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Energy-efficient caching strategies in ad hoc wireless networks
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Source International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing table of contents
Annapolis, Maryland, USA
SESSION: Resource management table of contents
Pages: 25 - 34  
Year of Publication: 2003
ISBN:1-58113-684-6
Authors
Pavan Nuggehalli  University of California at San Diego, La Jolla, CA
Vikram Srinivasan  University of California at San Diego, La Jolla, CA
Carla-Fabiana Chiasserini  CERCOM-Dip. di Elettronica, Politecnico di Torino, Torino, Italy
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 55,   Citation Count: 17
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  17

Collaborative Colleagues:
Pavan Nuggehalli: colleagues
Vikram Srinivasan: colleagues
Carla-Fabiana Chiasserini: colleagues