期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 17, 期 5, 页码 3030-3045出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2018.2805893
关键词
Cloud versus edge caching; Lyapunov optimization; submodularity property; hierarchical network architecture
资金
- Institute for Information & Communications Technology Promotion (IITP) - Korea government (MSIT) [2015-0-00557]
- ICT R&D program of MSIP/IITP [R-20161130-004520]
- Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [2016-0-00563-002] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Most existing content caching designs require accurate estimation of content popularity, which can be challenging in the dynamic mobile network environment. Moreover, emerging hierarchical network architecture enables us to enhance the content caching performance by opportunistically exploiting both cloud-centric and edge-centric caching. In this paper, we propose a hybrid content caching design that does not require the knowledge of content popularity. Specifically, our design optimizes the content caching locations, which can be original content servers, central cloud units (CUs) and base stations (BSs) where the design objective is to support as high average requested content data rates as possible subject to the finite service latency. We fulfill this design by employing the Lyapunov optimization approach to tackle an NP-hard caching control problem with the tight coupling between CU caching and BS caching control decisions. Toward this end, we propose algorithms in three specific caching scenarios by exploiting the submodularity property of the sum-weight objective function and the hierarchical caching structure. Moreover, we prove the proposed algorithms can achieve finite content service delay for all arrival rates within the constant fraction of capacity region using Lyapunov optimization technique. Furthermore, we propose practical and heuristic CU/BS caching algorithms to address a general caching scenario by inheriting the design rationale of the aforementioned performance-guaranteed algorithms. Trace-driven simulation demonstrates that our proposed hybrid CU/BS caching algorithms outperform the general popularity based caching algorithm and the independent caching algorithm in terms of average end-to-end service latency and backhaul/fronthaul load reduction ratios.
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