Efficient cache placement in multi-hop wireless networks

  • Authors:

  • Pavan Nuggehalli;Vikram Srinivasan;Carla-Fabiana Chiasserini;Ramesh R. Rao

  • Affiliations:

  • Center for Electronics Design and Technology, Indian Institute of Science, Bangalore, India;Department of Electrical and Computer Engineering, National University of Singapore, Singapore;Department of Electronics, Politecnico di Torino, Torino, Italy;Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2006

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Abstract

In this paper, we address the problem of efficient cache placement in multi-hop wireless networks. We consider a network comprising a server with an interface to the wired network, and other 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 of the nodes distributed across the network. Caching, however, can imply a considerable overhead cost; for instance, disseminating information incurs additional energy as well as bandwidth burden. Since wireless systems are plagued by scarcity of available energy and bandwidth, we need to design caching strategies that optimally trade-off between overhead cost 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 suboptimal 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 cache placement schemes, and show via extensive simulation that our algorithm consistently outperforms these alternative schemes.