Energy-efficient caching strategies in ad hoc wireless networks

  • Authors:
  • Pavan Nuggehalli;Vikram Srinivasan;Carla-Fabiana Chiasserini

  • Affiliations:
  • University of California at San Diego, La Jolla, CA;University of California at San Diego, La Jolla, CA;CERCOM-Dip. di Elettronica, Politecnico di Torino, Torino, Italy

  • Venue:
  • Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
  • Year:
  • 2003

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Abstract

In this paper, we address the problem of energy-conscious cache placement in wireless ad hoc networks. We consider a network comprising a server with an interface to the wired network, and some nodes requiring access to the information stored at the server. In order to reduce access latency in such a communication environment, an effective strategy is caching the server information at some nodes distributed across the network. Caching, however, can considerably impact the system energy expenditure; for instance, disseminating information incurs additional energy burden. Since wireless devices have limited amounts of available energy, we need to design caching strategies that optimally trade-off between energy consumption and access latency. We pose our problem as an integer linear program. We show that this problem is the same as a special case of the connected facility location problem, which is known to be NP-hard. We devise a polynomial time algorithm which provides a sub-optimal solution. The proposed algorithm applies to any arbitrary network topology and can be implemented in a distributed and asynchronous manner. In the case of a tree topology, our algorithm gives the optimal solution. In the case of an arbitrary topology, it finds a feasible solution with an objective function value within a factor of 6 of the optimal value. This performance is very close to the best approximate solution known today, which is obtained in a centralized manner. We compare the performance of our algorithm against three candidate caching schemes, and show via extensive simulation that our algorithm consistently outperforms these alternative schemes.