Resource Provisioning and Allocation in Function-as-a-Service Edge-Clouds
Resource Provisioning and Allocation in Function-as-a-Service Edge-Clouds
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DOI：
10.1109/tsc.2021.3052139
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发表时间：
2022-07-01
影响因子：
8.1
通讯作者：
Pavlou, George
中科院分区：
文献类型：
--
作者：
Ascigil, Onur;Tasiopoulos, Argyrios G.;Pavlou, George
边缘计算已经成为一种新的范式，使云应用程序更接近用户，以提高性能。与后端云系统不同，后端云系统将其资源整合在具有几乎无限容量的集中式数据中心位置，边缘云包括位于各个“计算点”的分布式资源，每个计算点的容量非常有限。在本文中，我们考虑功能即服务（FaaS）边缘云，其中应用程序提供商部署其延迟关键功能以处理具有严格响应时间期限的用户请求。在这种情况下，我们调查的问题，资源供应和分配。在制定最佳解决方案后，我们提出了从完全集中到完全分散的资源分配和配置算法。我们评估这些算法的性能，他们的能力，利用CPU资源，满足各种系统参数下的请求期限。我们的研究结果表明，实际的分散策略，这需要在计算点之间没有协调，实现的性能是接近最佳的完全集中的策略与协调开销。
Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. Unlike back-end cloud systems which consolidate their resources in a centralized data center location with virtually unlimited capacity, edge-clouds comprise distributed resources at various "computation spots", each with very limited capacity. In this article, we consider Function-as-a-Service (FaaS) edge-clouds where application providers deploy their latency-critical functions to process user requests with strict response time deadlines. In this setting, we investigate the problem of resource provisioning and allocation. After formulating the optimal solution, we propose resource allocation and provisioning algorithms across the spectrum of fully-centralized to fully-decentralized. We evaluate the performance of these algorithms in terms of their ability to utilize CPU resources and meet request deadlines under various system parameters. Our results indicate that practical decentralized strategies, which require no coordination among computation spots, achieve performance that is close to the optimal fully-centralized strategy with coordination overheads.