Energy and Latency-Aware Computation Offloading and Resource Allocation for a Multi-Access Edge Computing-Enabled Heterogeneous Network

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PubDate: December 2021

Teams: Ahsanullah University of Science and Technology

Writers: Mobasshir Mahbub; Bobby Barua

PDF: Energy and Latency-Aware Computation Offloading and Resource Allocation for a Multi-Access Edge Computing-Enabled Heterogeneous Network

Abstract

The 5th generation (5G) cellular network and support technologies are being developed and used to fulfill the growing demand for mobile data traffic and satisfy the demanding requirements of the upcoming Internet of Things (IoT) applications such as the intelligent city, interactive healthcare, augmented/virtual reality (AR/VR), etc. Multi-access edge computing (MEC), an evolving 5G technology and a core enabler, which combines telecom and IT services, provides cloud computing at the edge of the RAN (radio access network). MEC can minimize latency for end-user equipment by offering computing and storage capacity at the edge. Therefore the paper presented approaches and measurements for efficient computation offloading and radio resource allocation for the uplink (UL) concerning the MEC services.

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