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Elastic FemtoCaching: Scale, Cache, and Route

Elastic FemtoCaching: Scale, Cache, and Route
Kwak, JeonghoPaschos, GeorgiosIosifidis, George
DGIST Authors
Kwak, Jeongho; Paschos, Georgios; Iosifidis, George
Issue Date
IEEE Transactions on Wireless Communications, 20(7), 4174-4189
Author Keywords
DelaysBase stationsServersQuality of serviceLinear programmingElastic CDNfile cachingarea-BS associationWireless communicationIndexescache rental budgetLyapunov drift-plus-penaltysubmodularityrandomized cache lease method
The advent of elastic Content Delivery Networks (CDNs) enable Content Providers (CPs) to lease cache capacity on demand and at different cloud and edge locations in order to enhance the quality of their services. This paper addresses key challenges in this context, namely how to invest an available budget in cache space in order to match spatio-temporal fluctuations of demand, wireless environment and storage prices. Specifically, we jointly consider dynamic cache rental, content placement, and request-cache association in wireless scenarios in order to provide just-in-time CDN services. The goal is to maximize the an aggregate utility metric for the CP that captures both service benefits due to caching and fairness in servicing different end users. We leverage the Lyapunov drift-minus-benefit technique and Jensen’s inequality to transform our infinite horizon problem into hour-by-hour subproblems which can be solved without knowledge of future file popularity and transmission rates. For the case of non-overlapping small cells, we provide an optimal subproblem solution. However, in the general overlapping case, the subproblem becomes a mixed integer non-linear program (MINLP). In this case, we employ a randomized cache lease method to derive a scalable solution. We show that the proposed algorithm guarantees the theoretical performance bound by exploiting the submodularity property of the objective function and pick-and-compare property of the randomized cache lease method. Finally, via real dataset driven simulations, we find that the proposed algorithm achieves 154% utility compared to similar static cache storage-based algorithms in a representative urban topology. IEEE
Institute of Electrical and Electronics Engineers
Related Researcher
  • Author Kwak, Jeongho Intelligent Computing & Networking Laboratory
  • Research Interests 클라우드 컴퓨팅; 엣지컴퓨팅; 네트워크 자원관리; 모바일 시스템
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Department of Electrical Engineering and Computer ScienceIntelligent Computing & Networking Laboratory1. Journal Articles

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