U.S. patent application number 11/032336 was filed with the patent office on 2006-07-13 for workflow decision management with heuristics.
Invention is credited to William A. Brown, Richard William Muirhead, Francis Xavier Reddington.
Application Number | 20060156276 11/032336 |
Document ID | / |
Family ID | 36654810 |
Filed Date | 2006-07-13 |
United States Patent
Application |
20060156276 |
Kind Code |
A1 |
Brown; William A. ; et
al. |
July 13, 2006 |
Workflow decision management with heuristics
Abstract
Methods, systems, and computer program products are provided for
workflow decision management. Embodiments typically include
maintaining a device state history; identifying a device usage
pattern in dependence upon the device state history; identifying a
derived scenario in dependence upon the device usage pattern; and
selecting a heuristic in dependence upon the derived scenario. In
typical embodiments, the heuristic has a tolerance. Embodiments
also include identifying a workflow in dependence upon the selected
heuristic and executing the workflow in dependence upon the
tolerance.
Inventors: |
Brown; William A.; (Raleigh,
NC) ; Muirhead; Richard William; (Tyler, TX) ;
Reddington; Francis Xavier; (Richmond, VA) |
Correspondence
Address: |
INTERNATIONAL CORP (BLF)
c/o BIGGERS & OHANIAN, LLP
P.O. BOX 1469
AUSTIN
TX
78767-1469
US
|
Family ID: |
36654810 |
Appl. No.: |
11/032336 |
Filed: |
January 10, 2005 |
Current U.S.
Class: |
717/104 |
Current CPC
Class: |
G06Q 10/06 20130101 |
Class at
Publication: |
717/104 |
International
Class: |
G06F 9/44 20060101
G06F009/44 |
Claims
1. A method for workflow decision management, the method
comprising: maintaining a device state history; identifying a
device usage pattern in dependence upon the device state history;
identifying a derived scenario in dependence upon the device usage
pattern; selecting a heuristic in dependence upon the derived
scenario; wherein the heuristic has a tolerance; identifying a
workflow in dependence upon the selected heuristic; and executing
the workflow in dependence upon the tolerance.
2. The method of claim 1 wherein maintaining a device state history
further comprises recording a plurality of attribute values for a
device.
3. The method of claim 1 wherein identifying a device usage pattern
in dependence upon the device state history further comprises
comparing the device state history with a plurality of device usage
patterns records.
4. The method of claim 1 wherein identifying a derived scenario in
dependence upon the device usage pattern further comprises
retrieving a derived scenario ID from a derived scenario table.
5. The method of claim 1 wherein selecting a heuristic in
dependence upon the derived scenario further comprises reading a
heuristic ID from a derived scenario record.
6. The method of claim 1 wherein selecting a heuristic in
dependence upon the derived scenario further comprises retrieving a
heuristic ID from a heuristic table.
7. The method of claim 1 wherein identifying a workflow in
dependence upon the selected heuristic comprises retrieving a
workflow ID from a heuristic record.
8. The method of claim 1 wherein executing the workflow in
dependence upon the tolerance further comprises sending a message
to a device.
9. The method of claim 1 wherein executing the workflow in
dependence upon the tolerance further comprises calling a member
method in a device class.
10. A system for workflow decision management, the system
comprising: means for maintaining a device state history; means for
identifying a device usage pattern in dependence upon the device
state history; means for identifying a derived scenario in
dependence upon the device usage pattern; means for selecting a
heuristic in dependence upon the derived scenario; wherein the
heuristic has a tolerance; means for identifying a workflow in
dependence upon the selected heuristic; and means for executing the
workflow in dependence upon the tolerance.
11. The system of claim 10 wherein means for maintaining a device
state history further comprises means for recording a plurality of
attribute values for a device.
12. The system of claim 10 wherein means for identifying a device
usage pattern in dependence upon the device state history further
comprises means for comparing the device state history with a
plurality of device usage patterns records.
13. The system of claim 10 wherein means for identifying a derived
scenario in dependence upon the device usage pattern further
comprises means for retrieving a derived scenario ID from a derived
scenario table.
14. The system of claim 10 wherein means for selecting a heuristic
in dependence upon the derived scenario further comprises means for
reading a heuristic ID from a derived scenario record.
15. The system of claim 10 wherein means for selecting a heuristic
in dependence upon the derived scenario further comprises means for
retrieving a heuristic ID from a heuristic table.
16. The system of claim 10 wherein means for identifying a workflow
in dependence upon the selected heuristic further comprises means
for retrieving a workflow ID from a heuristic record.
17. The system of claim 10 wherein means for executing the workflow
in dependence upon the tolerance further comprises means for
sending a message to a device.
18. The system of claim 10 wherein means for executing the workflow
in dependence upon the tolerance further comprises means for
calling a member system in a device class.
19. A computer program product for workflow decision management,
the computer program product comprising: a recording medium; means,
recorded on the recording medium, for maintaining a device state
history; means, recorded on the recording medium, for identifying a
device usage pattern in dependence upon the device state history;
means, recorded on the recording medium, for identifying a derived
scenario in dependence upon the device usage pattern; means,
recorded on the recording medium, for selecting a heuristic in
dependence upon the derived scenario; wherein the heuristic has a
tolerance; means, recorded on the recording medium, for identifying
a workflow in dependence upon the selected heuristic; and means,
recorded on the recording medium, for executing the workflow in
dependence upon the tolerance.
20. The computer program product of claim 19 wherein means,
recorded on the recording medium, for maintaining a device state
history further comprises means, recorded on the recording medium,
for recording a plurality of attribute values for a device.
21. The computer program product of claim 19 wherein means,
recorded on the recording medium, for identifying a device usage
pattern in dependence upon the device state history further
comprises means, recorded on the recording medium, for comparing
the device state history with a plurality of device usage patterns
records.
22. The computer program product of claim 19 wherein means,
recorded on the recording medium, for identifying a derived
scenario in dependence upon the device usage pattern further
comprises means, recorded on the recording medium, for retrieving a
derived scenario ID from a derived scenario table.
23. The computer program product of claim 19 wherein means,
recorded on the recording medium, for selecting a heuristic in
dependence upon the derived scenario further comprises means,
recorded on the recording medium, for reading a heuristic ID from a
derived scenario record.
24. The computer program product of claim 19 wherein means,
recorded on the recording medium, for selecting a heuristic in
dependence upon the derived scenario further comprises means,
recorded on the recording medium, for retrieving a heuristic ID
from a heuristic table.
25. The computer program product of claim 19 wherein means,
recorded on the recording medium, for identifying a workflow in
dependence upon the selected heuristic further comprises means,
recorded on the recording medium, for retrieving a workflow ID from
a heuristic record.
26. The computer program product of claim 19 wherein means,
recorded on the recording medium, for executing the workflow in
dependence upon the tolerance further comprises means, recorded on
the recording medium, for sending a message to a device.
27. The computer program product of claim 19 wherein means,
recorded on the recording medium, for executing the workflow in
dependence upon the tolerance further comprises means, recorded on
the recording medium, for calling a member computer program product
in a device class.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The field of the invention is data processing, or, more
specifically, methods, systems, and products for workflow decision
management.
[0003] 2. Description of Related Art
[0004] Conventional networks contain various networked devices.
User's often use the various devices, or adjust particular settings
of the devices, in accordance with consistent patterns and
scenarios of device usage. Despite routinely using devices
according to these consistent patterns and scenarios of device
usage, conventional networked devices still often require user
intervention to change attribute values of a device. It would be
advantageous if there were a method of workflow decision management
that used workflows to change in values of device attributes in a
network in dependence upon identified patterns of usage and
identified scenarios that did not require user intervention.
SUMMARY OF THE INVENTION
[0005] Methods, systems, and computer program products are provided
for workflow decision management. Embodiments typically include
maintaining a device state history, identifying a device usage
pattern in dependence upon the device state history, identifying a
derived scenario in dependence upon the device usage pattern, and
selecting a heuristic in dependence upon the derived scenario. In
typical embodiments, the heuristic has a tolerance. Embodiments
also include identifying a workflow in dependence upon the selected
heuristic and executing the workflow in dependence upon the
tolerance.
[0006] In typical embodiments of the present invention, maintaining
a device state history includes recording a plurality of attribute
values for a device. In many embodiments, identifying a device
usage pattern in dependence upon the device state history includes
comparing the device state history with a plurality of device usage
patterns records. In some embodiments, identifying a derived
scenario in dependence upon the device usage pattern includes
retrieving a derived scenario ID from a derived scenario table.
[0007] In typical embodiments, selecting a heuristic in dependence
upon the derived scenario is carried out by reading a heuristic ID
from a derived scenario record. In some embodiments, selecting a
heuristic in dependence upon the derived scenario includes
retrieving a heuristic ID from a heuristic table. In many
embodiments, identifying a workflow in dependence upon the selected
heuristic includes retrieving a workflow ID from a heuristic
record.
[0008] In many embodiments, executing the workflow in dependence
upon the tolerance is carried out by sending a message to a device.
In some embodiments, executing the workflow in dependence upon the
tolerance is carried out by calling a member method in a device
class.
[0009] The foregoing and other objects, features and advantages of
the invention will be apparent from the following more particular
descriptions of exemplary embodiments of the invention as
illustrated in the accompanying drawings wherein like reference
numbers generally represent like parts of exemplary embodiments of
the invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] FIG. 1 depicts an exemplary data processing system capable
of workflow decision management according to embodiments of the
present invention.
[0011] FIG. 2 sets forth a block diagram of an exemplary device
useful in implementing workflow decision management according to
embodiments of the present invention.
[0012] FIG. 3 is a block diagram illustrating exemplary data
structures useful in implementing methods of workflow decision
management according to aspects of the present invention.
[0013] FIG. 4 is a block diagrams illustrating more exemplary data
structures useful in implementing methods of workflow decision
management according to aspects of the present invention
[0014] FIG. 5 is a block diagram illustrating an exemplary
relationship among the data structures of FIGS. 3 and 4.
[0015] FIG. 6 sets forth a data flow diagram illustrating an
exemplary method for workflow decision management.
DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS
Introduction
[0016] The present invention is described to a large extent in this
specification in terms of methods for workflow decision management.
Persons skilled in the art, however, will recognize that any
computer system that includes suitable programming means for
operating in accordance with the disclosed methods also falls well
within the scope of the present invention. Suitable programming
means include any means for directing a computer system to execute
the steps of the method of the invention, including for example,
systems comprised of processing units and arithmetic-logic circuits
coupled to computer memory, which systems have the capability of
storing in computer memory, which computer memory includes
electronic circuits configured to store data and program
instructions, programmed steps of the method of the invention for
execution by a processing unit.
[0017] The invention also may be embodied in a computer program
product, such as a diskette or other recording medium, for use with
any suitable data processing system. Embodiments of a computer
program product may be implemented by use of any recording medium
for machine-readable information, including magnetic media, optical
media, or other suitable media. Persons skilled in the art will
immediately recognize that any computer system having suitable
programming means will be capable of executing the steps of the
method of the invention as embodied in a program product. Persons
skilled in the art will recognize immediately that, although most
of the exemplary embodiments described in this specification are
oriented to software installed and executing on computer hardware,
nevertheless, alternative embodiments implemented as firmware or as
hardware are well within the scope of the present invention.
Definitions
[0018] "802.11" refers to a family of specifications developed by
the IEEE for wireless LAN technology. 802.11 specifies an
over-the-air interface between a wireless client and a base station
or between two wireless clients.
[0019] "API" is an abbreviation for "application programming
interface." An API is a set of routines, protocols, and tools for
building software applications.
[0020] "Bluetooth" refers to an industrial specification for a
short-range radio technology for RF couplings among client devices
and between client devices and resources on a LAN or other network.
An administrative body called the Bluetooth Special Interest Group
tests and qualifies devices as Bluetooth compliant. The Bluetooth
specification consists of a `Foundation Core,` which provides
design specifications, and a `Foundation Profile,` which provides
interoperability guidelines.
[0021] "CEBus" is an abbreviation for Consumer Electronics Bus.
CEBus is an open international standard for controlling devices
over different media such as power line, radio frequency (RF),
infrared (IR), coaxial cable, twisted pair, fiber optics and
audio/video. The CEBus standard is promulgated by the Consumer
Electronic Manufacturers Association (CEMA), a sector of the
Electronics Industries Association (EIA) and described in 12
standards: the ANSI/EIA-600 series. The CEBus standard describes a
physical design and topology of network media, a protocol for
message generation, and a common application language ("CAL"). The
CEBus specification is available for download at
http://www.cebus.org.
[0022] CEBus provides a Common Application Language (CAL) defined
in EIA 600.81 that uses an object-oriented model to provide
interoperability between diverse devices in a networked
environment. The CAL specification defines a set of classes that
provide an interface to the internal operations of these disparate
networked devices. If a function or feature cannot be mapped well
to one of the classes defined in the CAL specification, the CAL
specification has set aside a specific range of class identifiers
for defining special classes.
[0023] CAL objects have two important attributes Instance Variables
and Methods. Instance Variables contain information about a
particular CAL object such as Boolean indications, numeric
information, character-string information, and other data. Boolean
Instance Variables can only be set to TRUE or FALSE. As the name
implies, numeric Instance Variables are intended for storage of
numbers. The character-string type Instance Variables provide
storage of text. And other data-type Instance Variables provide
storage of other information as a single-dimensioned array of one
or more elements; each element containing the same number of one or
more bytes.
[0024] Access to the information contained in CAL Instance
Variables is accomplished through a set of member methods specific
to that object. Examples of common methods include: setOn, setOff,
setValue, getValue, setArray and getArray. Not all methods are
appropriate for each Instance Variable type. For example, a setOn
method is intended for manipulating Boolean Instance Variables and
is therefore undefined for an Instance Variable of the
character-string type.
[0025] "Coupled for data communications" means any form of data
communications, wireless, 802.11b, Bluetooth, infrared, radio,
internet protocols, HTTP protocols, email protocols, networked,
direct connections, dedicated phone lines, dial-ups, serial
connections with RS-232 (EIA232) or Universal Serial Buses,
hard-wired parallel port connections, network connections according
to the Power Line Protocol, and other forms of connection for data
communications as will occur to those of skill in the art.
Couplings for data communications include networked couplings for
data communications. Examples of networks useful with various
embodiments of the invention include cable networks, intranets,
extranets, internets, local area networks, wide area networks, and
other network arrangements as will occur to those of skill in the
art. The use of any networked coupling among television channels,
cable channels, video providers, telecommunications sources, and
the like, is well within the scope of the present invention.
[0026] "HAVi" stands for `Home Audio Video interoperability,` the
name of a vendor-neutral audio-video standard particularly for home
entertainment environments. HAVi allows different home
entertainment and communication devices (such as VCRs, televisions,
stereos, security systems, and video monitors) to be networked
together and controlled from one primary device, such as a services
gateway, PC, or television. Using IEEE 1394, the `Firewire`
specification, as the interconnection medium, HAVi allows products
from different vendors to comply with one another based on defined
connection and communication protocols and APIs. Services provided
by HAVi's distributed application system include an addressing
scheme and message transfer, lookup for discovering resources,
posting and receiving local or remote events, and streaming and
controlling isochronous data streams.
[0027] "HomePlug" stands for The HomePlug Powerline Alliance.
HomePlug is a not-for-profit corporation formed to provide a forum
for the creation of open specifications for high speed home
powerline networking products and services. The HomePlug
specification is designed for delivery of Internet communications
and multimedia to homes through the home power outlet using
powerline networking standards.
[0028] The HomePlug protocol allows HomePlug-enabled devices to
communicate across powerlines using Radio Frequency signals (RF).
The HomePlug protocol uses Orthogonal Frequency Division
Multiplexing (OFDM) to split the RF signal into multiple smaller
sub-signals that are then transmitted from one HomPlug
enabled-device to another HomePlug-enabled device at different
frequencies across the powerline.
[0029] "HTTP" stands for `HyperText Transport Protocol,` the
standard data communications protocol of the World Wide Web.
[0030] "ID" abbreviates "identification" as used by convention in
this specification with nouns represented in data elements, so that
`user ID` refers to a user identification and `userID` is the name
of a data element in which is stored a user identification.
[0031] "LAN" is an abbreviation for "local area network." A LAN is
a computer network that spans a relatively small area. Many LANs
are confined to a single building or group of buildings. However,
one LAN can be connected to other LANs over any distance via
telephone lines and radio waves. A system of LANs connected in this
way is called a wide-area network (WAN). The Internet is an example
of a WAN.
[0032] "LonWorks" is a networking platform available from Echelons.
Lon Works is currently used in various network applications such as
appliance control and lighting control. The LonWorks networking
platform uses a protocol called "LonTalk" that is embedded within a
"Neuron Chip" installed within Lon Works-enabled devices.
[0033] The Neuron Chip is a system-on-a-chip with multiple
processors, read-write and read-only memory (RAM and ROM), and
communication and I/O subsystems. The read-only memory contains an
operating system, the LonTalk protocol, and an I/O function
library. The chip has non-volatile memory for configuration data
and for application programs, which can be downloaded over a
LonWorks network to the device. The Neuron Chip provides the first
6 layers of the standard OSI network model. That is, the Neuron
Chip provides the physical layer, the data link layer, the network
layer, the transport layer, the session layer, and the presentation
layer.
[0034] The Neuron Chip does not provide the application layer
programming. Applications for LonWorks networks are written in a
programming language called "Neuron C." Applications written in
Neuron C are typically event-driven, and therefore, result in
reduced traffic on the network.
[0035] "OSGI" refers to the Open Services Gateway Initiative, an
industry organization developing specifications for services
gateways, including specifications for delivery of service bundles,
software middleware providing compliant data communications and
services through services gateways. The Open Services Gateway
specification is a java based application layer framework that
gives service providers, network operator device makers, and
appliance manufacturer's vendor neutral application and device
layer APIs and functions.
[0036] "USB" is an abbreviation for "universal serial bus." USB is
an external bus standard that supports data transfer rates of 12
Mbps. A single USB port can be used to connect up to 127 peripheral
devices, such as mice, modems, and keyboards. USB also supports
Plug-and-Play installation and hot plugging.
[0037] "WAP" refers to the Wireless Application Protocol, a
protocol for use with handheld wireless devices. Examples of
wireless devices useful with WAP include mobile phones, pagers,
two-way radios, and hand-held computers. WAP supports many wireless
networks, and WAP is supported by many operating systems. Operating
systems specifically engineered for handheld devices include
PalmOS, EPOC, Windows CE, FLEXOS, OS/9, and JavaOS. WAP devices
that use displays and access the Internet run "microbrowsers." The
microbrowsers use small file sizes that can accommodate the low
memory constraints of handheld devices and the low-bandwidth
constraints of wireless networks.
[0038] The "X-10" means the X-10 protocol. Typical X-10 enabled
devices communicate across AC powerline wiring, such as existing AC
wiring in a home, using an X-10 transmitter and an X-10 receiver.
The X-10 transmitter and the X-10 receiver use Radio Frequency (RF)
signals to exchange digital information. The X-10 transmitter and
the X-10 receiver communicate with short RF bursts which represent
digital information.
[0039] In the X-10 protocol, data is sent in data strings called
frames. The frame begins with a 4 bit start code designated as
"1110." Following the start code, the frame identifies a particular
domain, such as house, with a 4 bit "house code," and identifies a
device within that domain with a 4 bit "devices code." The frame
also includes a command string of 8 bits identifying a particular
preset command such as "on," "off," "dim," "bright," "status on,"
"status off," and "status request."
Workflow Decision Management with Derived Scenarios and Workflow
Tolerances
[0040] Exemplary methods, systems, and products for workflow
decision management, are now explained with reference to the
accompanying drawings, beginning with FIG. 1. FIG. 1 depicts an
exemplary data processing system capable of workflow decision
management according to embodiments of the present invention. The
exemplary system of FIG. 1 includes a number of workflow decision
management compliant devices capable of implementing workflow
decision management according to embodiments of the present
invention that are connected for data communications through a
local area network ("LAN") (103). In the example of FIG. 1, the
exemplary workflow decision management compliant devices include a
personal digital assistant ("PDA") (104), a computer workstation
(106), a personal video recorder (108), a server (110), personal
computer (112), a thermostat (114), a laptop (116), a desk lamp
(118), a compact disc player (120), and a telephone (102) are
coupled for data communications through a LAN. The network
connection aspect of the architecture of FIG. 1 is only for
explanation, not for limitation. In fact, systems for workflow
decision management according to embodiments of the present
invention may implemented with LANs, WANs, intranets, internets,
the Internet, webs, the World Wide Web itself, or other connections
as will occur to those of skill in the art. Such networks are media
that may be used to provide data communications connections between
various devices and computers connected together within an overall
data processing system.
[0041] In the example of FIG. 1, the PDA (104) is coupled for data
communications to the LAN (103) through a wireless link (124). The
Workstation (106), the server (110), the personal computer (112),
the laptop (116), and the telephone (102) are coupled for data
communications to the LAN through twisted pair wireline connections
(126, 130, 132, 136, 122). The personal video recorder (108) and
the compact disc player (120) are coupled for data communications
to the LAN through a coaxial cable wireline connection (128, 140).
The thermostat (114) and the desk lamp (118) are coupled for data
communications to the LAN through a powerline connection (134,
138).
[0042] The exemplary devices of FIG. 1 are capable of reporting
current values of supported device attributes and the exemplary
devices of FIG. 1 are also capable of receiving messages from other
devices instructing the device to change values of supported
attributes. The exemplary system of FIG. 1 is capable generally of
maintaining a device state history; identifying a device usage
pattern in dependence upon the device state history, identifying a
derived scenario in dependence upon the device usage pattern, and
selecting a heuristic in dependence upon the derived scenario. The
heuristic typically has a tolerance. The system of FIG. 1 is also
capable generally of identifying a workflow in dependence upon the
selected heuristic and executing the workflow in dependence upon
the tolerance.
[0043] A device state history is a data structure containing the
history of the values of one or more attributes of one or more
devices. In the example of FIG. 1, each device may maintain its own
device state history and store the device history in computer
memory installed on the device or single device state history of
all the devices in the network maybe maintained in computer memory
accessible to application programming implementing workflow
decision management that is installed on one or more devices.
[0044] A device usage pattern is typically implemented as a data
structure representing a predetermined pattern of device usage for
one or more devices. That is, a data structure representing a
pattern of device usage. A device usage pattern may represent a
pattern of usage of a single device or a pattern of usage of more
than one device. The system of FIG. 1 typically identifies a device
usage pattern in dependence upon the device state history by
searching a plurality of stored device usage records for a device
usage record that matches recent entries in the device state
history.
[0045] The system of FIG. 1 is also capable of identifying a
derived scenario in dependence upon the identified device usage
pattern. A derived scenario is typically implemented as a data
structure representing a particular state of devices in a networked
environment. Derived scenarios are created in dependence upon
actual past device usage within the networked environment and such
derived scenarios often represent scenarios of device usage of more
than one device. The system of FIG. 1 typically identifies a
derived scenario by retrieving a derived scenario ID from a derived
scenario table in dependence upon the identified device usage
pattern ID.
[0046] The system of FIG. 1 is also capable of identifying a
heuristic in dependence upon the derived scenario. A heuristic
represents a simplified solution directed at administering devices
according to a particular derived scenario. That is, a heuristic is
a data structure representing an approximate solution to a
particular state of devices in a networked environment comprising
the scenario.
[0047] The system of FIG. 1 is also capable of identifying a
workflow in dependence upon the heuristic and executing the
workflow. A workflow is software implementing a device controlling
action that when executed changes the values of one or more
attributes of one or more devices. Executing workflows typically
includes calling member methods in a CAL object for a device,
downloading an OSGi bundle to a device, calling member methods in a
device class, sending a message to a device, or any other method of
executing a workflow as will occur to those of skill in the
art.
[0048] The arrangement of devices making up the exemplary system
illustrated in FIG. 1 is for explanation, not for limitation. Data
processing systems useful according to various embodiments of the
present invention may include additional servers, routers, other
devices, and peer-to-peer architectures, not shown in FIG. 1, as
will occur to those of skill in the art. Networks in such data
processing systems may support many data communications protocols,
including for example, CEBus, X-10, LonTalk, HomePlug, HAVi,
TCP/IP, HTTP, WAP, and others as will occur to those of skill in
the art. Various embodiments of the present invention may also be
implemented in various computer environments such as for example
CEBus, OSGi, and others that will occur to those of skill in the
art. Although much of the present specification describes exemplary
embodiments of the present invention with particular reference to
CEBus, the such descriptions are for explanation not for
limitation. In fact, many environments and frameworks support
workflow decision management according to the present invention
such as, for example, CEBus, HAVi, HomePlug, LonWorks, X-10, OSGi,
as well as others that will occur to those of skill in the art, and
all such environments and frameworks are within the scope of the
present invention.
[0049] Workflow decision management in accordance with the present
invention is generally implemented with automated computing
machinery installed on one or more workflow decision management
compliant devices. For further explanation, FIG. 2 sets forth a
block diagram of an exemplary device (150) useful in implementing
workflow decision management according to embodiments of the
present invention. The device (150) of FIG. 2 includes at least one
computer processor (156) or `CPU` as well as random access memory
(168) ("RAM"). Stored in RAM (168) is an operating system (154).
Operating systems useful in computers according to embodiments of
the present invention include Unix, Linux, Microsoft NT.TM., and
many others as will occur to those of skill in the art. Operating
system (154) in the example of FIG. 2 is shown in RAM (168), but
many components of an operating system typically are stored in
non-volatile memory (166) also.
[0050] Also stored in RAM is a workflow decision management
application (162). The workflow decision management application is
application computer programming generally capable of maintaining a
device state history, identifying a device usage pattern in
dependence upon the device state history, and identifying a derived
scenario in dependence upon the device usage pattern. The workflow
decision management application is also generally capable of
selecting a heuristic in dependence upon the derived scenario. The
heuristic typically has a tolerance governing the execution of
workflows. The exemplary devices of FIG. 2 are also capable of
identifying a workflow in dependence upon the derived scenario; and
executing the workflow in dependence upon the tolerance. Methods of
workflow decision management in accordance with the present
invention can be implemented using many programming languages
including CAL, OSGi, Java, C++, Smalltalk, C, Pascal, Basic, COBOL,
Fortran, and so on, as will occur to those of skill in the art.
[0051] The device (150) of FIG. 2 includes non-volatile computer
memory (166) coupled through a system bus (160) to processor (156)
and to other components of the device (150). Non-volatile computer
memory (166) may be implemented as a hard disk drive (170), optical
disk drive (172), electrically erasable programmable read-only
memory space (so-called `EEPROM` or `Flash` memory) (174), RAM
drives (not shown), or as any other kind of computer memory as will
occur to those of skill in the art.
[0052] The exemplary device (150) of FIG. 2 includes a
communications adapter (167) for implementing connections for data
communications (184), including connections through networks, to
other workflow management compliant devices (182), including
servers, other workflow management client devices, and others as
will occur to those of skill in the art. Communications adapters
implement the hardware level of connections for data communications
through which local devices and remote devices or servers send data
communications directly to one another and through networks.
Examples of communications adapters useful for workflow decision
management according to embodiments of the present invention
include modems for wired dial-up connections, Ethernet (IEEE 802.3)
adapters for wired LAN connections, and 802.11b adapters for
wireless LAN connections.
[0053] The example device of FIG. 2 includes one or more
input/output interface adapters (178). Input/output interface
adapters in workflow management compliant devices implement
user-oriented input/output through, for example, software drivers
and computer hardware for controlling output to display devices
(180) such as computer display screens, as well as user input from
user input devices (181) such as keyboards and mice.
[0054] FIGS. 3 and 4 are block diagrams illustrating exemplary data
structures useful in implementing methods of workflow decision
management according to aspects of the present invention. In this
specification, the terms "field" and "data element," unless the
context indicates otherwise, generally are used as synonyms,
referring to individual elements of digital data. Aggregates of
data elements are referred to as "records" or "data structures."
Aggregates of records are referred to as "tables" or "files."
Aggregates of files or tables are referred to as "databases."
[0055] The example of FIG. 3 includes a device record (150) that
represents a workflow decision management compliant device in
accordance with the present invention. The exemplary device record
(150) includes a device ID field (302) uniquely identifying the
device. The exemplary device record (150) also includes an address
field (304) containing the network address of the device. The
exemplary device record (150) includes an attribute field (306).
The attribute field contains the value of a particular attribute of
a device indicating a device state such as on, off, a volume
setting, and so on. Although only one attribute field is shown in
the example of FIG. 3, this for simplicity of explanation. Many
workflow decision management compliant devices support more than
one attribute as will occur to those of skill in the art.
[0056] The example of FIG. 3 includes an exemplary device state
record (330) that represents the allowable device states of a
particular device. The device state record includes a device ID
field (302) uniquely identifying the device for which the device
state record represents acceptable device states. The device state
record (330) also includes a device state ID field (316) uniquely
identifying the device state. The device state record (330) also
includes a description field (339) containing a description of the
acceptable states or attribute values of the device.
[0057] The example of FIG. 3 includes a devices state history
(314). The device state history is a data structure containing the
history of the state of one or more devices. That is, the current
as well as past values of attributes of a device. Records in the
exemplary device state history (314) include a device ID (302)
uniquely identifying the device for which the device state is
recorded. Records of the exemplary device state history also
include a device state ID field (316) uniquely identifying
acceptable device states for the device. Records of the exemplary
device state history (314) include a value field (318) containing
the value of a particular attribute of the device. As stated above,
typical devices support more than one attribute and therefore
typical records of device state histories include a plurality of
value fields containing the values of the supported attributes.
Records of the exemplary device state history include a time stamp
field (320) containing date and time information identifying the
date and time that a particular device attribute of a particular
device had a particular value.
[0058] The example of FIG. 3 includes a device usage record (328)
that represents a predetermined pattern of device attributes for a
device. That is, a device usage is a data structure used to
identify whether the states of the devices in a particular
networked environment conform to a predetermined pattern. To
determine whether the state of current devices in a particular
networked environment conform to a predetermined pattern, recent
entries in the device state history compared with a plurality of
device usage. If the comparison results in a match, it is inferred
that the state of the devices in the particular networked
environment conform to a predetermined pattern.
[0059] The exemplary devices usage (328) includes a usage ID (376)
uniquely identifying a particular predetermined pattern of device
usage. The exemplary device usage of FIG. 3 includes a device ID
(302) uniquely identifying a particular device. The device usage
(328) also includes a device state ID (326) uniquely identifying
the acceptable device states for the particular device. The
exemplary device usage (328) includes a value field (318)
containing the value of a particular supported attribute of the
device.
[0060] The example of FIG. 3 includes a usage record (332) that
identifies and describes a particular pattern of device usage in
the networked environment. The usage record (332) includes usage ID
(334) that uniquely identifies the pattern of device usage, and a
description field (336) that contains a description of the pattern
of device usage represented by the usage record (332).
[0061] The example of FIG. 3 includes a scenario record (344) that
represents a particular scenario of device usage consistent with an
identified predetermined device usage pattern. Scenarios (344) are
predetermined and predefined generally from many users in many
networked environments. That is, they are not created from the
actual device usage in the networked domain in which they are
implemented. When the current states of a device conform to a
predetermined pattern of device usage, the current states of a
device may also conform to one of a plurality of scenarios. The
exemplary scenario record (344) of FIG. 3 includes a scenario ID
field (346) uniquely identifying the scenario. The exemplary
scenario record (344) of FIG. 3 includes a workflow ID (340)
identifying a workflow for execution when the current device states
in a particular networked environment identify a scenario. Although
the scenario record of FIG. 3 includes a single workflow ID field,
this for simplicity of explanation, not for limitation. In many
embodiments of the present invention, a particular scenario
supports the execution of more than one workflow. The scenario
(344) of FIG. 3 also contains a description field (350) that
contains a description of the scenario.
[0062] The example of FIG. 3 includes a workflow record (338) that
represents a particular device controlling action or a set of
device controlling actions. A workflow is software implementing a
device controlling action that when executed changes the values of
one or more attributes of one or more devices in accordance with
the present invention. The exemplary workflow record (338) includes
a workflow ID (340) uniquely identifying the workflow. The
exemplary workflow record (338) of FIG. 3 also includes a sequence
field (342) identifying whose value is used to execute this
workflow in a particular sequence of execution of a plurality of
workflows. That is, when more than one workflow is executed for a
scenario, the value of the sequence field is used to sequence the
execution of the plurality of workflows. Workflows can be
implemented using CAL, OSGi, Java, C++, Smalltalk, C, Pascal,
Basic, COBOL, Fortran, and so on, as will occur to those of skill
in the art.
[0063] The example of FIG. 3 includes a workflow session (362) that
represents an instance of an executed workflow. The exemplary
workflow session (362) includes a workflow session ID (364)
uniquely identifying the workflow session and a workflow ID (340)
identifying the executed workflow. The exemplary workflow session
also includes a user session state ID (366) uniquely identifying
the particular user session for which the workflow is executed. The
exemplary workflow session also includes a message ID (368)
identifying a message sent to a device to effect the workflow. That
is the message send to a device instructing the device to change
the value of a particular attribute. Sending such messages to the
device, in some embodiments, effect changes in device status and
therefore, carry out the workflow. The exemplary workflow session
(362) includes a user ID (370) identifying the user on whose behalf
the workflow is executed and a role ID field (372) identifying the
security role of the user.
[0064] The example of FIG. 3 includes a derived scenario (352) that
represents a particular scenario of device usage in the networked
domain. Derived scenarios are created in dependence upon the actual
device usage within the networked environment. Derived scenarios
(352) have two important distinctions from scenarios (344). First,
the derived scenarios are created in dependence upon the device
usage of the devices within the networked environment and therefore
reflect scenarios of device usage of the particular networked
environment from which they are derived rather than canned or off
the shelf scenarios. Second, derived scenarios have an associated
tolerance (360) which is a rule set that governs the execution of
workflows executed in dependence upon identifying the derived
scenario.
[0065] The exemplary derived scenario (352) of FIG. 3 includes a
derived scenario ID field (354) uniquely identifying the derived
scenario. The derived scenario (352) record contains a description
field (358) containing a description of the derived scenario.
[0066] The example of FIG. 3 includes a tolerance record (360) that
represents a rule set governing the execution of a workflow
executed in dependence upon a selected heuristic. Often a tolerance
is a subset of the range of acceptable attribute values that a
device supports. For example, a thermostat may support attribute
values that will, if set, eventually damage either the thermostat
itself or other devices. A tolerance is therefore often designed to
govern the execution of workflows such that device usage is not
harmful to devices within the networked environment. The exemplary
tolerance (360) of FIG. 3 includes a tolerance level ID field (362)
uniquely identifying the tolerance.
[0067] The example of FIG. 3 includes a device threshold record
(308) that represents the threshold minimum and threshold maximum
attribute values that device will support. The exemplary device
threshold record (308) of FIG. 3 includes a device ID (302)
identifying the device for which the thresholds are valid. The
exemplary device threshold record also includes MAX field (310)
containing the maximum attribute value that the device will support
and a MIN field (312) that includes the minimum attribute value
that the device will support.
[0068] The example of FIG. 3 includes a user record (374)
representing a user for which workflows are performed to affect
device status. Users according to aspects of workflow decision
management of the present invention are not limited to human users,
but also include processes as will occur to those of skill in the
art. The exemplary user record (374) of FIG. 3 includes a user ID
(376) uniquely identifying the user and a role ID (378) uniquely
representing the role of the user. A role is security role for the
user such as a systems administrator, a guest, and so on.
[0069] The example of FIG. 3 also includes a user session state
(382) that represents a session for a user. A session for a user
indications current workflow decision management being executed on
the user's behalf. The user session state (382) of FIG. 3 includes
a session state ID (384) that uniquely identifies the user session
state and a message ID (386) that identifies a message sent to give
effect to a particular workflow identified in a workflow session
and executed on behalf of the user. The user session state also
includes a user ID (376) identifying the user on whose behalf the
workflow is executed and a role ID (378) identifying the role of
the user.
[0070] FIG. 4 is a block diagram of more data structures useful in
workflow decision management according to embodiments of the
present invention. The example of FIG. 4 includes a role record
(402) that represents a security role for a user. The exemplary
role record (402) of FIG. 4 includes a role ID (378) that uniquely
identifies a security role.
[0071] The example of FIG. 4 includes a role device privileges
record (404) that representing the privileges assigned to a
particular role for a device. For example, some security roles have
only limited access to some devices. The role device privileges
record (404) includes a role privileges ID field (406) uniquely
identifying the role device privileges. The exemplary role device
privileges record (404) of FIG. 4 includes a privileges ID (408)
identifying an allowable privilege and a role ID (378) identifying
a particular security role having the privilege.
[0072] The example of FIG. 4 includes a privilege record (415)
representing a particular privilege. The exemplary privilege record
(415) includes a privilege ID field (436) identifying the privilege
and a description field (410) containing a description of the
privilege. The exemplary privilege record (415) includes a read
flag (412) and a write flag (414) containing a Boolean indication
of read and write privileges.
[0073] The example of FIG. 4 includes a message record (416)
representing a message. The message record (416) includes a message
ID field (386) uniquely representing the message. The example
message (416) of FIG. 4 also includes an origin address field (418)
containing the network address of the device originating the
message and a destination address field (420) containing the
network address of the device receiving the message.
[0074] The example of FIG. 4 includes a device privilege record
(422) that represents an available privilege appropriate for a
device. The exemplary device privilege record (422) of FIG. 4
includes a device privilege ID (424) uniquely identifying the
device privilege and a device ID (302) identifying the device. The
exemplary device privilege record (422) includes a privilege ID
(437) identifying an privilege appropriate for the device.
[0075] The example of FIG. 4 includes a heuristic record (338). In
computer science the term `heuristic` typically means a simplified
solution or an educated guess that reduces the search for solutions
in domains that are difficult and poorly understood. Unlike
algorithms, heuristics often do not guarantee optimal, or even
feasible, solutions and are often used with no theoretical
guarantee. In the case of workflow decision management according to
embodiments of the present invention, a heuristic record represents
a simplified solution directed at administering devices according
to a particular derived scenario. That is, a heuristic is a data
structure representing an approximate solution to a particular
scenario. For example, a device usage pattern may demonstrate that
a ceiling fan is operating at its maximum capacity and thermostat
is set to a target temperature of 72 degrees Farenheit. However,
the room temperature is over 80 degrees Farenheit. One derived
scenario representing this device usage pattern may be that the
temperature outside the window of the room is over 90 degrees
Farenheit. In this specification, a heuristic is a data structure
representing an approximate solution to the problem. In this
example, a heuristic record representing `cool the room` may have
associated workflows that give effect to the heuristic by
administering devices to cool the room, such as by calling member
methods for the thermostat to reduce the thermostat setting to 68
degrees Farenheit.
[0076] The exemplary heuristic record of FIG. 4 includes a
heuristic ID (341) uniquely identifying the heuristic. The
exemplary heuristic record (339) of FIG. 4 includes a workflow ID
field (340) identifying a workflow that when executed gives effect
to the heuristic. The exemplary heuristic record of FIG. 4 also
includes a tolerance ID (356) identifying an associated tolerance
for workflows executed in dependence upon the heuristic. The
workflow associated with the heuristic is executed in dependence
upon the associated tolerances of the heuristic.
[0077] FIG. 5 is a block diagram illustrating an exemplary
relationship among the data structures of FIGS. 3 and 4. In the
example of FIG. 5, the device record is related one-to-many to the
identified device usage record (328) through the device ID field
(302 on FIG. 3) used as a foreign key. The identified device usage
record (328) is related many-to-one to the usage record (332)
through the usage ID field (376 on FIG. 3) used as a foreign key.
The device record (150) is related one-to-many to the device
threshold record (308) through the device ID field (302 on FIG. 3)
used as a foreign key.
[0078] In the example of FIG. 5, the device record (150) is related
one-to-many to the device state record (330) through the device ID
field (302 on FIG. 3) used as a foreign key. The device state
record (330) is related one-to-many to the device state history
record (314) through the device state ID field (316 on FIG. 3) used
as a foreign key. The device state history record (314) is related
many-to-one to the device record (150) through the device ID field
(302 on FIG. 3) used as a foreign key.
[0079] In the example of FIG. 5, the device record (150) is related
one-to-many to the scenario record (344) through the device ID
field (302 on FIG. 3) used as a foreign key. The scenario record
(344) is related many-to-many to the heuristic record (339) through
the heuristic ID field (341 on FIG. 4). The heuristic record is
related one-to-many to the workflow record (338) through a workflow
ID field (340 on FIG. 3) used as a foreign key. The workflow record
(338) is related one-to-many to the workflow session (362) through
the workflow ID field (340 on FIG. 3) used as a foreign key.
[0080] In the example of FIG. 5, the device record (150) is related
one-to-many to the derived scenario record (352) through the device
ID field (302 on FIG. 3) used as a foreign key. The derived
scenario record (352) is related many-to-many to the heuristic
record (339) through the heuristic ID field (341 on FIG. 4). The
heuristic record (339) is related many-to-one to the tolerance
record (360) through the tolerance ID field (356 on FIG. 4) used as
a foreign key.
[0081] In the example of FIG. 5, the device record (150) is related
one to many with the device privileges record (422) through the
device ID field (302 on FIG. 3) used as a foreign key. The device
privileges record (422) is related many-to-one through to the
privileges record (415) through the privilege ID field (437 on FIG.
4) used as a foreign key. The privileges record (415) is related
one-to-many to the role device privileges record (404) through the
privilege ID field (436 on FIG. 4) used as a foreign key. The role
device privileges record (404) is related many-to-one to the role
record (402) through a role field (378 on FIG. 4) used as a foreign
key.
[0082] In the example of FIG. 5, the user record (374) is related
many-to-one through to the role record (402) through the role ID
field (378 on FIG. 4) used as a foreign key. The user record (374)
is related to the user session state (382) one-to-many through the
user ID field (376 on FIG. 3) used as a foreign key. In the example
of FIG. 5, the user session state (382) is related many-to-one to
the message record (416) through the message ID field (386 on FIG.
4) used as a foreign key. In the example of FIG. 5, the user
session state (382) is related one-to-many to the workflow session
(362) through the user session state ID (384 on FIG. 3) used as a
foreign key.
Workflow Decision Management with Heuristics
[0083] FIG. 6 sets forth a data flow diagram illustrating an
exemplary method for workflow decision management. The method of
FIG. 6 includes maintaining (602) a device state history (314). As
discussed above, the device state history is a data structure
containing the history of the values of one or more attributes of
one or more devices. A device state history for a single device can
be maintained in computer memory on the device itself or a single
device state history for many devices in the networked environment
can be maintained in computer memory accessible to application
programming implementing the method of FIG. 6.
[0084] In the method of FIG. 6, maintaining (602) a device state
history (314) includes recording a plurality of attribute values
(306) for a device (150). In the example of FIG. 6, each time an
attribute value (306) of a device (150) is changed, the change is
recorded by creating a new entry in a device state history. In some
such embodiments, the latest entry in the device state history
(314) represents the current state of the device. In some
embodiments, workflow decision management devices are configured to
report to application programming implementing a device state
manager with each change in an attribute value and the device state
manager creates a new entry in a device state history recording the
change in attribute value.
[0085] The method of FIG. 6 also includes identifying (604) a
device usage pattern (328) in dependence upon the device state
history (314). As discussed above, a device usage record represents
a predetermined pattern of device usage and includes a collection
of device attribute values defining the device usage pattern. In
the method of FIG. 6, identifying (604) a device usage pattern
(328) in dependence upon the device state history (314) includes
comparing the device state history (314) with a plurality of device
usage patterns records (329). In the example of FIG. 6, a window of
the entries of the device state history (314) representing recent
device states is compared with device usage records (329) in a
device usage pattern database (616) to identify a matching an
identified device usage record (328). If such a matching an
identified device usage record (328) exists, the current state of
devices within a networked environment conform to a device usage
pattern represented by the record.
[0086] As will occur to those of skill in the art, in typical
embodiments, the values of the entries in the device state history
do not have to be exactly the same as the values of the device
usage records to identify a matching device usage record. In fact,
the values of the entries of the device state history will often
not be the exactly the same as the values of the device usage
records when a matching record is identified. The degree to which
the values of the entries in the device state history must be
similar to the values of the device usage records to be considered
a match will vary according to factors such as tolerances and
methods used to used to compare the device state history with the
device usage records, predefined tolerances for identifying a
match, as well as other numerous factors that will occur to those
of skill in the art.
[0087] The method of FIG. 6 also includes identifying (606) a
derived scenario (352) in dependence upon the identified device
usage pattern (328). As discussed above, a derived scenario (352)
represents a particular scenario created in dependence upon actual
device usage within the networked environment. Derived scenarios
(352) have at least one important distinction from other canned
scenarios or off-the-shelf scenarios. The derived scenarios are
created in dependence upon the actual past device usage of the
devices within the networked environment and therefore reflect
scenarios of device usage of the particular networked
environment.
[0088] In the method of FIG. 6, identifying (606) a derived
scenario (352) in dependence upon the identified device usage
pattern (328) further comprises retrieving a derived scenario ID
from a derived scenario table. In the example of FIG. 6 a derived
scenario table (609) includes a plurality of derived scenario IDs
(354) indexed by device usage IDs (330) identifying predefined
device usage patterns. Identifying (606) a derived scenario (352)
in dependence upon the identified device usage pattern (328)
therefore includes retrieving a derived scenario ID from a derived
scenario table in dependence upon the device usage ID (330) of the
identified device usage record (328).
[0089] In the method of FIG. 6, identifying (606) a derived
scenario (352) in dependence upon the identified device usage
pattern (328) includes identifying a derived scenario (352) in
dependence upon a rule (608). A rule (608) governs the
identification of a particular derived scenario among a plurality
of derived scenarios when more than one derived scenario associated
with a single device usage pattern exists. Consider the example of
a user cooking in a networked kitchen. The states of the devices in
a living room match a device usage pattern that the user is
cooking. However, more than one scenario corresponds with the
device usage pattern as the user may be cooking breakfast, cooking
lunch, or cooking supper. An exemplary rule identifying a scenario
is: If time of day is between 4:30 p.m. and 7:30 p.m. and device
usage pattern identifies a cooking scenario, then user is cooking
supper.
[0090] The method of FIG. 6 also includes selecting (607) a
heuristic (339) in dependence upon the derived scenario (609). As
discussed above, a heuristic record represents a simplified
solution directed at administering devices according to a
particular derived scenario. That is, a heuristic is a data
structure representing an approximate solution to a particular
state of devices in a networked environment. For example, a device
usage pattern may be identified for a ceiling fan operating at its
maximum capacity, a thermostat set to a target temperature of 72
degrees Fahrenheit, but the room temperature is still over 80
degrees Fahrenheit. One derived scenario representing this device
usage pattern may be that the temperature outside the window of the
room is over 90 degrees Fahrenheit. An example heuristic
representing an approximate solution is implemented as a heuristic
record representing `cool the room.` Such a heuristic has
associated one or more workflows that administer devices to carry
out the approximate solution. Continuing with the same example,
workflows that turn on a fan, draw shades, and lower the thermostat
by one degree every 10 minutes carry out an approximate solution to
cool the room. Those of skill in the art will recognize that the
heuristics provide a vehicle to separate the problem from the
solution and advantageously provide increased granularity in
approaching executing workflows to administer devices in response
to identifying derived scenarios.
[0091] In the method of FIG. 6, selecting (607) a heuristic (339)
in dependence upon the derived scenario (352) includes reading a
heuristic ID (359) from a derived scenario record (352). In other
embodiments, selecting (607) a heuristic (339) in dependence upon
the derived scenario (352) includes retrieving a heuristic ID from
a heuristic table.
[0092] In the example of FIG. 6, the heuristic (339) also has an
associated tolerance (356). As discussed above, a tolerance is a
rule set governing the execution of workflows executed in
dependence upon the selected heuristic. Often a tolerance is a
subset of the range of acceptable attribute values that a device
supports. Such tolerances are often designed to prevent the
execution of workflows from damaging devices within the networked
environment.
[0093] The method of FIG. 6 also includes identifying (612) a
workflow (338) in dependence upon the heuristic (339). As discussed
above, a workflow is software implementing a device controlling
action that when executed changes the values of one or more
attributes of one or more devices in accordance with the present
invention. In the method of FIG. 6, identifying (612) a workflow
(338) in dependence upon the selected heuristic comprises
retrieving a workflow ID (340) from a heuristic record (339).
[0094] The method of FIG. 6 also includes executing (614) the
workflow (338) in dependence upon the tolerance (356). As discussed
above, a tolerance represents a rule governing the execution of a
workflow. Often a tolerance is a subset of the range of acceptable
attribute values that a device supports. Such tolerances are often
designed to prevent the execution of workflows from damaging
devices within the networked environment.
[0095] Consider the following example. A networked home has a
number of devices that are used to cool the west wing of the home.
These devices include a fan, an air conditioner, and automatic
shades. However, the automatic shades are currently not working and
they currently will not close properly. A workflow decision
management application operating according to the present invention
has identified a scenario within a home network demonstrating that
the west wing of the home is too warm and identified an appropriate
heuristic to cool the wing. The workflow decision management
application identifies and executes a workflow associated with the
heuristic to cool the wing that includes reducing the thermostat
for the air conditioner, increasing fan speed and closing the
automatic shades.
[0096] Because the automatic shades are not working properly, the
workflow does not reduce the temperature in the west wing
sufficiently and soon thereafter the scenario that the room is too
hot is again identified and again the same heuristic is identified.
The same workflow is again identified and executed. By providing a
tolerance for the execution of the workflow that defines a minimum
tolerance value allowed for the thermostat, the air conditioner is
spared from being overworked to the point of damage. That is,
tolerances provide some boundaries for the execution of workflow
preventing devices from being damaged by unforeseen problems with
the execution of a workflow, such as in this case, the automatic
shades not working properly. These tolerance values are often
designed as a subset of the actual values that devices support.
Such design advantageously recognizes that devices often support
attribute values that will ultimately lead to damaging the
device.
[0097] In the method of FIG. 6, executing (614) the workflow (338)
in dependence upon the tolerance (356) further comprises sending a
message to a device instructing the device to change the value of
an attribute. In some such examples, a device receiving such a
method can effect the change in value of the device by calling a
member methods in a device class representing the device such as,
for example, SomeDeviceClass.setAtrribute( ) parameterized with an
attribute value.
[0098] It will be understood from the foregoing description that
modifications and changes may be made in various embodiments of the
present invention without departing from its true spirit. The
descriptions in this specification are for purposes of illustration
only and are not to be construed in a limiting sense. The scope of
the present invention is limited only by the language of the
following claims.
* * * * *
References