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To Cache or Not to Cache: Stable Service Caching in Mobile Edge-Clouds of a Service Market

机译:缓存或不缓存:在服务市场的移动边缘云中稳定服务缓存

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Mobile edge computing (MEC) is emerging as an enabling technology of low-latency network services, such as Augmented Reality (AR) and Virtual Reality (VR), by deploying cloudlets in locations close to users. In MEC networks, telcooperators can place their services to cloudlets, such that the service accessing delay of users is minimized. In this paper, we investigate a fundamental problem of caching services that are originally deployed in remote clouds to cloudlets in an MEC network within the proximity of users. Specifically, we focus on the service caching problem in a two-tiered MEC network with both remote clouds and cloudlets that are close to users, in which multiple network service providers competing computing and bandwidth resources. This setting is significantly different from existing studies that focused on offloading user tasks from mobile devices to cloudlets in MEC networks that typically do not consider a service market with multiple network service providers. For the service caching problem in a two-tiered MEC network, we propose a novel approximation-restricted framework that guarantees the stableness of the service market. Under the proposed framework, an approximation algorithm with an approximation ratio for the problem with non-selfish players and an efficient, stable Stackelberg congestion game with selfish players have been proposed. We also analyze the Price of Anarchy (PoA) of the proposed Stackelberg congestion game to measure the efficiency of the proposed game degrades due to selfish behavior of network service providers. We finally evaluate the performance of our mechanism on both simulated environments and a real test-bed. Results show that the performance of our proposed mechanism is promising.
机译:移动边缘计算(MEC)是作为低延迟网络服务的启用技术,例如增强现实(AR)和虚拟现实(VR),通过将Cloudlet部署在靠近用户附近的位置。在MEC网络中,电视机可以将他们的服务放在Cloudlets上,使得用户访问用户的服务被最小化。在本文中,我们调查了在用户附近的MEC网络中最初部署到MEC网络中的远程云中的缓存服务的基本问题。具体而言,我们专注于双层MEC网络中的服务缓存问题,其中包括靠近用户的远程云和Cloudlet,其中多个网络服务提供商竞争计算和带宽资源。此设置与现有的研究显着不同,这些研究集中在MEC网络中从移动设备卸载到MEC网络中的Cloudlets,这些研究通常不考虑与多个网络服务提供商的服务市场。对于双层MEC网络中的服务缓存问题,我们提出了一种新颖的近似受限制的框架,可确保服务市场的稳定性。在所提出的框架下,已经提出了一种近似算法,具有非自私玩家的问题的近似率和具有自私参与者的高效稳定的Stackelberg拥塞游戏。我们还分析了拟议的Stackelberg拥塞游戏的无政府状态(POA)的价格来衡量所提出的游戏效率因网络服务提供商的自私行为而退化。我们终于评估了我们在模拟环境和真正的测试床上的机制的表现。结果表明,我们提出的机制的表现很有前景。

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