An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming

An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming

The efficient management of the limited energy resources of a wireless visual sensor network is central to its successful operation. Within this context, this article focuses on the adaptive sampling, forwarding, and routing actions of each node in order to maximise the information value of the data collected. These actions are inter-related in a multi-hop routing scenario because each node’s energy consumption must be optimally allocated between sampling and transmitting its own data, receiving and forwarding the data of other nodes, and routing any data. Thus, we develop two optimal agent-based decentralised algorithms to solve this distributed constraint optimization problem. The first assumes that the route by which data is forwarded to the base station is fixed, and then calculates the optimal sampling, transmitting, and forwarding actions that each node should perform. The second assumes flexible routing, and makes optimal decisions regarding both the integration of actions that each node should choose, and also the route by which the data should be forwarded to the base station. The two algorithms represent a trade-off in optimality, communication cost, and processing time. In an empirical evaluation on sensor networks (whose underlying communication networks exhibit loops), we show that the algorithm with flexible routing is able to deliver approximately twice the quantity of information to the base station compared to the algorithm using fixed routing (where an arbitrary choice of route is made). However, this gain comes at a considerable communication and computational cost (increasing both by a factor of 100 times). Thus, while the algorithm with flexible routing is suitable for networks with a small numbers of nodes, it scales poorly, and as the size of the network increases, the algorithm with fixed routing is favoured.

1277-1290

Kho, Johnsen

8041e715-eaad-419b-8b25-12b5657ceecf

Tran-Thanh, Long

e0666669-d34b-460e-950d-e8b139fab16c

Rogers, Alex

f9130bc6-da32-474e-9fab-6c6cb8077fdc

Jennings, Nicholas R.

ab3d94cc-247c-4545-9d1e-65873d6cdb30

2010

Kho, Johnsen

8041e715-eaad-419b-8b25-12b5657ceecf

Tran-Thanh, Long

e0666669-d34b-460e-950d-e8b139fab16c

Rogers, Alex

f9130bc6-da32-474e-9fab-6c6cb8077fdc

Jennings, Nicholas R.

ab3d94cc-247c-4545-9d1e-65873d6cdb30

Kho, Johnsen, Tran-Thanh, Long, Rogers, Alex and Jennings, Nicholas R.
(2010)
An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming.
*The Computer Journal*, 53 (8), .

## Abstract

The efficient management of the limited energy resources of a wireless visual sensor network is central to its successful operation. Within this context, this article focuses on the adaptive sampling, forwarding, and routing actions of each node in order to maximise the information value of the data collected. These actions are inter-related in a multi-hop routing scenario because each node’s energy consumption must be optimally allocated between sampling and transmitting its own data, receiving and forwarding the data of other nodes, and routing any data. Thus, we develop two optimal agent-based decentralised algorithms to solve this distributed constraint optimization problem. The first assumes that the route by which data is forwarded to the base station is fixed, and then calculates the optimal sampling, transmitting, and forwarding actions that each node should perform. The second assumes flexible routing, and makes optimal decisions regarding both the integration of actions that each node should choose, and also the route by which the data should be forwarded to the base station. The two algorithms represent a trade-off in optimality, communication cost, and processing time. In an empirical evaluation on sensor networks (whose underlying communication networks exhibit loops), we show that the algorithm with flexible routing is able to deliver approximately twice the quantity of information to the base station compared to the algorithm using fixed routing (where an arbitrary choice of route is made). However, this gain comes at a considerable communication and computational cost (increasing both by a factor of 100 times). Thus, while the algorithm with flexible routing is suitable for networks with a small numbers of nodes, it scales poorly, and as the size of the network increases, the algorithm with fixed routing is favoured.

Text

** atsn_Kho.pdf
- Accepted Manuscript**
## More information

Published date: 2010

Organisations:
Agents, Interactions & Complexity

## Identifiers

Local EPrints ID: 268566

URI: https://eprints.soton.ac.uk/id/eprint/268566

PURE UUID: 28888e4c-6cae-49bc-9141-8a9cac223471

## Catalogue record

Date deposited: 01 Mar 2010 00:01

Last modified: 15 Aug 2019 00:40

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## Contributors

Author:
Johnsen Kho

Author:
Long Tran-Thanh
Author:
Alex Rogers

Author:
Nicholas R. Jennings

## University divisions

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