M
Mike Jia
Researcher at Australian National University
Publications - 15
Citations - 1365
Mike Jia is an academic researcher from Australian National University. The author has contributed to research in topics: Cloudlet & Cloud computing. The author has an hindex of 13, co-authored 15 publications receiving 997 citations.
Papers
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Journal ArticleDOI
Optimal Cloudlet Placement and User to Cloudlet Allocation in Wireless Metropolitan Area Networks
TL;DR: An algorithm is devised that enables the placement of the cloudlets at user dense regions of the WMAN, and assigns mobile users to the placed cloudlets while balancing their workload, which indicates that the performance of the proposed algorithm is very promising.
Journal ArticleDOI
Efficient Algorithms for Capacitated Cloudlet Placements
TL;DR: This paper studies the cloudlet placement problem in a large-scale Wireless Metropolitan Area Network (WMAN) consisting of many wireless Access Points (APs) with the objective to minimize the average access delay between mobile users and the cloudlets serving the users.
Proceedings ArticleDOI
Heuristic offloading of concurrent tasks for computation-intensive applications in mobile cloud computing
Mike Jia,Jiannong Cao,Lei Yang +2 more
TL;DR: This paper presents an online task offloading algorithm that minimizes the completion time of the application on the mobile device and is significantly better than other existing algorithms.
Proceedings ArticleDOI
Cloudlet load balancing in wireless metropolitan area networks
TL;DR: This paper introduces a system model to capture the response times of offloaded tasks, and proposes a fast, scalable algorithm for the problem to find an optimal redirection of tasks between cloudlets such that the maximum of the average response times at cloudlets is minimized.
Proceedings ArticleDOI
Capacitated cloudlet placements in Wireless Metropolitan Area Networks
TL;DR: This paper considers placing multiple cloudlets with different computing capacities at some strategic local locations in a WMAN to reduce the average cloudlet access delay of mobile users at different APs and proposes a fast yet efficient heuristic.