Hierarchical Load Balancing and Clustering Technique for Home Edge Computing
Hierarchical Load Balancing and Clustering Technique for Home Edge Computing
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DOI：
10.1109/access.2020.3007944
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发表时间：
2020-01-01
期刊：
影响因子：
3.9
通讯作者：
Kadobayashi, Youki
中科院分区：
文献类型：
--
作者：
Babou, Cheikh Saliou Mbacke;Fall, Doudou;Kadobayashi, Youki
边缘计算系统备受关注，有望满足新兴物联网应用所需的超低响应时间。然而，由于存在诸如新出现的需要非常敏感延迟的流量等延迟问题，提出了一种新的边缘计算系统架构，即支持这些实时应用的家庭边缘计算（HEC）。HEC是一个三层架构，由离用户非常近的HEC服务器、多接入边缘计算（MEC）服务器和中央云组成。针对HEC服务器资源有限导致的延迟问题，提出了一种解决方案。流量速率的增加在这些服务器上创建了一个很长的队列，也就是说，请求的处理时间（延迟）增加了。通过利用集群和负载平衡技术，我们提出了一种名为HEC-Clustering Balance的新技术。它允许我们在HEC集群上分层地分发请求，并且架构的另一个重点是避免HEC服务器上的拥塞，从而减少延迟。结果表明，HEC-Clustering Balance比基线聚类和负载平衡技术更有效。因此，与HEC架构相比，我们在两个实验场景中分别将HEC服务器上的处理时间减少了19%和73%。
The edge computing system attracts much more attention and is expected to satisfy ultra-low response time required by emerging IoT applications. Nevertheless, as there were problems on latency such as the emerging traffic requiring very sensitive delay, a new Edge Computing system architecture, namely Home Edge Computing (HEC) supporting these real-time applications has been proposed. HEC is a three-layer architecture made up of HEC servers, which are very close to users, Multi-access Edge Computing (MEC) servers and the central cloud. This paper proposes a solution to solve the problems of latency on HEC servers caused by their limited resources. The increase in the traffic rate creates a long queue on these servers, i.e., a raise in the processing time (delay) for requests. By leveraging, based on clustering and load balancing techniques, we propose a new technique called HEC-Clustering Balance. It allows us to distribute the requests hierarchically on the HEC clusters and another focus of the architecture to avoid congestion on a HEC server to reduce the latency. The results show that HEC-Clustering Balance is more efficient than baseline clustering and load balancing techniques. Thus, compared to the HEC architecture, we reduce the processing time on the HEC servers to 19% and 73% respectively on two experimental scenarios.