Optimized Resource Sharing in Mobile Cloud Computing for Reducing Service Latency

Abstract

Fog computing is a notion that merges the benefits of cloud and edge devices to furnish excellent services, diminish delay, offer mobility assistance, multi-user access, and other characteristics that maintain current computing systems. It is also identified as fogging or fog networking. This write-up introduces a numerical structure for dissimilar resource allocation via task-driven usefulness functions based on the combination of Mayfly and Reformed Multi-Objective Particle Swarm Optimization (RMPSO), referred to as MRMPSO. An idea with the organization of multi-goal function is brought and projected to prior to a fresh and innovative optimization set of rules for updating the rate of the fundamental mayfly set of rules. The RMPSO with function of the crossover series permits each and every mayfly adopting its non-public conduct to make it quicker with the organization information. In multi-level mayfly set of rules, speed is updated, based at the offspring’s first-class function of the mayfly. At the identical time, it is brought with prominence to offer higher resource sharing characteristics. This framework includes cloud computing, mobile cloud computing (MCC), and mobile edge computing (MEC), with the aim of enhancing the QoS (quality of service) among terminal devices and the cloud. Taxonomy of MCC is proposed based on current research in the field, covering confidential challenges, data management, operational and service issues. The review identifies challenges and potential applications in cloud computing, with security, privacy, communication and application challenges being prominent in addition to the academic contributions. The article also explores potential applications of MCC, such as healthcare, smart city, and agriculture applications.