Abstract
Edge-cloud computing is an emerging computational model that allows offloading of service requests by the autonomous mobile agents from the edge-server to the cloud-server. This is to reduce the network latency prevalent in the cloud-IoT model. However, Quality-of-Service (QoS)-Aware computation offloading in a heterogeneous and dynamic edge-cloud environment remains an open problem. In this paper, we propose a queuing theory-based edge-cloud computing framework for QoS-aware offloading in mobile autonomous agents. This framework model decides whether to execute an incoming request to the edge-server on the edge itself or to offload to one of the heterogeneous cloud servers such that the request’s execution time is the minimum. To model a request’s execution time, we consider the processing capabilities and the queues overheads of the edge and cloud servers, and the edge-cloud communications’ time. The details of the evaluation results, using dataset generated from real-life scenarios, are presented in the paper.
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This work was funded by the National Water and Energy Center under Grant 31R215.
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Ismail, L., Materwala, H. (2021). IoT-Edge-Cloud Computing Framework for QoS-Aware Computation Offloading in Autonomous Mobile Agents: Modeling and Simulation. In: Bouzefrane, S., Laurent, M., Boumerdassi, S., Renault, E. (eds) Mobile, Secure, and Programmable Networking. MSPN 2020. Lecture Notes in Computer Science(), vol 12605. Springer, Cham. https://doi.org/10.1007/978-3-030-67550-9_11
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