Optimal Cloudlet Selection in Edge Computing for Resource Allocation

Mobile and Edge Computing devices have limited resources to perform computationally intensive jobs, and hence, there is a need for task offloading. In Mobile Cloud Computing, cloud servers are placed far from the user devices; as a consequence, many challenges are faced, such as security, limited bandwidth, network latency, and storage. Whereas edge servers are placed near the user devices in Edge Cloud Computing; however, issues of Cloud computing are also faced in Edge computing due to the huge number of devices, which also generates a significant load on edge servers. Some resource optimization approaches help in achieving optimal Cloudlet selection at the edge servers. When users access edge resources, such as CPU, memory, and hard disk, load balancing helps in distributing tasks among edge servers and achieving efficient results. The user devices communicate either within a Cloudlet or between Cloudlets using resource sharing, in which one of the main issues is optimal Cloudlet selection. This paper presents an optimal Cloudlet selection algorithm in which, first of all, an index value for each resource is calculated using parameters like weight, cluster of Cloudlets, availability, and total resource usage. Thereafter, the resource level and available resources of this level are calculated for each Cloudlet. Finally, an algorithm is proposed to help in finding the optimal Cloudlet for the cloud broker. The proposed approach is implemented in Cloud-Sim. The simulation results have shown efficiency of the proposed approach. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.