Abstract
Development of internet of things (IoT) and smart devices eased life by offering numerous applications targeting to provide real-time low latency services, but they also brought challenges in handling huge data generated from the powerful computations, to get a job done. Decentralized edge computing could help to achieve latency requirements of the applications by executing them closer to the user at edge of network, but most of the current studies actually deployed centralized approaches for cluster computing at edge, which put extra overhead of cluster formation and management. In this article, we propose to group heterogeneous edge nodes on task arrival with a more decentralized method and execute tasks in parallel to meet their deadline. On the other hand, to guarantee successful execution of critical IoT application running in an edge network, fault tolerance has to be significantly considered. For resource limited edge devices, there is a great need for efficient fault tolerance techniques, which can provide reliability based on device's local information, without worrying about overall network topology. In this article, our novel method is to increase task reliability being executed in distributed edge computing environment through finding reliability of an edge node locally, and by providing fault tolerance to increase overall application availability. Our proposed fault tolerance technique works in decentralized mode by executing new algorithms to handle above mentioned problems. Our experiment results show that our approach is effective as well as providing desired goals of achieving deadline for latency-aware IoT applications, with staggering decrease in overall network traffic along with ensuring reliability and availability.
Highlights
Internet of Things (IoT) is expanding day by day and making lives of individuals easier by offering many applications like smart cities, home automation, security surveillance, and smart health care at any time from any place
Single edge node might not be able to process the entire job of a solider well in time, decentralized computing could help to distribute tasks to nearby edge nodes and get the results quickly
In this paper, we have proposed a decentralized technique to leverage edge nodes to execute a resource intensive task inside the edge network to reduce the latency and by providing fault tolerance ensured availability in the error prone edge network
Summary
Internet of Things (IoT) is expanding day by day and making lives of individuals easier by offering many applications like smart cities, home automation, security surveillance, and smart health care at any time from any place. All of these devices and applications under umbrella of IoT are generating large amount of data, which can be very useful if analyzed properly well on time. Big data processing technologies usually use cloud-computing resources for big task processing, but accessing cloud resources from end user devices adds latency It requires high bandwidth and is not suitable. In edge computing where resources are available inside local network, it offers more privilege to a number of applications that require: a) low-latency real-time results; b) decentralization; c) location-oriented; d) mobility; e) heterogeneity [2]
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