Proceedings ArticleDOI
Content caching at the wireless network edge: A distributed algorithm via belief propagation
Juan Liu,Bo Bai,Jun Zhang,Khaled Ben Letaief +3 more
- pp 1-6
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TLDR
Simulation results show that the proposed low-complexity distributed algorithm can greatly reduce the average download delay by collaborative caching and transmissions.Abstract:
Caching popular contents at the edge of wireless networks has recently emerged as a promising technology to improve the quality of service for mobile users, while balancing the peak-to-average transmissions over backhaul links. In contrast to existing works, where a central coordinator is required to design the cache placement strategy, we consider a distributed caching problem which is highly relevant in dense network settings. In the considered scenario, each Base Station (BS) has a cache storage of finite capacity, and each user will be served by one or multiple BSs depending on the employed transmission scheme. A belief propagation based distributed algorithm is proposed to solve the cache placement problem, where the parallel computations are performed by individual BSs based on limited local information and very few messages passed between neighboring BSs. Thus, no central coordinator is required to collect the information of the whole network, which significantly saves signaling overhead. Simulation results show that the proposed low-complexity distributed algorithm can greatly reduce the average download delay by collaborative caching and transmissions.read more
Citations
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A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions
TL;DR: This paper presents a detailed survey on the emerging technologies to achieve low latency communications considering three different solution domains: 1) RAN; 2) core network; and 3) caching.
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Collaborative Cloud and Edge Computing for Latency Minimization
TL;DR: This work investigates the collaboration between cloud computing and edge computing, where the tasks of mobile devices can be partially processed at the edge node and at the cloud server and obtains the closed-form computation resource allocation strategy by leveraging the convex optimization theory.
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Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading
TL;DR: The novel partial compression offloading model can significantly reduce the end-to-end latency in a multi-user time-division multiple access MECO system with joint communication and computation resource allocation.
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Optimal and Scalable Caching for 5G Using Reinforcement Learning of Space-Time Popularities
TL;DR: In this paper, local and global Markov processes model user requests, and a reinforcement learning (RL) framework is put forth for finding the optimal caching policy when the transition probabilities involved are unknown, providing a simple, yet practical asynchronous caching approach.
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Mobility-aware caching for content-centric wireless networks: modeling and methodology
TL;DR: This article presents a general framework for mobility-aware caching in CCWNs, and key properties of user mobility patterns that are useful for content caching are first identified, and then different design methodologies for mobility -aware caching are proposed.
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Journal ArticleDOI
FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers
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TL;DR: This work shows that the uncoded optimum file assignment is NP-hard, and develops a greedy strategy that is provably within a factor 2 of the optimum, and provides an efficient algorithm achieving a provably better approximation ratio of 1-1/d d, where d is the maximum number of helpers a user can be connected to.