A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation

Mobile edge caching/computing (MEC) has been emerging as a promising paradigm to provide ultra-high rate, ultra-reliable, and/or low-latency communications in future wireless networks. In this paper, we introduce a novel MEC network architecture that leverages the optimal joint caching-delivering wi...

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Veröffentlicht in:IEEE transactions on mobile computing Jg. 20; H. 1; S. 19 - 31
Hauptverfasser: Saputra, Yuris Mulya, Hoang, Dinh Thai, Nguyen, Diep N., Dutkiewicz, Eryk
Format: Magazine Article
Sprache:Englisch
Veröffentlicht: Los Alamitos IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Bandwidth
branch-and-bound
Caching
Computer architecture
Cooperation
Cooperative caching
Decisions
delay
Delays
Design optimization
Edge computing
horizontal cooperative caching
interior-point
joint caching-delivering
Mixed integer
Mobile computing
Mobile edge caching
Network architecture
Network latency
Network topologies
Nonlinear programming
Optimization
Servers
Storage capacity
Wireless communications
Wireless networks
ISSN:1536-1233, 1558-0660
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Zusammenfassung:Mobile edge caching/computing (MEC) has been emerging as a promising paradigm to provide ultra-high rate, ultra-reliable, and/or low-latency communications in future wireless networks. In this paper, we introduce a novel MEC network architecture that leverages the optimal joint caching-delivering with horizontal cooperation among mobile edge nodes (MENs). To that end, we first formulate the content-access delay minimization problem by jointly optimizing the content caching and delivering decisions under various network constraints (e.g., network topology, storage capacity and users' demands at each MEN). However, the strongly mutual dependency between the decisions makes the problem a nested dual optimization that is proved to be NP-hard. To deal with it, we propose a novel transformation method to transform the nested dual problem to an equivalent mixed-integer nonlinear programming (MINLP) optimization problem. Then, we design a centralized solution using an improved branch-and-bound algorithm with the interior-point method to find the joint caching and delivering policy which is within 1 percent of the optimal solution. Since the centralized solution requires the full network topology and information from all MENs, to make our solution scalable, we develop a distributed algorithm which allows each MEN to make its own decisions based on its local observations. Extensive simulations demonstrate that the proposed solutions can reduce the total average delay for the whole network up to 40 percent compared with other current caching policies. Furthermore, the proposed solutions also increase the cache hit ratio for the network up to 4 times, thereby dramatically reducing the traffic load on the backhaul network.
Bibliographie:ObjectType-Article-1
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ISSN:1536-1233
1558-0660
DOI:10.1109/TMC.2019.2938510