An Optimized Multi-Layer Resource Management in Mobile Edge Computing Networks: A Joint Computation Offloading and Caching Solution
Amir Ziaeddini, Amin Mohajer, Davoud Yousefi, A.Mirzaei, Shu Gonglee

TL;DR
This paper presents a joint computation offloading and caching framework for mobile edge computing networks, optimizing resource management to significantly enhance throughput and energy efficiency at the cell edge.
Contribution
It introduces a novel distributed offloading technique combined with neural weighted optimization considering power flow and Lyapunov stability for improved MEC performance.
Findings
2-3 times increase in cell edge user throughput
Significant energy savings over existing techniques
Enhanced aggregate throughput per cluster
Abstract
Nowadays, data caching is being used as a high-speed data storage layer in mobile edge computing networks employing flow control methodologies at an exponential rate. This study shows how to discover the best architecture for backhaul networks with caching capability using a distributed offloading technique. This article used a continuous power flow analysis to achieve the optimum load constraints, wherein the power of macro base stations with various caching capacities is supplied by either an intelligent grid network or renewable energy systems. This work proposes ubiquitous connectivity between users at the cell edge and offloading the macro cells so as to provide features the macro cell itself cannot cope with, such as extreme changes in the required user data rate and energy efficiency. The offloading framework is then reformed into a neural weighted framework that considers…
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Taxonomy
TopicsCaching and Content Delivery · Energy Harvesting in Wireless Networks · Advanced MIMO Systems Optimization
