Cuckoo-Neural Approach for Secure Execution and Energy Management in Mobile Cloud Computing

Vishal ,Bikrampal Kaur,Surender Jangra

doi:10.14569/ijacsa.2021.0120175

Abstract

Along with an explosive growth in mobile appli-cations and the emergence of the concept of cloud computing, in mobile cloud computing (MCC) has been familiarized as a potential technology for mobile users. Employing MCC to enable mobile users to realize the benefits of cloud computing in an environment friendly way is an effective strategy to meet today’s industrial demands. With the ever-increasing demand for MCC technology, energy efficiency has become extremely relevant in mobile cloud computing infrastructure. The concept of mobile cloud computing offers low cost and high availability to the mobile cloud users on pay-per-use basis. However, the challenges such as resource management and energy consumption are still faced by mobile cloud providers. If the allocation of the resources is not managed in a secure manner, the false allocation will lead to more energy consumption. This article demonstrates the importance of energy-saving mechanisms in cloud data centers and elaborates the importance of the “energy efficiency” relationship to promote the adoption of these mechanisms in practical scenarios. The utilization of resources are being maximized by minimizing the energy consumption. To achieve this, an integrated approach using Cuckoo Search (CS) with Artificial Neural network (ANN) is presented here. Initially, the Virtual Machines (VMs) are sorted as per their CPU utilization using Modified Best Fit Decreasing Approach (MBFD). This suffers from the increase in Service Level Agreement (SLA) violation along with many VM migrations. If the migration is not done at an appropriate host, which can hold the VM for long, Service Level Agreement Violation (SLAV) will be high.

Highlights

Mobile Cloud Computing (MCC) is the development of numerous internet-based technologies that allow mobile users to take advantage of cloud computing while using their mobile devices and achieve green computing [1,2]
The graph indicates that the number of migrations using the proposed MFCSNN approach is less compared to the existing Modified Best Fit Decreasing Approach (MBFD) approach
Power consumption has become a critical problem in the mobile cloud computing environment

Summary

Introduction

Mobile Cloud Computing (MCC) is the development of numerous internet-based technologies that allow mobile users to take advantage of cloud computing while using their mobile devices and achieve green computing [1,2]. By taking the advantages of all these techniques, MCC allows user to upload data and stored into the MCC cloud server [3]. It’s minimizes the loss of data risk for mobile users. This is possible by sending data to the mobile cloud [4]. MCC facilitate mobile user with a number of advantages, but still facing some challenging [5]. In this modern era, the population of smart phone users has increased intensely by some billions (see Fig. 1). The requirements have changed and most users prefer to transmit video data over cloud instead of text and images [7].

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