IEEE Access (Jan 2021)
A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications
Abstract
Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different applications which offer real-time latency features; however, it is difficult to handle the large volumes of data produced during the computational process, to adequately complete tasks. The decentralized edge computing process handles the task at the user’s end to accomplish latency applications, but recent research adopted centralized methodologies for computing in the edge network, placing additional overhead for cluster management and grouping. In this paper, we formulate an edge nodes group on task arrivals with a decentralized technique to process jobs, in a parallel mode, to complete execution. In addition, high availability will be added to promise effective processing of IoT based applications executed in the edge computing system. In the edge node environment, where resources are restricted, there is a requirement for high availability methods, which can deliver system reliability according to the local device information, without the data of network topology. In this paper, our technique is to enhance network reliability with the help of the edge node’s local information, which is executed in the distributed edge computing network, while also proposing a high availability technique to enhance the overall IoT environment. Our proposed Latency Aware Algorithm for Edge Computing with High Availability (LAAECHA) detects edge nodes faults, repairs edge nodes and replaces edge nodes with backups, using a new algorithm in a decentralized mode. Our research results show that the proposed LAAECHA method is more effective than existing methods, ensuring latency-aware IoT applications achieve their deadlines, while significantly reducing network traffic as well as guaranteeing system availability and reliability of the IoT network.
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