Multilayer Architecture Model for Mobile Cloud Computing Paradigm

Abstract

Mobile Cloud Computing is one of today's more disruptive paradigms of computation due to its effects on the performance of mobile computing and the development of Internet of Things. It is able to enhance the capabilities of devices by outsourcing the workload to external computing platforms deployed along the network, such as cloud servers, cloudlets, or other edge platforms. The research described in this work presents a computational model of a multilayer architecture for increasing the performance of devices using the Mobile Cloud Computing paradigm. The main novelty of this work lies in defining a comprehensive model where all the available computing platforms along the network layers are involved to perform the outsourcing of the application workload. This proposal provides a generalization of the Mobile Cloud Computing paradigm which allows handling the complexity of scheduling tasks in such complex scenarios. The behaviour of the model and its ability of generalization of the paradigm are exemplified through simulations. The results show higher flexibility for making offloading decisions.

Mobile agent‐based service migration in mobile edge computing

“…However, mobile agents relatively do not require much external assistance; the optimization of them themselves is more important and effective. For this situation, Fernando et al 24 and Mora et al 25 also require further researches on mobile agent to meet increasingly complex needs. Our reference list also includes Wang et al 26,27 Wang et al 26 proposes a microservice coordination method for MEC, in which Markov decision process framework is used to coordinate problems and a reinforcement learning approach is adopted to find the optimal solution.…”

“…These auxiliary modules are not necessary for mobile agents but will make mobile agents unable to exert their intelligence. Then, different agents may have different migration strategies and algorithms, but servers in the container framework often use only one general algorithm when guiding container migration, 25 making it difficult to manage and utilize multiple methods. At last, the optimization work done by existing researches may not be suitable for mobile agents, because they are optimizations of the framework.…”

Efficient Multi-task offloading with energy and computational resources optimization in a mobile edge computing node

“…For the third solution and for comparison purpose, we take the version of the solution proposed by [5] and denote it Original Simulated Annealing Offloading (OSAO). In this solution, the local execution probability increases with the increase of the computing density.…”

“…Mobile Edge Computing (MEC) concept [1][2][3], it has been recognized as the next generation computing infrastructure that is based on Mobile Cloud Computing paradigm [4][5][6][7]. It can offer nearby customized services that require good transmission bandwidth, additional data storage and processing.…”

Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities

“…This paradigm plays a key role in the development of citizen-centric applications since edge computing can be deployed on several layers at the edge of the network, e.g. fog, mobile edge computing (MEC), ad hoc clouds, and cloudlets [7].…”