让我们共享虚拟机：MEC系统中基站间的最佳配置和定价
Let's Share VMs: Optimal Placement and Pricing across Base Stations in MEC Systems
摘要：
在移动边缘计算（MEC）系统中，用户将计算密集型任务卸载到基站处的边缘服务器。然而，由于整个网络的需求不均衡，某些地点的需求可能过多，而另一些地点的资源利用不足。为了解决MEC系统中的负载不平衡问题，在本文中，我们提出了虚拟机（VM）共享基站。具体来说，我们考虑跨基站的联合VM放置和定价问题，以匹配需求和供应，并在网络层面上实现收入最大化。为了使这个问题易于处理，我们将其分解为主问题和从问题。对于布局主问题，我们提出了一种基于连续时间马尔可夫链设计的马尔可夫近似算法MAP。对于定价奴隶问题，我们提出了OPA -一种最优虚拟机定价拍卖，其中所有用户都是真实的。此外，考虑到用户的潜在的不诚实行为，我们提出了一个激励兼容拍卖iCAT随着分区机制PUFF，我们证明了激励兼容性和收入保证。最后，我们结合MAP和OPA或PUFF来解决原问题，并分析最优性差距。仿真结果表明，协作基站可以增加高达50%的收入。
英文摘要：
In mobile edge computing (MEC) systems, users offload computationally intensive tasks to edge servers at base stations. However, with unequal demand across the network, there might be excess demand at some locations and underutilized resources at other locations. To address such load-unbalanced problem in MEC systems, in this paper we propose virtual machines (VMs) sharing across base stations. Specifically, we consider the joint VM placement and pricing problem across base stations to match demand and supply and maximize revenue at the network level. To make this problem tractable, we decompose it into master and slave problems. For the placement master problem, we propose a Markov approximation algorithm MAP on the design of a continuous time Markov chain. As for the pricing slave problem, we propose OPA - an optimal VM pricing auction, where all users are truthful. Furthermore, given users' potential untruthful behaviors, we propose an incentive compatible auction iCAT along with a partitioning mechanism PUFF, for which we prove incentive compatibility and revenue guarantees. Finally, we combine MAP and OPA or PUFF to solve the original problem, and analyze the optimality gap. Simulation results show that collaborative base stations increases revenue by up to 50%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
