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无线城域网中的经济有效的边缘服务器放置。

Cost-Effective Edge Server Placement in Wireless Metropolitan Area Networks.

机构信息

School of Software, Central South University, Changsha 410083, China.

Department of Computer Science, New York Institute of Technology, New York, NY 10023, USA.

出版信息

Sensors (Basel). 2018 Dec 21;19(1):32. doi: 10.3390/s19010032.

DOI:10.3390/s19010032
PMID:30577685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6339009/
Abstract

Remote clouds are gradually unable to achieve ultra-low latency to meet the requirements of mobile users because of the intolerable long distance between remote clouds and mobile users and the network congestion caused by the tremendous number of users. Mobile edge computing, a new paradigm, has been proposed to mitigate aforementioned effects. Existing studies mostly assume the edge servers have been deployed properly and they just pay attention to how to minimize the delay between edge servers and mobile users. In this paper, considering the practical environment, we investigate how to deploy edge servers effectively and economically in wireless metropolitan area networks. Thus, we address the problem of minimizing the number of edge servers while ensuring some QoS requirements. Aiming at more consistence with a generalized condition, we extend the definition of the dominating set, and transform the addressed problem into the minimum dominating set problem in graph theory. In addition, two conditions are considered for the capacities of edge servers: one is that the capacities of edge servers can be configured on demand, and the other is that all the edge servers have the same capacities. For the on-demand condition, a greedy based algorithm is proposed to find the solution, and the key idea is to iteratively choose nodes that can connect as many other nodes as possible under the delay, degree and cluster size constraints. Furthermore, a simulated annealing based approach is given for global optimization. For the second condition, a greedy based algorithm is also proposed to satisfy the capacity constraint of edge servers and minimize the number of edge servers simultaneously. The simulation results show that the proposed algorithms are feasible.

摘要

远程云由于远程云和移动用户之间无法忍受的长距离以及大量用户导致的网络拥塞，逐渐无法实现超低延迟以满足移动用户的要求。一种新的范例——移动边缘计算已被提出以缓解上述影响。现有研究大多假设边缘服务器已经被正确部署，它们只关注如何最小化边缘服务器和移动用户之间的延迟。在本文中，考虑到实际环境，我们研究了如何在无线城域网中有效地、经济地部署边缘服务器。因此，我们解决了在确保某些服务质量要求的同时最小化边缘服务器数量的问题。为了更符合一般情况，我们扩展了支配集的定义，并将所解决的问题转化为图论中的最小支配集问题。此外，我们考虑了两种边缘服务器容量的情况：一种是边缘服务器的容量可以按需配置，另一种是所有边缘服务器的容量都相同。对于按需配置的情况，我们提出了一种基于贪婪的算法来找到解决方案，其关键思想是在延迟、度数和簇大小约束下迭代选择可以连接尽可能多其他节点的节点。此外，我们还提出了一种基于模拟退火的全局优化方法。对于第二种情况，我们还提出了一种基于贪婪的算法来同时满足边缘服务器的容量约束并最小化边缘服务器的数量。仿真结果表明，所提出的算法是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff20/6339009/48f1cc4c76d8/sensors-19-00032-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff20/6339009/c3d5f2daee9d/sensors-19-00032-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff20/6339009/857d2f18857c/sensors-19-00032-g010.jpg
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