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A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks

A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks
A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks
This article reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multisensor networks. The specific application on which we illustrate our mechanism is that of GlacsWeb. This is a deployed system that uses battery-powered sensors to collect environmental data related to glaciers which it transmits back to a base station so that it can be made available world-wide to researchers. In this context, we first develop a sensing protocol in which each sensor locally adjusts its sensing rate based on the value of the data it believes it will observe. The sensors employ a Bayesian linear model to decide their sampling rate and exploit the properties of the Kullback-Leibler divergence to place an appropriate value on the data. Then, we detail a communication protocol that finds optimal routes for relaying this data back to the base station based on the cost of communicating it (derived from the opportunity cost of using the battery power for relaying data). Finally, we empirically evaluate our protocol by examining the impact on efficiency of a static network topology, a dynamic network topology, the size of the network, the degree of dynamism of the environment, and the mobility of the nodes. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 78%, 133%, 100%, and 93%, respectively. Furthermore, we show that our system performs at 65%, 70%, 63%, and 70% of the theoretical optimal, respectively, despite being a distributed protocol that operates with incomplete knowledge of the environment.
article 27-[39pp]
Padhy, Paritosh
2f4b1c09-f0d1-4f04-8b03-44499e672dca
Dash, Rajdeep
6c83d6ec-5b7d-4fd9-ab62-0394a8181ff4
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Padhy, Paritosh
2f4b1c09-f0d1-4f04-8b03-44499e672dca
Dash, Rajdeep
6c83d6ec-5b7d-4fd9-ab62-0394a8181ff4
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Padhy, Paritosh, Dash, Rajdeep, Martinez, Kirk and Jennings, Nick (2010) A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks. ACM Transactions on Sensor Networks, 6 (3), article 27-[39pp]. (doi:10.1145/1754414.1754423).

Record type: Article

Abstract

This article reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multisensor networks. The specific application on which we illustrate our mechanism is that of GlacsWeb. This is a deployed system that uses battery-powered sensors to collect environmental data related to glaciers which it transmits back to a base station so that it can be made available world-wide to researchers. In this context, we first develop a sensing protocol in which each sensor locally adjusts its sensing rate based on the value of the data it believes it will observe. The sensors employ a Bayesian linear model to decide their sampling rate and exploit the properties of the Kullback-Leibler divergence to place an appropriate value on the data. Then, we detail a communication protocol that finds optimal routes for relaying this data back to the base station based on the cost of communicating it (derived from the opportunity cost of using the battery power for relaying data). Finally, we empirically evaluate our protocol by examining the impact on efficiency of a static network topology, a dynamic network topology, the size of the network, the degree of dynamism of the environment, and the mobility of the nodes. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 78%, 133%, 100%, and 93%, respectively. Furthermore, we show that our system performs at 65%, 70%, 63%, and 70% of the theoretical optimal, respectively, despite being a distributed protocol that operates with incomplete knowledge of the environment.

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Published date: June 2010
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 267848
URI: http://eprints.soton.ac.uk/id/eprint/267848
PURE UUID: ee0829ea-6a53-47b2-bdb0-a496372d13c9
ORCID for Kirk Martinez: ORCID iD orcid.org/0000-0003-3859-5700

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Date deposited: 10 Sep 2009 15:21
Last modified: 15 Mar 2024 02:53

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Contributors

Author: Paritosh Padhy
Author: Rajdeep Dash
Author: Kirk Martinez ORCID iD
Author: Nick Jennings

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