Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds

By Xinchen Lyu, Hui Tian, Cigdem Sengul, Ping Zhang. IEEE Transactions on Vehicular Technology, 2017

372 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/131e2ed3d64144da8f2dd70495a17ca0d930f8be

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (2019, neutral): “[27]–[29] - Review of how to exploit MEC and other edge computing paradigms for IoT applications.”
Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks (2017, methodology): “Furthermore, we consider that each user and BS have a single antenna for uplink transmissions (as also considered in [14], [35]).”
Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee (2018, methodology): “[13]) to the decision maker (DM) in the fog node [17].”
Edge-Computing-Enabled Smart Cities: A Comprehensive Survey (2019, neutral): “How does one effectively manage computation, communication, and storage resources between different players in smart cities to optimize the overall system performance? To answer this question, we must devise resource management schemes that consider energy [156]–[159], latency [160], traffic handlin”
Multi-Objective Resource Optimization for Hierarchical Mobile Edge Computing (2018, methodology): “However, this results in extra load on the back-haul network and the server [1].”
A Survey on Mobile Edge Computing: The Communication Perspective (2017, methodology): “, [87], [88], [96], [119], [121], [140], wireless channels were assumed to remain static during the whole task execution process for simplicity.”
Mobile Cooperative Computing: Energy-Efficient Peer-to-Peer Computation Offloading (2017, neutral): “On the other hand, algorithms for distributed resource allocation are designed in [10], [11] by solving formulated integer optimization problems using game theory and decomposition techniques.”