Publication | Open Access
Adaptive Resource Allocation for Computation Offloading
42
Citations
24
References
2019
Year
Cluster ComputingLoad Balancing (Computing)EngineeringDynamic Resource AllocationComputer ArchitectureCloud Load BalancingCloud Resource ManagementLinear SystemsAdaptive Resource AllocationService MetricsMobile Data OffloadingNetwork FlowsLoad BalancingComputer EngineeringEdge ServersComputer ScienceMobile ComputingEdge ArchitectureEdge ComputingCloud ComputingMulti-access Edge ComputingParallel ProgrammingScheduling (Project Management)Resource Optimization
Although mobile devices today 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 toward 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 quality of service metrics, whereas at the upper level, an optimizer tackles the problems of load balancing and application placement toward the maximization of the number the offloaded requests. The evaluation illustrates the effectiveness of the proposed offloading mechanism regarding the performance indicators, such as application average response time, and the optimal utilization of the computational resources of edge servers.
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