%0 Journal Article %1 JurdakUW06 %A Jurdak, Raja %A Lopes, Cristina Videira %A Baldi, Pierre %D 2006 %I IEEE %J Sensor Network Operations %K Battery Life Networks Sensor Underwater %P 397-420 %T Battery Life Estimation and Optimization for Underwater Sensor Networks %U http://csserver.ucd.ie/~rjurdak/UWpowermodel.pdf %X Acoustic technology has been established as the exclusive technology that provides robust underwater communications for military and civilian applications. One particular civilian application of interest is the deployment of underwater acoustic sensor networks. The main challenges of deploying such a network are the cost and the limited battery resources of individual sensor nodes. Here, we provide a method that addresses these challenges by estimating the battery lifetime and power cost of shallow water networks, in terms of four independent parameters: (1) internode distance; (2) transmission frequency; (3) frequency of data updates; and (4) number of nodes per cluster. Because transmission loss in water is dependent on both frequency and distance, we extend the general method to exploit topology-dependent distance and frequency assignments. We use the method to estimate the battery life for tree, chain, and grid topologies for various combinations of internode distance, frequency and cluster size in a shallow water setting. The estimation results reveal that topology-dependent assignments prolong battery life of the tier-independent method by a factor of 1.05 to 131 for large networks. In the case of a linear network deployed along a coastline with a target battery life of 100 days, topology-dependent assignments could increase the network range and aggregated sensor data of the topology-independent method by a factor of 3.5.

@article{JurdakUW06, abstract = {Acoustic technology has been established as the exclusive technology that provides robust underwater communications for military and civilian applications. One particular civilian application of interest is the deployment of underwater acoustic sensor networks. The main challenges of deploying such a network are the cost and the limited battery resources of individual sensor nodes. Here, we provide a method that addresses these challenges by estimating the battery lifetime and power cost of shallow water networks, in terms of four independent parameters: (1) internode distance; (2) transmission frequency; (3) frequency of data updates; and (4) number of nodes per cluster. Because transmission loss in water is dependent on both frequency and distance, we extend the general method to exploit topology-dependent distance and frequency assignments. We use the method to estimate the battery life for tree, chain, and grid topologies for various combinations of internode distance, frequency and cluster size in a shallow water setting. The estimation results reveal that topology-dependent assignments prolong battery life of the tier-independent method by a factor of 1.05 to 131 for large networks. In the case of a linear network deployed along a coastline with a target battery life of 100 days, topology-dependent assignments could increase the network range and aggregated sensor data of the topology-independent method by a factor of 3.5.}, added-at = {2007-07-19T12:36:27.000+0200}, author = {Jurdak, Raja and Lopes, Cristina Videira and Baldi, Pierre}, biburl = {https://www.bibsonomy.org/bibtex/2788a47f334003a471cbb714d0b67fcca/jurdak}, description = {UW_battery}, interhash = {51041ecc6698d192352d8b4ac389c8aa}, intrahash = {788a47f334003a471cbb714d0b67fcca}, journal = {Sensor Network Operations}, keywords = {Battery Life Networks Sensor Underwater}, month = May, pages = {397-420}, publisher = {IEEE}, timestamp = {2007-07-19T12:36:27.000+0200}, title = {Battery Life Estimation and Optimization for Underwater Sensor Networks}, url = {http://csserver.ucd.ie/~rjurdak/UWpowermodel.pdf}, year = 2006 }