., a location where computing and communication
resources are not constrained), resulting in a gateway to sensor
and sensor to gateway communication model. As described in
preceding sections herein, this implies that the sensor network
system can be envisioned as a hierarchical tree structure, such as
directional acyclic graph (DAG), with the root node of the
hierarchical tree being the gateway node and sensor nodes forming
various tiers of child/leaf nodes. In some embodiments, the gateway
node is expected to periodically transmit beacon frames for
deployed sensor nodes to synchronize with. This is not an issue for
the gateway node since it does not have the power, computing, and
communication resource constraints experienced by sensor nodes.
[0047] One challenge involved in maintaining an effective sensor
network that is self-configuring, self-organizing, and self-healing
relates to the automatic discovery of the sensor nodes and
establishment of the DAG that effectively connects the sensor
network to the gateway node, which may be driven by particular
mission objectives, and may thus, change over time. In other words,
as part of the seeding process, each sensor node determines where
it stands relative to other nodes (e.g., within the hierarchical
tree structure described above). Accordingly, while the seeding of
the sensor nodes across a geographical area may be random from a
micro level, (i.e., not based on a specific or relative location),
distribution of sensor nodes at macro level is organized based on
the mission objectives.
[0048] Once the sensor nodes have been deployed, the more capable
sensor nodes establish direct or indirect connectivity with the
gateway node for authentication and subsequently to receive command
and control information from the gateway node. For example, soon
after physical deployment, existing sensor nodes are configured to
detect newly deployed nodes and incorporate them into the network
in an organized and meaningful way. In one illustrative example, a
new set of sensor nodes are physically deployed within the network.
Upon deployment, these nodes each broadcast a signal to surrounding
nodes in their vicinity (assuming the sensors were deployed in the
proper area and such nodes actually exist). In some embodiments,
more capable sensor nodes that have already been configured
periodically transit beacon frames to enable recently deployed less
capable sensor nodes to synchronize and associate with the given
more capable sensor node. The more capable sensor nodes also update
the gateway node with information and state of the less capable
sensor nodes that have been associated with it. The gateway nodes
compiles this overall information of the sensor network state to
compute the desired topology and routing hierarchy to be used by
the sensor network system at each phase of the mission. The
computed routing, primary, and alternate, information for each of
the more capable sensor nodes is sent to the respective sensor
nodes by the gateway node, thereby enabling self-configuring
operation of the sensor network.
[0049] Even if there are no network controllers operating in the
immediate vicinity of the newly deployed sensors (i.e., within
range of receiving such broadcasted signals), by employing
multi-hop techniques (the passing on of information from one node
to another to reach an intended destination) an indication of the
broadcasted signals eventually reach a network controller capable
of managing the self-organization and self-configuration of the
network relative to these newly deployed nodes. In particular, the
network controller may be programmed to send out information via
lower level gateway nodes to each node that is to be affected by
these newly deployed nodes. This information may specify the
role/operation of the newly deployed nodes and provide rules of
interaction between the new nodes and existing nodes. In addition,
the network controller may be programmed to send out
self-configuration information for the newly deployed nodes, so
that they may each be made aware of their specific operation/role
within the network. This specific operation/role may be based not
only on the capabilities of the deployed nodes, but also on the
actual location in which it is deployed. Thus, in some cases where
physical deployment at a precise location is difficult to achieve
(e.g., with aerial deployment), the ultimate role and or operation
of a newly deployed node cannot be verified in advance and is not
determined until it has come to rest at its location and its actual
location coordinates can be determined.
[0050] In addition to self-configuration and self-organization
based on newly deployed nodes, the sensor network system may also
perform self-configuration and self-organization when faced with
instructions to perform a new task, activity, or mission. For
example, given a new mission to monitor ground activity within an
area defined by a set of coordinates, the network controller may
send out new self-configuration/self-organization messages to an
affected set of nodes within that area. Likewise, problems in the
network, (e.g., defective or malfunctioning nodes) may also be
handled using similar techniques. For example, if a particular
network node is no longer functioning properly an its quality of
performance falls below a given level (detected, for example, using
the self-monitoring techniques described above), the network
controller is programmed to send out instructions to affected nodes
so that they can self-reconfigure to eliminate that node from the
network.
[0051] In general, self-configuration, self-organization, and
self-healing is performed via the communication of key information
within the network, sample techniques for which are described below
with respect to FIGS. 5 and 6.
[0052] FIG. 5 provides an example of a routine 500 for
disseminating information to nodes in a sensor network in a
particular embodiment. For example, users of the sensor network may
want to disseminate information to full and/or reduced functional
nodes of the network in order to configure the network in
accordance with new performance requirements (e.g., as specified in
a mission plan). This also facilities the self-organizing and
self-managing of the sensor network system.
[0053] The routine 500 of FIG. 5 is described from the perspective
of a gateway node such as a network controller node. At block 505,
the network controller receives network configuration information
from a source (e.g., such as would be associated with a new mission
plan), such as the management subsystem 205 of FIG. 2, or some
other user-controlled source (including sources from an external
network) that has access to the network controller. At block 510,
the network controller determines which nodes in the sensor network
are to receive updated information based on the received network
configuration information. At block 515, the network controller
determines a best route for disseminating information to each of
the nodes that are to receive updated information. In some
embodiments, network routing may be handled using Internet protocol
(IP) with respect to name-space and packet framing for low and high
data rate network features. To improve effectiveness, network
routing within the sensor network system may involve the network
controller defining and then selecting from multiple paths between
itself and a given network node. At block 520, once the network
controller determines the appropriate route, the information is
disseminated to the relevant network nodes, thereby allowing the
sensor network to implement the desired configuration updates. The
routine 500 then ends.
[0054] FIG. 6 provides an example of a routine 600 for exporting
information from nodes in a sensor network. The routine 600 is
performed by an embodiment of a sensor network system. The routine
600 begins at the individual device level and ends at the network
controller level. At block 605 a non-intelligent end device in the
network (e.g., a vibration sensor, an audio sensor, and RF sensor,
etc.) reacts to stimulus in its environment by transmitting a
signal (e.g., via Bluetooth, 802.11, infrared, RF, etc.) to a
reduced function device (e.g., a sensor with image processing
capabilities, acoustic processing capabilities, etc.) in the
network. At block 610, the reduced or full function device (which
may be in the proximity of the non-intelligent end device) may wake
from a "sleeping" or power-safe mode in response to receipt of the
transmitted signal. At block 615, the awakened reduced or full
function device performs appropriate sensing/data collection and
processing, as it is programmed to do. This may include decision
making with respect to how the device collects information, and
what the device, in turn, does with the collected information.
[0055] For example, the reduced or full function device may collect
image information, perform initial processing of that image
information and determine that additional surveillance is needed.
Based on this, the reduced or full function device may awaken other
devices/nodes in the network to perform additional tasks. In
another example, the reduced or full function device may determine
that collected information should be transmitted to another network
node, so that the information may be fused with other information
that is being collected by nodes in the network. More specifically,
smart storage using information fusion of sensor data allows the
sensor network to provide only "best of best" information for later
communication back to users. It may also provide for graceful loss
of event information if in-network storage capacities are exceeded.
In yet another example, the reduced or full function device may
determine that the collected information should be transmitted to a
network controller for exportation outside the network.
[0056] At decision block 620, if there is no need for the reduced
or full function device to communicate with other nodes within the
network, the routine skips forward to block 630. Otherwise, the
routine continues at block 625, where one or more network
controllers may compute and disseminate the routing optimization
information (e.g., as a result of request from one or more network
nodes). For example, in connection with low data rate network
features, the network controller may use hierarchical routing
protocols with table-driven optimizations to determine a "best
path" at any given time. Such routing optimizations may be
implemented using several techniques, such as a cluster tree
routing algorithm, an ad hoc on-demand distance vector (AODV)
routing protocol, a landmark ad hoc routing (LANMAR) protocol,
etc.
[0057] At block 630, select collected data intended for consumption
for end users is transferred from one or more network nodes
(including high function devices, reduced function devices, and/or
other devices) to one or more network controllers. Routing to nodes
such as the network controller may be performed using high data
rate network features and routing decisions may also be based on
table-driven routing information, in which the network controller
computes and disseminates routing table information to devices with
which it communicates. Once at the network controllers, the
information can be exported under an information exportation
scheme. For example, this may include real-time updates and/or
involve periodic uploads over a network connection. It is also
possible to use over-flight data collection mechanisms where
network type connections are not available. For example, power
efficient store-and-forward communications combined with WLAN
techniques allow not only for sensor/network coordination, but also
for over-flight data retrieval. The routine 600 then ends.
[0058] In some embodiments, a gateway node such as a network
controller manages the operation of the sensor network (e.g., by
dynamically creating new communication links between sensor nodes)
based on the needs of the mission, which can change throughout the
mission based on how the mission progresses. FIG. 7 is a system
diagram showing an example of a mission phase-based configuration
of a sensor network system in an embodiment. In particular, FIG. 7
illustrates the use of the sensor network across a mission having
three phases (702, 704, and 706). In some cases, these mission
phases may be determined as the mission progresses, based on
real-life conditions (as opposed to being known in advance). As
illustrated, not all the sensor nodes need to be active for the
entire mission. Thus, sensor nodes are configured and organized in
a manner that they best serve each mission phase. In some
embodiments, the system places sensor nodes that are not utilized
for a given mission into a deep sleep state to conserve power
resources. As subsequent mission phases begin, the system awakens
the appropriate sensor nodes for the particular mission phase into
active state. The demarcation between sensor nodes used within
different mission phases is not mutually exclusive (i.e., certain
sensor nodes may be used across multiple mission phases).
[0059] In some embodiments, the gateway nodes performs management
of the sensor nodes utilized for a given mission phase. Thus,
during any given point during the mission, the sensor network is
customized based on the needs of the particular mission phase. It
is possible that during a given mission phase, some of the sensor
nodes may become non-operational for various reasons, such as,
power storage capacity, adverse environmental conditions, or being
disabled by external entities such as the enemy. This may result in
reach-back disruption between the active sensor nodes to the
gateway node. Under such circumstances the gateway node analyzes
the topology map, computes the new routing hierarchy, and commands
the appropriate inactive sensor node(s) from deep sleep state into
active state. Following this, the gateway node updates the
appropriate active sensor nodes with the updated routing, primary
and alternate, information thereby enabling self healing operation
of the sensor network to fulfill the objectives of the current
mission phase(s).
[0060] From the foregoing, it will be appreciated that specific
embodiments of the invention have been described herein for
purposes of illustration, but that various modifications may be
made without deviating from the spirit and scope of the invention
and aspects of the invention described in the context of particular
embodiments may be combined or eliminated in other embodiments. For
example, while certain embodiments describe the use of sensor
networks operating in a military environment, the invention may be
implemented in the context of other environments where a need for
surveillance is established.
[0061] Although advantages associated with certain embodiments of
the invention have been described in the context of those
embodiments, other embodiments may also exhibit such advantages.
Additionally, none of the foregoing embodiments need necessarily
exhibit such advantages to fall within the scope of the invention.
Accordingly, the invention is not limited except as by the appended
claims.
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