Energy and Delay Aware Computation Offloading Scheme in MCC Environment

• Published in: 2022 5th Conference on Cloud and Internet of Things (CIoT) pp. 247 - 254
• Main Authors: Sufyan, Farhan, Chishti, Mohd Sameen, Banerjee, Amit
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.03.2022
• Subjects: Cloud computing; Computation Offloading; Computational modeling; Delays; Energy consumption; Mobile Cloud Computing (MCC); Quality of service; Queuing Theory; Simulation; Smart Devices (SDs); Stochastic processes
• DOI: 10.1109/CIoT53061.2022.9766509

Computation Offloading is a technique that utilizes cloud resources to maintain the QoS of computation-intensive applications executed on resource-constrained smart devices (SDs). Researchers have proposed various profiling-based offloading frameworks to minimize the execution delay and extend the battery lifetime of the SDs. Most of these offloading strategies rely on the availability of infinite cloud resources to spun independent VMs for profiling the SDs, which may not be an efficient method to handle the increasing application demands of the SDs. To address this, we investigate a generic mobile cloud computing (MCC) computation offloading framework for handling the computational demands generated by a large number of SDs. The framework utilizes appropriate queuing models to simulate the traffic generated by the SDs and formulate a non-linear multi-objective optimization problem to minimize the energy consumption and execution delay of the SDs. Finally, we propose a Stochastic Gradient descent (SGD) solution that jointly optimizes offloading probability and transmission power to find the optimal trade-off between the offloading objectives. Simulation results show the proposed system's effectiveness and efficiency for an increasing number of SDs.