Maximum lifetime routing in wireless sensor networks

  • Authors:

  • Jae-Hwan Chang;Leandros Tassiulas

  • Affiliations:

  • Telecommunication R&D Center, Samsung Electronics Company, Ltd., Suwon 442-600, Korea and Institute for Systems Research and the Department of Electrical and Computer Engineering, University of Ma ...;Computer Engineering and Telecommunications, University of Thessaly, Volos, Greece and Institute for Systems Research and the Department of Electrical and Computer Engineering, University of Maryl ...

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2004

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Abstract

A routing problem in static wireless ad hoc networks is considered as it arises in a rapidly deployed, sensor based, monitoring system known as the wireless sensor network. Information obtained by the monitoring nodes needs to be routed to a set of designated gateway nodes. In these networks, every node is capable of sensing, data processing, and communication, and operates on its limited amount of battery energy consumed mostly in transmission and reception at its radio transceiver. If we assume that the transmitter power level can be adjusted to use the minimum energy required to reach the intended next hop receiver then the energy consumption rate per unit information transmission depends on the choice of the next hop node, i.e., the routing decision. We formulate the routing problem as a linear programming problem, where the objective is to maximize the network lifetime, which is equivalent to the time until the network partition due to battery outage. Two different models are considered for the information-generation processes. One assumes constant rates and the other assumes an arbitrary process. A shortest cost path routing algorithm is proposed which uses link costs that reflect both the communication energy consumption rates and the residual energy levels at the two end nodes. The algorithm is amenable to distributed implementation. Simulation results with both information-generation process models show that the proposed algorithm can achieve network lifetime that is very close to the optimal network lifetime obtained by solving the linear programming problem.