Cost Aware Cloudlet Placement for Big Data Processing at the Edge
As accessing computing resources from the remote cloud for big data processing inherently incurs high end-toend (E2E) delay for mobile users, cloudlets, which are deployed at the edge of networks, can potentially mitigate this problem. Although load offloading in cloudlet networks has been proposed, placing the cloudlets to minimize the deployment cost of cloudlet providers and E2E delay of user requests has not been addressed so far. The locations and number of cloudlets and their servers have a crucial impact on both the deployment cost and E2E delay of user requests. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing strategy (CAPABLE) to optimize the tradeoff between the deployment cost and E2E delay. When cloudlets are already placed in the network, we also design a load allocation scheme to minimize the E2E delay of user requests by assigning the workload of each region to the suitable cloudlets. The performance of CAPABLE is demonstrated by extensive simulation results.