QUICK: QoS-guaranteed efficient cloudlet placement in wireless metropolitan area networks

This article defines the QoS-guaranteed efficient cloudlet deployment problem in wireless metropolitan area network, which aims to minimize the average access delay of mobile users, i.e., the average delay when service requests are successfully sent and being served by cloudlets. Meanwhile, we try to optimize total deployment cost represented by the total number of deployed cloudlets. For the first target, both un-designated capacity and constrained capacity cases are studied, and we have designed efficient heuristic and clustering algorithms, respectively. We show our algorithms are more efficient than the existing algorithm. For the second target, we formulate an integer linear programming to minimize the number of used cloudlets with given average access delay requirement. A clustering algorithm is devised to guarantee the scalability. For a special case of the deployment cost optimization problem where all cloudlets’ computing capabilities have been given, i.e., designated capacity, an efficient heuristic algorithm is further proposed to minimize the number of cloudlets. We finally evaluate the performance of proposed algorithms through extensive experimental simulations. Simulation results demonstrate the proposed algorithms are more than 46%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$46\%$$\end{document} efficient than existing algorithms on the average cloudlet access delay. Compared with existing algorithms, our proposed clustering and heuristic algorithms can reduce the number of deployed cloudlets by about 50%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$50\%$$\end{document} averagely, owing to the calculation processes of shortest paths between APs and the sorting processes of user access delays.