Although mobile devices nowadays have powerful hardware and networking capabilities, they fall short when it comes to executing compute-intensive applications. Computation Offloading, i.e. delegating resource consuming tasks to servers located at the edge of the network, contributes towards moving to a Mobile Cloud Computing paradigm. In this work, a two-level resource allocation and admission control mechanism for a cluster of edge servers, offers an alternative choice to mobile users for executing their tasks. At the lower level, the behavior of edge servers is modeled by a set of linear systems, and linear controllers are designed to meet the system’s constraints and QoS metrics, while at the upper level, an optimizer tackles the problems of load balancing and application placement towards the maximization of the number the offloaded requests. The evaluation illustrates the effectiveness of the proposed offloading mechanism regarding the performance indicators, e.g. application average response time, and the optimal utilization of the computational resources of edge servers.
Avgeris, M., Dechouniotis, D., Athanasopoulos, N., & Papavassiliou, S. (2019). Adaptive Resource Allocation for Computation Offloading: A Control-Theoretic Approach. ACM Transactions on Internet Technology (TOIT), 19(2), . https://doi.org/10.1145/3284553