A Novel Approach of Reducing Energy Consumption by Utilizing Enthalpy in Mobile Cloud Computing

The Mobile Cloud Computing (MCC) technology is a growing technology that aids in improving the quality of mobile services. The resources in MCC are dynamically allocated to the users based on their needs. The users pay for the resources consumed by their programs, but the drawbacks of process failures and knapsack problems of resource allocation still exist in MCC. Furthermore, the scheduling of energy consumption and computational cost is very high. To solve these issues, an optimized energy efficiency resource management technique is set forth in this study. The recommended method holds two stages: a) the initial stage, when the task loss, transmission probability, delay, utilization and reputation for every single task is individually measured and the enthalpy was calculated, and b) the second stage, when the enthalpy-related Cuckoo Search Optimization (CSO) algorithm was used to optimize and prioritize the resources to the powerful resource management. The execution of the recommended method automatically reduced the knapsack issue, energy and cost. A formal analysis of the resource management framework has ensured that the provider executes resources based on the power consumption. The performance of the suggested algorithm was benchmarked against the performance of other conventional algorithms.