Improving Application Placement for Cluster-Based Web Applications

Dynamic application placement for clustered web applications heavily influences system performance and quality of user experience. Existing approaches claim that they strive to maximize the throughput, keep resource utilization balanced across servers, and minimize the start/stop cost of application instances. However, they fail to minimize the worst case of server utilization; the load balancing performance is not optimal. What´s more, some applications need to communicate with each other, which we called dependent applications; the network cost of them also should be taken into consideration. In this paper, we investigate how to minimize the resource utilization of servers in the worst case, aiming at improving load balancing among clustered servers. Our contribution is two-fold. First we propose and define a new optimization objectives: limiting the worst case of each individual server´s utilization, formulated by a min-max problem. A novel framework based on binary search is proposed to detect an optimal load balancing solution. Second, we define system cost as the weighted combination of both placement change and inter-application communication cost. By maximizing the number of instances of dependent applications that reside in the same set of servers, the basic load-shifting and placement-change procedures are enhanced to minimize whole system cost. Extensive experiments have been conducted and effectively demonstrate that: 1) the proposed framework achieves a good allocation for clustered web applications. In other words, requests are evenly allocated among servers, and throughput is still maximized; 2) the total system cost maintains at a low level; 3) our algorithm has the capacity of approximating an optimal solution within polynomial time and is promising for practical implementation in real deployments.