Joint Resource Allocation Using Evolutionary Algorithms in Heterogeneous Mobile Cloud Computing Networks

The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.

Collaborative Mobile Charging and Coverage

Wireless energy charging using mobile vehicles has been a viable research topic recently in the area of wireless networks and mobile computing. This paper gives a short survey of recent research conducted in our research group in the area of collaborative mobile charging. In collaborative mobile charging, multiple mobile chargers work together to accomplish a given set of ob jectives. These ob jectives include charging sensors at different frequencies with a minimum number of mobile chargers and reaching the farthest sensor for a given set of mobile chargers, subject to various constraints, including speed and energy limits of mobile chargers. Through the process of problem formulation, solution construction, and future work extension for problems related to collaborative mobile charging and coverage, we present three principles for good practice in conducting research. These principles can potentially be used for assisting graduate students in selecting a research problem for a term project, which can eventually be expanded to a thesis/dissertation topic.