This paper reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multi-sensor networks. The specific application considered is that of GLACSWEB, 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. 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 the network topology, the size of the network, and the degree of dynamism of the environment. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 470%, 250% and 300% respectively. Categories and Subject Descriptors General TermsAlgorithms, Design, Experimentation KeywordsAgents and ambient intelligence, agents and novel computing paradigms, Agent-based sensor networks.

This paper introduces a new way to investigate in situ processes, the wireless multi-sensor probe, as part of an environmental sensor network. Instruments are housed within a ‘probe’ which can move freely and so behave like a clast. These were deployed in the ice and till at Briksdalsbreen, Norway. The sensors measure temperature, resistivity, case stress, tilt angle and water pressure and send their data to a base station on the glacier surface via radio links. These data are then forwarded by radio to a reference station with mains power 2.5 km away, from where they are sent to a web server in the UK. The system deployed during 2004/05 was very successful and a total of 859 probe days worth of data from the ice and till were collected, along with GPS, weather and diagnostic data about the system.

This paper reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multi-sensor 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.

Wireless sensor networks demand the need to design practical and robust communication protocols to meet the application specifications. Our research focuses on designing and implementing an environmental sensor network to be used for sub-glacial study. The glacier is a very hostile environment presenting severe challenges and complications in the smooth functioning of such a network. In light of these challenges, we present a low power sensor node design and an energy-efficient medium access control protocol called GWMAC developed for a network deployed in a glacier in Norway. The general architecture of GWMAC is based on scheduling and time division multiple accesses (TDMA). We argue that for a highly dynamic network such as ours, GWMAC is more desirable over more widespread protocols such as S-MAC and LMAC. In doing so, we perform extensive series of simulations to empirically evaluate our claim. Our results illustrate that on average GWMAC can increase the network life time by at least 63%. This also has a significant effect on the amount of data that can be collected over network life time.