U.S. patent application number 12/724104 was filed with the patent office on 2011-09-15 for techniques for self-organizing activity-diffusion-based wireless sensor network.
This patent application is currently assigned to SAMSUNG ELECTRONICS CO. LTD.. Invention is credited to Shu Wang.
Application Number | 20110222438 12/724104 |
Document ID | / |
Family ID | 44170479 |
Filed Date | 2011-09-15 |
United States Patent
Application |
20110222438 |
Kind Code |
A1 |
Wang; Shu |
September 15, 2011 |
TECHNIQUES FOR SELF-ORGANIZING ACTIVITY-DIFFUSION-BASED WIRELESS
SENSOR NETWORK
Abstract
Methods and wireless sensor nodes for aggregation-driven
topology formation in a Wireless Sensor Network (WSN) are provided.
A method for aggregation-driven topology formation in a WSN
includes aggregating sensor data by one or more first sensor nodes,
sending, by each of the one or more first sensor nodes, at least
one activity diffusion message to each of at least one neighboring
node of one or more second sensor nodes, wherein each activity
diffusion message includes an activity diffusion weight, receiving,
by each of the one or more second sensor nodes, respective of the
at least one activity diffusion message from at least one
neighboring node of the one or more first sensor nodes,
accumulating, by each of the one or more second sensor nodes,
activity diffusion weights included in the at least one activity
diffusion message received from the at least one neighboring node
of the one or more first sensor nodes, sending, by each of the one
or more first sensor nodes, the aggregated data to at least one of
the at least one neighboring node of the one or more second sensor
nodes, and receiving, by the at least one of the at least one
neighboring node of the one or more second sensor nodes, the
aggregated data from respective of the one or more first sensor
nodes.
Inventors: |
Wang; Shu; (Richardson,
TX) |
Assignee: |
SAMSUNG ELECTRONICS CO.
LTD.
Suwon-si
KR
|
Family ID: |
44170479 |
Appl. No.: |
12/724104 |
Filed: |
March 15, 2010 |
Current U.S.
Class: |
370/255 ;
370/254 |
Current CPC
Class: |
H04W 4/00 20130101; H04L
45/123 20130101; H04L 45/26 20130101; H04W 84/18 20130101; H04W
40/246 20130101 |
Class at
Publication: |
370/255 ;
370/254 |
International
Class: |
H04L 12/28 20060101
H04L012/28 |
Claims
1. A method for aggregation-driven topology formation in a Wireless
Sensor Network (WSN), the method comprising: aggregating sensor
data by one or more first sensor nodes; sending, by each of the one
or more first sensor nodes, at least one activity diffusion message
to each of at least one neighboring node of one or more second
sensor nodes, wherein each activity diffusion message includes an
activity diffusion weight; receiving, by each of the one or more
second sensor nodes, respective of the at least one activity
diffusion message from at least one neighboring node of the one or
more first sensor nodes; accumulating, by each of the one or more
second sensor nodes, activity diffusion weights included in the at
least one activity diffusion message received from the at least one
neighboring node of the one or more first sensor nodes; sending, by
each of the one or more first sensor nodes, the aggregated data to
at least one of the at least one neighboring node of the one or
more second sensor nodes; and receiving, by the at least one of the
at least one neighboring node of the one or more second sensor
nodes, the aggregated data from respective of the one or more first
sensor nodes.
2. The method of claim 1, wherein each of the one or more first
sensor nodes sends the activity diffusion message while aggregating
the data.
3. The method of claim 1, wherein the one or more second sensor
nodes comprise next-hop sensor nodes to the one or more first
sensor nodes.
4. The method of claim 1, wherein the activity diffusion weight
comprises at least one of a path history and an aggregation
history.
5. The method of claim 1, wherein the activity diffusion weight
comprises a temporal component that decays with time.
6. The method of claim 1, further comprising determining, by each
of the one or more second sensor nodes, activity diffusion metrics
by combining the accumulated activity diffusion weight with one or
more other factors, wherein the accumulated activity diffusion
weight and the one or more other factors comprise respective
coefficients when combined.
7. The method of claim 1, further comprising: sending, by each of
the one or more first sensor nodes, a probe message to each of the
at least one neighboring node of one or more second sensor nodes,
wherein the probe message includes a request for information on
activity diffusion metrics, and wherein the activity diffusion
metrics are based on an accumulated activity diffusion weight;
receiving, by each of the one or more second sensor nodes,
respective probe messages from the at least one neighboring node of
the one or more first sensor nodes; sending, by each of the one or
more second sensor nodes, information on the activity diffusion
metrics to the at least one neighboring node of the one or more
first sensor nodes; and receiving, by each of the one or more first
sensor nodes, information on respective activity diffusion metrics
of each of the at least one neighboring node of the one or more
second sensor nodes.
8. The method of claim 1, further comprising: determining, by each
of the one or more first sensor nodes, at least one sensor node of
the at least one neighboring node of the one or more second sensor
nodes comprising a highest activity diffusion metrics, wherein the
at least one of the at least one neighboring node of the one or
more second sensor nodes to which the aggregated data is sent
comprises the at least one sensor node of the at least one
neighboring node of the one or more second sensor nodes determined
to comprise the highest activity diffusion metrics.
9. The method of claim 1, wherein the at least one neighboring node
of the one or more second sensor nodes is a sensor node included in
a connection history list of respective one or more first sensor
nodes.
10. A method for aggregation-driven topology formation in a
Wireless Sensor Network (WSN), the method comprising: aggregating
sensor data by a first sensor node; sending, by the first sensor
node, at least one activity diffusion message to each of at least
one neighboring node of one or more second sensor nodes, wherein
each activity diffusion message includes an activity diffusion
weight; and sending, by the first sensor node, the aggregated data
to at least one of the one or more second sensor nodes.
11. The method of claim 10, wherein the first sensor node sends the
activity diffusion message while aggregating the data.
12. The method of claim 10, wherein the one or more second sensor
nodes comprise next-hop sensor nodes to the first sensor node.
13. The method of claim 10, wherein the activity diffusion weight
comprises a temporal component that decays with time.
14. The method of claim 10, further comprising: sending, by the
first sensor node, a probe message to each of the one or more
second sensor nodes, wherein the probe message includes a request
for information on activity diffusion metrics, wherein the activity
diffusion metrics are based on a combination of an accumulated
activity diffusion weight and one or more other factors, and
wherein the accumulated activity diffusion weight and the one or
more other factors comprise respective coefficients when combined;
and receiving, by the first sensor node, information on respective
activity diffusion metrics of each of the one or more second sensor
nodes.
15. The method of claim 10, further comprising: determining, by the
first sensor node, at least one sensor node of the one or more
second sensor nodes comprising a highest activity diffusion
metrics, wherein the at least one of the one or more second sensor
nodes to which the aggregated data is sent comprises the at least
one sensor node of the one or more second sensor nodes determined
to comprise the highest activity diffusion metrics.
16. A method for aggregation-driven topology formation in a
Wireless Sensor Network (WSN), the method comprising: receiving, by
a second sensor node, respective of at least one activity diffusion
message from one or more first sensor nodes, wherein each activity
diffusion message includes an activity diffusion weight;
accumulating, by the second sensor node, activity diffusion weights
included in the at least one activity diffusion messages received
from the one or more first sensor nodes; and receiving, by second
sensor node, aggregated data from respective at least one of the
one or more first sensor nodes.
17. The method of claim 16, wherein the second sensor node
comprises a next-hop sensor node to the one or more first sensor
nodes.
18. The method of claim 16, wherein the activity diffusion weight
comprises a temporal component that decays with time.
19. The method of claim 16, further comprising: receiving, by the
second sensor node, respective probe messages from at least one of
the one or more first sensor nodes, wherein each of the probe
messages includes a request for information on activity diffusion
metrics, wherein the activity diffusion metrics are based on a
combination of an accumulated activity diffusion weight and one or
more other factors, wherein the accumulated activity diffusion
weight and the one or more other factors comprise respective
coefficients when combined; and sending, by the second sensor node,
information on the activity diffusion metrics to the at least one
of the one or more first sensor nodes.
20. The method of claim 16, wherein the second sensor node
comprises a highest activity diffusion metrics among sensor nodes
receiving the at least one activity diffusion message from
respective at least one of the one or more first sensor nodes.
21. A Wireless Sensor Network (WSN) for aggregation-driven topology
formation, the WSN comprising: one or more first sensor nodes for
aggregating sensor data, for sending at least one activity
diffusion message to each of at least one neighboring node of one
or more second sensor nodes, wherein each activity diffusion
message includes an activity diffusion weight, and for sending the
aggregated data to at least one of the at least one neighboring
node of the one or more second sensor nodes; and the one or more
second sensor nodes for receiving respective of the at least one
activity diffusion message from at least one neighboring node of
the one or more first sensor nodes, for accumulating activity
diffusion weights included in the at least one activity diffusion
message received from the at least one neighboring node of the one
or more first sensor nodes; and for receiving, by the at least one
of the at least one neighboring node of the one or more second
sensor nodes, the aggregated data from respective of the one or
more first sensor nodes.
22. The WSN of claim 21, wherein each of the one or more first
sensor nodes sends the activity diffusion message while aggregating
the data.
23. The WSN of claim 21, wherein the one or more second sensor
nodes comprise next-hop sensor nodes to the one or more first
sensor nodes.
24. The WSN of claim 21, wherein the activity diffusion weight
comprises at least one of a path history and an aggregation
history.
25. The WSN of claim 21, wherein the activity diffusion weight
comprises a temporal component that decays with time.
26. The WSN of claim 21, wherein each of the one or more second
sensor nodes determine activity diffusion metrics by combining the
accumulated activity diffusion weight with one or more other
factors, wherein the accumulated activity diffusion weight and the
one or more other factors comprise respective coefficients when
combined.
27. The WSN of claim 21, wherein each of the one or more first
sensor nodes sends a probe message to each of the at least one
neighboring node of one or more second sensor nodes, wherein the
probe message includes a request for information on activity
diffusion metrics, and wherein the activity diffusion metrics are
based on an accumulated activity diffusion weight, and receive
information on respective activity diffusion metrics of each of the
at least one neighboring node of the one or more second sensor
nodes, and wherein each of the one or more second sensor nodes
receive respective probe messages from the at least one neighboring
node of the one or more first sensor nodes, and send information on
the activity diffusion metrics to the at least one neighboring node
of the one or more first sensor nodes.
28. The WSN of claim 21, wherein each of the one or more first
sensor nodes determine at least one sensor node of the at least one
neighboring node of the one or more second sensor nodes comprising
a highest activity diffusion metrics, and wherein the at least one
of the at least one neighboring node of the one or more second
sensor nodes to which the aggregated data is sent comprises the at
least one sensor node of the at least one neighboring node of the
one or more second sensor nodes determined to comprise the highest
activity diffusion metrics.
29. The WSN of claim 21, wherein the at least one neighboring node
of the one or more second sensor nodes is a sensor node included in
a connection history list of respective one or more first sensor
nodes.
30. A wireless sensor node apparatus for aggregation-driven
topology formation in a Wireless Sensor Network (WSN), the
apparatus comprising: a transceiver for receiving and transmitting
information; and a controller for controlling the transceiver, for
controlling to aggregate sensor data, for controlling to send at
least one activity diffusion message to each of at least one
neighboring node of one or more other sensor nodes, wherein each
activity diffusion message includes an activity diffusion weight,
and for controlling to send the aggregated data to at least one of
the one or more other sensor nodes.
31. The apparatus of claim 30, wherein the controller controls to
send the activity diffusion message while aggregating the data.
32. The apparatus of claim 30, wherein the one or more other sensor
nodes comprise next-hop sensor nodes to the first sensor node.
33. The apparatus of claim 30, wherein the activity diffusion
weight comprises a temporal component that decays with time.
34. The apparatus of claim 30, wherein the controller further
controls to sending a probe message to each of the one or more
other sensor nodes, wherein the probe message includes a request
for information on activity diffusion metrics, wherein the activity
diffusion metrics are based on a combination of an accumulated
activity diffusion weight and one or more other factors, and
wherein the accumulated activity diffusion weight and the one or
more other factors comprise respective coefficients when combined,
and wherein the controller further controls to receive information
on respective activity diffusion metrics of each of the one or more
other sensor nodes.
35. The apparatus of claim 30, wherein the controller further
controls to determine at least one sensor node of the one or more
other sensor nodes comprising a highest activity diffusion metrics,
and wherein the at least one of the one or more other sensor nodes
to which the aggregated data is sent comprises the at least one
sensor node of the one or more other sensor nodes determined to
comprise the highest activity diffusion metrics.
36. A wireless sensor node apparatus for aggregation-driven
topology formation in a Wireless Sensor Network (WSN), the
apparatus comprising: a transceiver for receiving and transmitting
information; and a controller for controlling the transceiver, for
controlling to receive respective of at least one activity
diffusion message from one or more other sensor nodes, wherein each
activity diffusion message includes an activity diffusion weight,
for controlling to accumulate activity diffusion weights included
in the at least one activity diffusion messages received from the
one or more other sensor nodes, and for controlling to receive
aggregated data from respective at least one of the one or more
other sensor nodes.
37. The apparatus of claim 36, wherein the second sensor node
comprises a next-hop sensor node to the one or more other sensor
nodes.
38. The apparatus of claim 36, wherein the activity diffusion
weight comprises a temporal component that decays with time.
39. The apparatus of claim 36, wherein the controller further
controls to receive respective probe messages from at least one of
the one or more other sensor nodes, wherein each of the probe
messages includes a request for information on activity diffusion
metrics, wherein the activity diffusion metrics are based on a
combination of an accumulated activity diffusion weight and one or
more other factors, wherein the accumulated activity diffusion
weight and the one or more other factors comprise respective
coefficients when combined; and wherein the controller further
controls to send information on the activity diffusion metrics to
the at least one of the one or more other sensor nodes.
40. The apparatus of claim 36, wherein the second sensor node
comprises a highest activity diffusion metrics among sensor nodes
receiving the at least one activity diffusion message from
respective at least one of the one or more other sensor nodes.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention relates to a Wireless Sensor Network
(WSN). More particularly, the present invention relates to
techniques for a self-organizing activity-diffusion-based WSN.
[0003] 2. Description of the Related Art
[0004] Recently, the concept of a Wireless Sensor Network (WSN) has
received considerable attention. A WSN typically includes a
collection of low-power transceivers (henceforth referred to as
sensor nodes) each having some type of sensor function for one or
more properties of an environment in which they are placed. The
term "environment" here has a very broad meaning and could include
any object or geographical area. Likewise, the range of properties
which might be sensed is wide, and includes any property that may
be indirectly or directly sensed, or determined based on the
sensing of one or more other properties.
[0005] Each sensor node is capable of transmitting sensor data,
usually as discrete packets, to any other devices in its vicinity,
usually to another sensor node. By relaying data from one sensor
node to another, the data can be directed to a so-called sink node
or base station. The sensor node may be fixed or mobile, and the
sink nodes may be fixed or mobile. Although the precise
communication standard used by the sensor nodes of a WSN is not
important, one suitable standard is Institute of Electrical and
Electronics Engineers (IEEE) 802.15.4 standard, an implementation
of which is referred to as ZigBee.
[0006] Depending upon the capabilities of the sink node, the data
can be forwarded from the sink node directly or indirectly to some
form of outside entity, typically via another network such as a
mobile telephone network or the Internet. Where the sink node is
able to communicate with another network it may also be referred to
as a gateway.
[0007] In some implementations, the terms sink node, base station
and gateway denote the same thing. In other implementations, the
terms sink node, base station and gateway denote distinct
functions, in which case, the sink node will communicate the
gathered data to a separate base station and/or gateway for further
transmission, possibly after some type of aggregation or other
processing.
[0008] Moreover, in some implementations, the sensor nodes (or a
subset thereof) are also capable of acting as the sink node.
Multiple sink nodes, and multiple gateways, may be present in a
WSN, but, for simplicity, a single sink node is assumed in the
following description.
[0009] In the present disclosure, the terms "sink node" and "base
station" are used synonymously to denote any type of data-gathering
entity in a WSN, whether or not it also acts as a gateway.
[0010] The WSN differs from a wireless mesh network and an ad hoc
network. Typically, the sensor nodes are unattended, have a low
computational ability, and are reliant on battery power. Thus,
power consumption of the sensor nodes is a major consideration and
the transmission of data is typically the most power-hungry
function of a sensor node. Therefore, the sensor nodes operate with
severe energy constraints. However, the sensor nodes may be Radio
Frequency IDentification (RFID)-based devices, which might not be
reliant on battery power. Nevertheless, since the available
transmission power of such devices is very low, similar
considerations apply.
[0011] One technique employed to conserve battery power is to
deactivate sensor nodes that are not currently engaged in sensing
or communication (including relaying). Thus, sensor nodes may
alternate between active and inactive states, for example, in
response to the presence or absence of a sensed property or
incoming data. In this way, the useful lifetime of the sensor can
be prolonged.
[0012] Another technique employed to conserve battery power is to
have sensor nodes only communicate with their nearest neighbors.
However, by limiting the communication of sensor nodes to only
their nearest neighbors, multi-hop techniques need to be used to
enable sensor data to reach the sink node by several different
routes. However, in employing this technique, the sensor nodes
transmit data in all directions indiscriminately without knowing or
caring which other nodes receive it. Accordingly, a WSN suffers
from the transmission of redundant data.
[0013] Data aggregation has been put forward as a useful solution
to address the limited energy constraints and redundant data. Data
aggregation exploits the fact that a sensor node consumes less
energy for data processing than for communication. Also, it
minimizes the number of transmissions and thereby conserves energy.
Instead of transmitting the packets of each individual sensor node
separately, each sensor node first combines the incoming data from
different sources en-route and then forwards the aggregated data to
the next node when its aggregation interval is reached.
[0014] In a WSN, the interplay between topology formation and data
aggregation is very important. Data aggregation schemes of the
related art separate the topology formation and data aggregation
from each other. In other words, a topology is formed first and
then data aggregation is performed based on the topology. However,
the pre-constructed topologies are not always the best structures
for efficient data aggregation. An aggregation topology according
to the related art will be discussed below with reference to FIG.
1.
[0015] FIG. 1 illustrates an aggregation topology according to the
related art.
[0016] Referring to FIG. 1, the communication paths of sensor data
collected by sensor nodes N.sub.1, N.sub.2 and N.sub.3 and
communicated to the sink node S.sub.1 are shown. Here, the
communication paths are formed based on the shortest paths for the
data to travel between the sensor nodes N.sub.1, N.sub.2 and
N.sub.3 and the sink node S.sub.1. The aggregation topology
employed here is referred to as a shortest path tree. By following
the shortest path, the packets from sensor nodes N.sub.1, N.sub.2
and N.sub.3 are routed separately to the sink node S.sub.1 and are
not able to be aggregated en-route. In this case, this topology
does not yield the most efficient result. Here, it would have been
more efficient to perform data-aggregation and then have the
aggregated data communicated to the sink node S.sub.1.
[0017] Therefore, a need exists for a data-aggregation driven
topology for efficient data aggregation.
SUMMARY OF THE INVENTION
[0018] An aspect of the present invention is to address at least
the above-mentioned problems and/or disadvantages and to provide at
least the advantages described below. Accordingly, an aspect of the
present invention is to provide techniques for a self-organizing
activity-diffusion-based Wireless Sensor Network (WSN).
[0019] In accordance with an aspect of the present invention, a
method for aggregation-driven topology formation in a WSN is
provided. The method includes aggregating sensor data by one or
more first sensor nodes, sending, by each of the one or more first
sensor nodes, at least one activity diffusion message to each of at
least one neighboring node of one or more second sensor nodes,
wherein each activity diffusion message includes an activity
diffusion weight, receiving, by each of the one or more second
sensor nodes, respective of the at least one activity diffusion
message from at least one neighboring node of the one or more first
sensor nodes, accumulating, by each of the one or more second
sensor nodes, activity diffusion weights included in the at least
one activity diffusion message received from the at least one
neighboring node of the one or more first sensor nodes, sending, by
each of the one or more first sensor nodes, the aggregated data to
at least one of the at least one neighboring node of the one or
more second sensor nodes, and receiving, by the at least one of the
at least one neighboring node of the one or more second sensor
nodes, the aggregated data from respective of the one or more first
sensor nodes.
[0020] In accordance with another aspect of the present invention,
a method for aggregation-driven topology formation in a WSN is
provided. The method include aggregating sensor data by a first
sensor node, sending, by the first sensor node, at least one
activity diffusion message to each of at least one neighboring node
of one or more second sensor nodes, wherein each activity diffusion
message includes an activity diffusion weight, and sending, by the
first sensor node, the aggregated data to at least one of the one
or more second sensor nodes.
[0021] In accordance with yet another aspect of the present
invention, a method for aggregation-driven topology formation in a
WSN is provided. The method includes receiving, by a second sensor
node, respective of at least one activity diffusion message from
one or more first sensor nodes, wherein each activity diffusion
message includes an activity diffusion weight, accumulating, by the
second sensor node, activity diffusion weights included in the at
least one activity diffusion messages received from the one or more
first sensor nodes, and receiving, by second sensor node,
aggregated data from respective at least one of the one or more
first sensor nodes.
[0022] In accordance with still another aspect of the present
invention, a WSN for aggregation-driven topology formation is
provided. The WSN includes one or more first sensor nodes and one
or more second sensor nodes. The one or more first sensor nodes
aggregate sensor data, send at least one activity diffusion message
to each of at least one neighboring node of one or more second
sensor nodes, wherein each activity diffusion message includes an
activity diffusion weight, and send the aggregated data to at least
one of the at least one neighboring node of the one or more second
sensor nodes. The one or more second sensor nodes receive
respective of the at least one activity diffusion message from at
least one neighboring node of the one or more first sensor nodes,
accumulate activity diffusion weights included in the at least one
activity diffusion message received from the at least one
neighboring node of the one or more first sensor nodes, receive, by
the at least one of the at least one neighboring node of the one or
more second sensor nodes, the aggregated data from respective of
the one or more first sensor nodes.
[0023] In accordance with another aspect of the present invention,
wireless sensor node apparatus for aggregation-driven topology
formation in a WSN is provided. The apparatus includes a
transceiver for receiving and transmitting information, and a
controller. The controller controls the transceiver, controls to
aggregate sensor data, controls to send at least one activity
diffusion message to each of at least one neighboring node of one
or more other sensor nodes, wherein each activity diffusion message
includes an activity diffusion weight, and controls to send the
aggregated data to at least one of the one or more other sensor
nodes.
[0024] In accordance with another aspect of the present invention,
wireless sensor node apparatus for aggregation-driven topology
formation in a WSN is provided. The apparatus includes a
transceiver for receiving and transmitting information, and a
controller. The controller controls the transceiver, controls to
receive respective of at least one activity diffusion message from
one or more other sensor nodes, wherein each activity diffusion
message includes an activity diffusion weight, controls to
accumulate activity diffusion weights included in the at least one
activity diffusion messages received from the one or more other
sensor nodes, and controls to receive aggregated data from
respective at least one of the one or more other sensor nodes.
[0025] Other aspects, advantages, and salient features of the
invention will become apparent to those skilled in the art from the
following detailed description, which, taken in conjunction with
the annexed drawings, discloses exemplary embodiments of the
invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0026] The above and other aspects, features, and advantages of
certain exemplary embodiments of the present invention will be more
apparent from the following description taken in conjunction with
the accompanying drawings, in which:
[0027] FIG. 1 illustrates an aggregation topology according to the
related art;
[0028] FIG. 2 illustrates activity diffusion according to an
exemplary embodiment of the present invention;
[0029] FIG. 3 illustrates a sensor node receiving activity
diffusion messages according to an exemplary embodiment of the
present invention;
[0030] FIG. 4 illustrates aggregation-driven topology formation
according to an exemplary embodiment of the present invention;
[0031] FIG. 5 illustrates the determination of activity diffusion
metrics based on accumulated activity diffusion weights and other
factors according to an exemplary embodiment of the present
invention;
[0032] FIG. 6 is a block diagram illustrating a sensor node in a
Wireless Sensor Network (WSN) according to an exemplary embodiment
of the present invention.
[0033] Throughout the drawings, like reference numerals will be
understood to refer to like parts, components, and structures.
DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS
[0034] The following description with reference to the accompanying
drawings is provided to assist in a comprehensive understanding of
exemplary embodiments of the invention as defined by the claims and
their equivalents. It includes various specific details to assist
in that understanding but these are to be regarded as merely
exemplary. Accordingly, those of ordinary skill in the art will
recognize that various changes and modifications of the embodiments
described herein can be made without departing from the scope and
spirit of the invention. In addition, descriptions of well-known
functions and constructions are omitted for clarity and
conciseness.
[0035] The terms and words used in the following description and
claims are not limited to the bibliographical meanings, but, are
merely used by the inventor to enable a clear and consistent
understanding of the invention. Accordingly, it should be apparent
to those skilled in the art that the following description of
exemplary embodiments of the present invention are provided for
illustration purpose only and not for the purpose of limiting the
invention as defined by the appended claims and their
equivalents.
[0036] It is to be understood that the singular forms "a," "an,"
and "the" include plural referents unless the context clearly
dictates otherwise. Thus, for example, reference to "a component
surface" includes reference to one or more of such surfaces.
[0037] By the term "substantially" it is meant that the recited
characteristic, parameter, or value need not be achieved exactly,
but that deviations or variations, including for example,
tolerances, measurement error, measurement accuracy limitations and
other factors known to those of skill in the art, may occur in
amounts that do not preclude the effect the characteristic was
intended to provide.
[0038] Exemplary embodiments of the present invention described
below relate to techniques for a self-organizing
activity-diffusion-based Wireless Sensor Network (WSN).
[0039] It should be understood that the following description might
refer to terms utilized in various standards merely for simplicity
of explanation. For example, the following description may refer to
terms utilized in the Institute of Electrical and Electronics
Engineers (IEEE) 802.15.4 standard. However, this description
should not be interpreted limiting the present invention to
application with the IEEE 802.15.4 standard. Independent of the
mechanism used to implement a self-organizing
activity-diffusion-based WSN, it is advantageous for that ability
to conform to a standardized mechanism.
[0040] Exemplary embodiments of the present invention are hereafter
described with a limited number and types of sensor nodes or
limited use cases for ease of explanation. However, the present
invention is equally applicable to an arbitrary number and types of
nodes and other related use cases. Further, exemplary embodiments
of the present invention are hereafter described under the
assumption that the sensor nodes are location-aware. Herein, the
sensor nodes may obtain their location information through the use
of a Global Positioning System (GPS), distance or hop count
techniques, or any other technique by which the sensor nodes may be
aware of their location.
[0041] Exemplary embodiments of the present invention employ an
activity diffusion technique to form aggregation-driven sensor node
neighborhoods and encourage spatial aggregation (meet at the same
place) and temporal aggregation (meet at the same time). In the
activity diffusion technique, while all the sensor nodes act
individually, from a global perspective, the sensor nodes cooperate
to achieve efficient data aggregation. When the activity diffusion
technique is implemented according to exemplary embodiments of the
present invention, the resulting WSN is scalable, adaptive and
robust.
[0042] In the activity diffusion technique, while a sensor node or
group of sensor nodes are active and performing data aggregation,
their activity will simultaneously influence their next-hop
neighbor formation. More specifically, when a sensor node is in the
aggregation status, its activity is diffused to its immediate
neighborhoods, in a similar manner as a wave-front. An example of
activity diffusion is discussed below with reference to FIG. 2.
[0043] FIG. 2 illustrates activity diffusion according to an
exemplary embodiment of the present invention.
[0044] Referring to FIG. 2, sensor nodes N.sub.1, N.sub.2 and
N.sub.3 and sensor nodes K.sub.1, K.sub.2, K.sub.3, K.sub.4 and
K.sub.5 are shown. Here, as sensor nodes N.sub.1, N.sub.2 and
N.sub.3 perform data aggregation, they send activity diffusion
messages to their next-hop neighborhoods. In this case, the
activity diffusion messages are spread to sensor nodes K.sub.1,
K.sub.2, K.sub.3, K.sub.4 and K.sub.5. More specifically, sensor
node N.sub.1 sends an activity diffusion message to its neighbor
sensor nodes K.sub.1, K.sub.2, and K.sub.3, sensor node N.sub.2
sends an activity diffusion message to its neighbor sensor nodes
K.sub.2, K.sub.3, and K.sub.4, and sensor node N.sub.3 sends an
activity diffusion message to its neighbor sensor nodes K.sub.3,
K.sub.4, and K.sub.5. Each of the activity diffusion messages
includes an activity diffusion weight of the sensor node from which
it was transmitted. In an exemplary embodiment of the present
invention, the activity diffusion messages may include additional
information. An example of a sensor node receiving activity
diffusion messages is described below with reference to FIG. 3.
[0045] FIG. 3 illustrates a sensor node receiving activity
diffusion messages according to an exemplary embodiment of the
present invention.
[0046] Referring to FIG. 3, activity diffusion weights 1, 2, 3 and
4 are sent in corresponding activity diffusion messages to an
inactive sensor node in the next layer (i.e., a sensor node that is
one hop closer to the sink node). When the sensor node in the next
layer receives the activity diffusion messages, it accumulates the
activity diffusion weights that are included in the activity
diffusion messages. The accumulated activity diffusion weights are
used to determine activity diffusion metrics of the senor node. In
this example, the activity diffusion metrics only include the
accumulated activity diffusion weights. When the sensor node's
activity diffusion metrics are greater than a threshold, it will
become an aggregation candidate node.
[0047] When a sensor node in the previous layer finishes its data
aggregation (i.e., its aggregation interval is almost reached), the
sensor node selects its neighbor from the aggregation candidate
nodes in the next layer. The higher the activity diffusion metrics
an aggregation candidate node has, the higher the probability it
will be chosen. The sensor node in the previous layer may determine
which sensor nodes are aggregation candidate nodes and their
corresponding activity diffusion metrics by sending a probe message
to its next layer neighbors. In response to the probe message, the
neighboring nodes send their current activity diffusion metrics.
Here it is assumed that each node maintains a set of neighbor node
addresses by exchanging address information with its neighbors. An
example of aggregation-driven topology formation is described below
with reference to FIG. 4.
[0048] FIG. 4 illustrates aggregation-driven topology formation
according to an exemplary embodiment of the present invention.
[0049] Referring to FIG. 4, sensor nodes N.sub.1, N.sub.2 and
N.sub.3 and sensor nodes K.sub.1, K.sub.2, K.sub.3, K.sub.4 and
K.sub.5 are shown. Here, sensor nodes N.sub.1, N.sub.2 and N.sub.3
spread activity diffusion messages to sensor nodes K.sub.1,
K.sub.2, K.sub.3, K.sub.4 and K.sub.5 while performing data
aggregation. The activity diffusion messages from sensor nodes
N.sub.1, N.sub.2 and N.sub.3 have the activity diffusion weights of
f(N.sub.1), f(N.sub.2) and f(N.sub.3), respectively. More
specifically, sensor node N.sub.1 sends an activity diffusion
message with an activity diffusion weight of f(N.sub.1) to its
neighbor sensor nodes K.sub.1, K.sub.2, and K.sub.3, sensor node
N.sub.2 sends an activity diffusion message with an activity
diffusion weight of f(N.sub.2) to its neighbor sensor nodes
K.sub.2, K.sub.3, and K.sub.4, and sensor node N.sub.3 sends an
activity diffusion message with an activity diffusion weight of
f(N.sub.3) to its neighbor sensor nodes K.sub.3, K.sub.4, and
K.sub.5. Each sensor node of the sensor nodes K.sub.1, K.sub.2,
K.sub.3, K.sub.4 and K.sub.5 in the next layer receives the
activity diffusion messages and accumulates the activity diffusion
weights to determine its activity diffusion metrics. After the
activity diffusion weights are accumulated, sensor node K.sub.1 has
activity diffusion metrics with an accumulated activity diffusion
weight of f(N.sub.1), sensor node K.sub.2 has activity diffusion
metrics with an accumulated activity diffusion weight of
f(N.sub.1)+f(N.sub.2), sensor node K.sub.3 has activity diffusion
metrics with an accumulated activity diffusion weight of
f(N.sub.1)+f(N.sub.2)+f(N.sub.3), sensor node K.sub.4 has activity
diffusion metrics with an accumulated activity diffusion weight of
f(N.sub.2)+f(N.sub.3), and sensor node K.sub.5 has activity
diffusion metrics with an accumulated activity diffusion weight of
f(N.sub.3).
[0050] When sensor node N.sub.1, N.sub.2, or N.sub.3 finishes data
aggregation and is ready to send its aggregated data, it chooses
the neighbor (next-hop) node with the highest activity diffusion
metrics. In this case, assuming that each of the activity diffusion
messages f(N.sub.1), f(N.sub.2) and f(N.sub.3) are not negative,
sensor node K.sub.3 has the highest activity diffusion metrics with
an accumulated activity diffusion weight of
f(N.sub.1)+f(N.sub.2)+f(N.sub.3). By choosing sensor node K.sub.3,
spatial aggregation (meet at the same place) is achieved.
[0051] The activity diffusion weight sent by a node in an activity
diffusion message may be based on any number of the same or
different criteria. For example, the activity diffusion weight may
be based on at least one of node aggregation history and path
history of the aggregated data received by the node. Here, the
activity diffusion weight sent by a sensor node, for aggregated
data it received, may correspond to at least one of an amount of
the aggregated data's aggregation history (e.g., the number of
previous nodes from which aggregated data of those nodes are
included) and a length of the aggregated data's path history (e.g.,
the number of hops the aggregated data has passed through). In this
example, the activity diffusion weight sent out by the sensor node
is larger if the amount of aggregation history is greater and/or
the length of the path history is longer.
[0052] In order to address temporal aggregation (meet at the same
time), each activity diffusion weight may have temporal information
and may decay with time. For example, if sensor node N.sub.1,
N.sub.2, or N.sub.3 are active at about the same time, there will
be a strong accumulated activity diffusion weight, and thus strong
activity diffusion metrics, at sensor node K.sub.3, which
encourages the aggregation to meet at substantially the same time
period.
[0053] In addition, instead of the activity diffusion metrics only
including accumulated activity diffusion weights, the activity
diffusion metrics may be determined by combining the accumulated
activity diffusion weights with one or more other factors. An
example of determining activity diffusion metrics using other
factors is described below with reference to FIG. 5.
[0054] FIG. 5 illustrates the determination of activity diffusion
metrics based on accumulated activity diffusion weights and other
factors according to an exemplary embodiment of the present
invention.
[0055] Referring to FIG. 5, sensor nodes N.sub.1, N.sub.2 and
N.sub.3 and sensor nodes K.sub.1, K.sub.2, K.sub.3, K.sub.4 and
K.sub.5 are shown. Here, sensor nodes N.sub.1, N.sub.2 and N.sub.3
spread activity diffusion messages to sensor nodes K.sub.1,
K.sub.2, K.sub.3, K.sub.4 and K.sub.5 while performing data
aggregation. More specifically, sensor node N.sub.1 sends an
activity diffusion message to sensor nodes K.sub.1, K.sub.2, and
K.sub.3, sensor node N.sub.2 sends an activity diffusion message to
sensor nodes K.sub.2, K.sub.3, and K.sub.4, and sensor node N.sub.3
sends an activity diffusion message to sensor nodes K.sub.3,
K.sub.4, and K.sub.5. Each sensor node of the sensor nodes K.sub.1,
K.sub.2, K.sub.3, K.sub.4 and K.sub.5 in the next layer receives
the activity diffusion messages and accumulates the activity
diffusion weights included in the activity diffusion messages. The
accumulated activity diffusion weights are combined with one or
more other factors to determine activity diffusion metrics. The one
or more other factors may include one or more of node energy, a
load-balance-factor, a node degree, etc.
[0056] Further, respective coefficients may be applied to any
number of the components of the activity diffusion metrics, namely
the accumulated activity diffusion weights and the one or more
other factors. In one exemplary implementation, in order to
emphasize the data aggregation factor, a higher coefficient may be
applied to the accumulated activity diffusion weight (e.g.,
activity_metric_val=C.sub.a*Activity Diffusion
Weight+C.sub.b*Energy Factor+ . . . +C.sub.x*Factor X). In another
example, if a sensor node has a higher energy, a high diffusion
weight and a low traffic load, the sensor node is more likely to be
chosen as a next-hop neighbor for routing and data aggregation.
While there may be a respective coefficient applied to any number
of the components of the activity diffusion metrics, there may
alternatively or in addition be a coefficient commonly applied to
the activity diffusion metrics.
[0057] When sensor node N.sub.1, N.sub.2, or N.sub.3 finishes data
aggregation and is ready to send its aggregated data, it chooses
the neighbor (next-hop) node with the highest aggregation activity
diffusion metrics. In this case, sensor node K.sub.3 is assumed to
have the highest activity diffusion metrics. By choosing sensor
node K.sub.3, spatial aggregation (meet at the same place) is
achieved.
[0058] Still further, temporal aggregation (meet at the same time)
may be employed such that each of the activity diffusion metrics
may have temporal information and may decay with time. The temporal
information may be associated with the activity diffusion metrics
and/or one or more of the components of the activity diffusion
metrics, namely the accumulated activity diffusion weights and/or
one or more other factors.
[0059] In addition, instead of or in addition to using activity
diffusion weights (and/or activity diffusion metrics) a sensor node
may choose a next hop sensor node based on a connection history
with one of the aggregation candidate nodes. For example, if a
sensor node among aggregation candidate nodes is always (or
frequently) selected as the next hop node, that node may be
selected as the next hop node based on the connection history.
Herein, the sensor node may retain a list of sensor nodes that are
always (or frequently) selected as a next hop node. The list may
further include information used to determine an order of the
sensor nodes included in the list. The information may be used to
select a sensor node from a plurality of aggregation candidate
nodes that are included in the list. Similarly, the list may
include sensor nodes that are never (or rarely) selected as a next
hop node. In this case, a node on the list may not be selected to
be selected as the next hop node based on the connection
history.
[0060] In addition, a sensor node may limit its aggregation
candidate nodes based on a connection history with one or more of
its neighboring sensor nodes. For example, if a set of sensor nodes
among neighboring sensor nodes is always (or frequently) selected
as the aggregation candidate nodes and/or next hop nodes, those
nodes may be selected as the aggregation candidate nodes (or a
portion thereof) based on the connection history. Herein, the
sensor node may retain a list of sensor nodes that are always (or
frequently) selected as aggregation candidate nodes and/or next hop
nodes. The list may further include information used to determine
an order of the sensor nodes included in the list. The information
may be used to select a smaller set of sensor nodes from a
plurality of neighboring sensor nodes that are included in the
list. Similarly, the list may include sensor nodes that are never
(or rarely) selected as an aggregation candidate node and/or a next
hop node. In this case, a node on the list may not be selected to
be selected as the aggregation candidate node based on the
connection history.
[0061] A structure of a sensor node will be described below with
reference to FIG. 6.
[0062] FIG. 6 is a block diagram illustrating a sensor node in a
WSN according to an exemplary embodiment of the present
invention.
[0063] Referring to FIG. 6, the sensor node 600 includes a
transceiver 610, a controller 620, a storage unit 630, and a sensor
640. The sensor node 600 may include any number of additional
structural elements, such as a power supply, a battery, a housing,
etc. However, a description of additional structural elements of
the sensor node 600 is omitted for conciseness.
[0064] The transceiver 610 receives and transmits information from
and to other sensor nodes via one or more communication mediums.
The communication mediums may be any of Radio Frequency (RF)
communications, communications via a capacitive coupling,
communications via an inductive coupling, visible light
communications, infrared communications, wired communications, or
any other communications medium. The transceiver includes the
appropriate hardware and/or software to communicate via the one or
more communication mediums being employed, such as an antenna, a
duplexer, a communication processor, an analog to digital
convertor, a digital to analog convertor, a demodulator, a
modulator, a decoder, a coder, etc. Further, the transceiver may
include a plurality of transceivers. In addition, the transceiver
may include at least one of a receiver and a transmitter.
[0065] The controller 620 controls overall operations of the sensor
node 600. The operations of sensor node 600 include any of the
operations explicitly or implicitly described herein as being
performed by a sensor node. Further, the controller controls the
operations of and communicates with the transceiver 610, storage
unit 630 and sensor 640.
[0066] The storage unit 630 stores programs required for overall
operations of the sensor node 600 and various data including any of
the data discussed herein as being received, transmitted, retained
or used by a sensor node.
[0067] The sensor 640 senses a range of properties. The sensor 640
may be omitted or deactivated in one or more sensor nodes of a
WSN.
[0068] Thereby, exemplary embodiments of the present invention
apply an activity diffusion technique to form a self-organizing
aggregation driven WSN. When a node performs data aggregation, the
node simultaneously spreads its activity diffusion messages to its
neighbors in the next layer. The sensor nodes in the next layer
accumulate the activity diffusion weights and become an aggregation
candidate node if its diffusion metrics are greater than a
threshold (e.g., when the accumulated activity diffusion weights
are greater than a threshold). When the node in the previous layer
finishes its data aggregation, the sensor node selects its neighbor
from the aggregation candidate nodes in the next layer. By using
the activity diffusion approach, an aggregation-driven topology is
dynamically formed that encourages temporal and spatial data
aggregation. In addition, exemplary embodiments of the present
invention are advantageous in that they are scalable, yield
adaptive and efficient aggregation, are self-organizing, and
robust. More specifically, exemplary embodiments of the present
invention are scalable in that the algorithm is decentralized and
self-organized. Thus, the resulting WSN is scalable and easily
provides for the addition of new nodes. The exemplary embodiments
of the present invention yield adaptive and efficient aggregation
in that an aggregation-driven topology is formed dynamically. Thus,
the exemplary embodiments of the present invention are suitable for
dynamic scenarios and for both static and mobile WSNs. The
exemplary embodiments of the present invention are self-organizing
in that each sensor node uses simple neighbor-to-neighbor
interactions and all sensor nodes together achieve the goal of
efficient data aggregation. The exemplary embodiments of the
present invention are robust in that, since no fixed topology needs
to be maintained, the WSN is robust to individual failures.
[0069] Certain aspects of the present invention may also be
embodied as computer readable code on a computer readable recording
medium. A computer readable recording medium is any data storage
device that can store data, which can be thereafter read by a
computer system. Examples of the computer readable recording medium
include Read-Only Memory (ROM), Random-Access Memory (RAM),
CD-ROMs, magnetic tapes, floppy disks, and optical data storage
devices. The computer readable recording medium can also be
distributed over network coupled computer systems so that the
computer readable code is stored and executed in a distributed
fashion. Also, functional programs, code, and code segments for
accomplishing the present invention can be easily construed by
programmers skilled in the art to which the present invention
pertains.
[0070] While the invention has been shown and described with
reference to certain exemplary embodiments thereof, it will be
understood by those skilled in the art that various changes in form
and details may be made therein without departing from the spirit
and scope of the invention as defined by the appended claims and
their equivalents.
* * * * *