On Multi-Sensor Task Allocation

Seminar @ DEI
Cardiff School of Computer Science University of Padova (Italy)
April, 2009

On Multi-Sensor
Task Allocation
Diego Pizzocaro
PhD candidate

Supervisors:
Prof. Alun Preece - Dr. Roger Whitaker

http://users.cs.cf.ac.uk/D.Pizzocaro D.Pizzocaro@cs.cf.ac.uk

Brief Bio
• 2007 - Computer Engineering, University of Padova (Italy),
supervised by Prof. Luca Schenato

• 2008 - Start PhD in Computer Science at Cardiff University (UK),
supervised by Prof. Alun Preece and Dr. Roger Whitaker

• International Technology Alliance (ITA) project:
multi-national teams supported by complex information networks

U.K. Ministry of Defence U.S. Army Research Lab

• Our research focus: intelligent resource allocation in sensor networks.


Outline

1. Motivations & MSTA problem

2. MSTA in Homogeneous Sensor Network

3. MSTA in Heterogeneous Sensor Network

4. Taxonomy of MSTA problems

5. Conclusion


Motivation
&
MSTA problem


Sensors
Simple sensors

Platforms


Sensors Tasks
Simple sensors e.g. Search-&-Rescue mission

Platforms


Sensors Tasks
Simple sensors e.g. Search-&-Rescue mission

TASK 3
TASK 4
Area
Surveillance
Area (possible threats)
TASK 1
Platforms Surveillance
(possible threats) Injured
people to TASK 2
identify Injured
people to
identify


Scenario


Scenario

• An already deployed network of sensors


Scenario
TASK 3
TASK 7
Monitor
Area
weather
Surveillance TASK 4
TASK 6
Identify
Identify evacuation
route
evacuation
route

TASK 2
TASK 5 TASK 8
TASK 1 Area
Monitor Surveillance Detect
weather Injured vehicles
people to
identify


- Support multiple tasks to be accomplished simultaneously


Scenario
TASK 3
TASK 7
Monitor
Area
weather
Surveillance TASK 4
TASK 6
Identify
Identify evacuation
route
evacuation
route

TASK 2
TASK 5 TASK 8
TASK 1 Area
people to
identify



- Sensors are scarce and in high demand.


Scenario
TASK 3
TASK 7
Monitor
Area
weather
Surveillance TASK 4
TASK 6
Identify
Identify evacuation
route
evacuation
route

TASK 2
TASK 5 TASK 8
TASK 1 Area
people to
identify




- Highly dynamic (sensor failures, change of plan)

Scenario

“Where is it better to send that particular UAV?”

TASK 2
TASK 1 Area
Surveillance
Injured
people to
identify




- Highly dynamic (sensor failures, change of plan)

MSTA problem
• We need schemes to allocate sensors to the task
they best serve, considering all the relevant parameters.

• In general we can have
• static or mobile sensing devices
• tasks requiring multiple sensors or one sensor
• sensors shared or not shared between multiple tasks
• etc...


MSTA problem

• etc...

• The fundamental question remains:

Which sensor should
be allocated to which task?


MSTA problem

• etc...

• The fundamental question remains:

Which sensor should Multi-Sensor Task Allocation
be allocated to which task? (MSTA)


MSTA applications
• MSTA arises in a variety of domains:
• environmental monitoring
• natural disaster (e.g. earthquakes), ....


MSTA applications

• We focus on military/humanitarian scenarios
‣ our allocation mechanisms can be applied to other domains!


MSTA applications


• The task allocation process differs a lot when
‣ in a homogeneous sensor network (e.g. only seismic sensors)
‣ in a heterogeneous sensor network (e.g. seismic+UAVs+UGVs)


MSTA applications


• The task allocation process differs a lot when
‣ in a homogeneous sensor network (e.g. only seismic sensors)
‣ in a heterogeneous sensor network (e.g. seismic+UAVs+UGVs)

• We discuss two examples of MSTA instances in both networks


MSTA
in Homogeneous
Sensor Network


Why Homogeneous SN ?

• Governmental institutions (ARL, MoD), and researchers suggest Wireless
Sensor Networks (WSNs) as “the future” for military operations.




• WSNs are often composed exclusively by hundreds of cheap miniaturized
wireless sensors (called motes) with the same sensing capabilities.




• WSNs are often composed exclusively by hundreds of cheap miniaturized
wireless sensors (called motes) with the same sensing capabilities.

• In general every network composed exclusively sensors with the same sensing
capabilities is called “Homogeneous Sensor Network”.


Problem settings
• We considered a particular instance of the MSTA problem in a
Homogeneous Sensor Network (see DCOSS 08).

• Assumptions:

‣ Sensors can serve only one task per time: Single-Task sensors
- Therefore tasks are competing for the exclusive usage of a sensor

x T2

T1

‣ A task might require more than one sensor: Multi-Sensor tasks

T1

‣ Available info does not permit planning for future: Instantaneous allocation


Formal model
• Tasks: Sensors

‣ vary in priority S1
(e11, c11
Tasks
)
‣ have a different demand for sensing resource (e
12
,c (p1, d1, b1)
capabilities
T1
12
)

‣ have to respect a budget (e.g. monetary). S2

• Each sensor:
T2 (p2, d2, b2)
‣
S3
has a different utility for each task
(e.g. geography & distance)
‣ has a different cost for each task.
S4

e = utility of sensor to a task

• Goal: c = cost of a sensor to a task

maximizes the utility p = task priority
while not exceeding the budgets of each task. d = task utility demand
b = task budget


Allocation algorithms
• At least as hard as the Knapsack problem which is NP-Complete

➡ we developed heuristic algs and
compared them with state of the art pre-existent approaches.

• Simulation environment implemented in Java (with Penn State University)


Allocation algorithms
• At least as hard as the Knapsack problem which is NP-Complete

➡ we developed heuristic algs and
compared them with state of the art pre-existent approaches.

• Simulation environment implemented in Java (with Penn State University)

• The algorithm which offers the best trade-off optimality Vs computational cost:
MRGAP algorithm:

‣ a centralized algorithm:
i.e. we collect all the info about the network in a single node

‣ it can be easily implemented as a distributed algorithm:
less communication overhead.


MSTA
in Heterogeneous
Sensor Network


Why Heterogeneous SN ?
• Sensor network deployment during military/humanitarian missions:
‣ UAV will ﬂy on the battleﬁeld and drop hundreds of motes
‣ Some motes might also be mobile.



• Therefore we have a sensor network composed by sensors with different sensing
capabilities and mobility capabilities: “Heterogeneous sensor network”



• Therefore we have a sensor network composed by sensors with different sensing
capabilities and mobility capabilities: “Heterogeneous sensor network”

• Another example: Sensor Web by Open Geospatial Consortium (OGC) with
environmental monitoring applications.

Problem settings
• We considered a particular instance of the MSTA problem in a Heterogeneous
Sensor Network.
x
• Same assumptions: T2

T1

‣ Single-Task sensors
‣ Multi-Sensor tasks

‣ Instantaneous allocation
T1

• Difference with homogeneous case:
‣ Combined utilities of groups of sensors (bundles) are in general much
complex to compute than the homogeneous SN.

TASK 1

Area video
Surveillance
(possible threats)


Problem settings
• We considered a particular instance of the MSTA problem in a Heterogeneous
Sensor Network.
x
• Same assumptions: T2

T1

‣ Single-Task sensors
‣ Multi-Sensor tasks

‣ Instantaneous allocation
T1

• Difference with homogeneous case:
‣ Combined utilities of groups of sensors (bundles) are in general much
complex to compute than the homogeneous SN.

Sensor bundles

TASK 1

Area video
Surveillance
(possible threats)


Formal model

• We ﬁrst want to group sensors into bundles,
and then we want to ﬁnd the best assignment of bundles to tasks.

Sensors
Bundles Tasks

S1
e11
B1 T1 (p1)

S2
e1
2

S3

B2 T2 (p2)

S4

e = joint utility of a bundle to a task
p = task priority


Allocation mechanisms (1)
• Problem well studied in Multi-agent Systems: Coalition formation

• Typical approach: combinatorial auction

‣ bidders: tasks

‣ items: sensors

‣ tasks bids for bundles of sensors


• Problem well studied in Multi-agent Systems: Coalition formation

• Typical approach: combinatorial auction

‣ bidders: tasks

‣ items: sensors

‣ tasks bids for bundles of sensors

• Need to enumerate all possible bundles for each task.

• Large number of sensors and tasks: the computational cost is too large.

• Our contribution:
Prune the set of bids placed by tasks (i.e. reduce the number of possible bundles).


• We deﬁne a system architecture in which we gradually reduce the search space of the
allocation algorithms (see EKAW08).



• Three main components:
Reasoner

< Package Conﬁg >
Sensor types compatible
with the task.

Bundle
Generator

{ < Bundle1, e1 >,
< Bundle2, e2 >, ... } Sensor Bundles generated based
on the package conﬁguration.

Allocation
Algorithms



• Three main components:
Reasoner

< Package Conﬁg >
Sensor types compatible
with the task.

Bundle
Generator

{ < Bundle1, e1 >,
< Bundle2, e2 >, ... } Sensor Bundles generated based
on the package conﬁguration.

Allocation
Algorithms

• Current work:
Implementing/Testing this approach using the simulation environment “Player/Stage”.


Taxonomy of
MSTA problems


Related work - MRTA
• MSTA is closely related to Multi-Robot Task Allocation (MRTA):
“Which robot should execute which task?"
in a Multi-Robot System (MRS).


Related work - MRTA
• MSTA is closely related to Multi-Robot Task Allocation (MRTA):
“Which robot should execute which task?"
in a Multi-Robot System (MRS).

• Gerkey et al (2004) proposed an MRTA taxonomy:

➡ MRTA problems can be viewed as instances of other well-studied,
optimization problems.

➡ therefore allowing comparison of different solutions.


Preliminary MSTA taxonomy

• We propose a preliminary MSTA taxonomy as an extension of MRTA to cover
important features of sensor networks (INFOCOM 09).


Preliminary MSTA taxonomy

• We propose a preliminary MSTA taxonomy as an extension of MRTA to cover
important features of sensor networks (INFOCOM 09).

• MSTA taxonomy organized on four main axes:
1. Sensors: Single-task (ST) vs. multi-task (MT).
2. Tasks: Single-sensor (SS) vs. multi-sensor (MS).
3. Assignment: Instantaneous (IA) vs. time-extended (TA).
4. Sensor Network: Homogeneous (HO) vs. heterogeneous (HE).

• Example: previously we have considered ST-MS-IA-HO and ST-MS-IA-HE


Conclusion
• We have presented the general MSTA problem,
• Discussed two MSTA instances with applications in military/humanitarian
missions,
• Outlined the need for a MSTA taxonomy and presented a preliminary
version of it.


Conclusion
• We have presented the general MSTA problem,
• Discussed two MSTA instances with applications in military/humanitarian
missions,
• Outlined the need for a MSTA taxonomy and presented a preliminary
version of it.

• Future research:

‣ Reﬁne MSTA taxonomy

‣ What are the most important SN features to include?

‣ Explore different MSTA instances:

‣ Heterogeneous SN with Multi-Task sensors (sensors can be shared)


Thanks for listening !

Cardiff School of Computer Science

D.Pizzocaro@cs.cf.ac.uk

http://users.cs.cf.ac.uk/D.Pizzocaro

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