A Survey of Architecture, Framework and Algorithms for Resource Management in Edge Computing

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. Copyright © 2020 S. Premkumar et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.