Abstract
Internet-based applications predominantly use the existing method of acquiring the computing resources remotely from the cloud data centers. This method of computation is not applicable in future since it is expected that the latencies in communication tend to expand largely due to the internet connectivity among billions of devices. This enormous expansion in latencies induces an adverse impact in the Quality of Service (QoS) and Quality of Experience (QoE) parameters. Edge computing is an imminent computing methodology that deploys the decentralized resources present at the edge of the network to make data processing within the proximity of user devices like smartphones, sensors or wearables. This approach is contrary to the conventional methods of utilizing centralized and distant cloud data centers. Managing the resources becomes a major challenge to be approached due to the diverse and rapidly evolving resources in comparison with the cloud. The lucrative role of Internet of Things (IoT) and Edge, and the challenges posed by the dynamic technologies are presented. This paper presents a survey of the research publications from edge computing from 2013 to 2020, covering the various architectures, frameworks, and the fundamental algorithms involved in resource management in edge computing.
Highlights
An appropriate medium for information exchange is facilitated by the growth of Internet-based wireless communication methodologies that has brought more convenience in people’s regular life
An extensive range of technical challenges regarding management of resources in fog/edge computing is approached in this survey work
Some demanding issues prevail with respect to the capacities and performance factors in fog/edge computing, few future research directions are discussed to confront the remaining issues
Summary
An appropriate medium for information exchange is facilitated by the growth of Internet-based wireless communication methodologies that has brought more convenience in people’s regular life. With recent advancements in the field of data science and artificial intelligence, the usage of lightweight, smart devices has attained a massive growth. The interconnectivity among devices, known as things, has paved the way for the evolution of Internet-based wireless communication networks [1]. It indicates the arrival of the Internet of Things (IoT) era bundled with huge sensing components, mobile devices and actuators utilized at the network edge. For every second, these interconnected devices generate a substantial volume of data
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