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A Survey of Computation Offloading for Mobile Systems

Published: 01 February 2013 Publication History

Abstract

Mobile systems have limited resources, such as battery life, network bandwidth, storage capacity, and processor performance. These restrictions may be alleviated by computation offloading: sending heavy computation to resourceful servers and receiving the results from these servers. Many issues related to offloading have been investigated in the past decade. This survey paper provides an overview of the background, techniques, systems, and research areas for offloading computation. We also describe directions for future research.

Cited By

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  • (2024)Multiple-Time-Slot Multiple Access Binary Computation Offloading in the $K$-User CaseIEEE Transactions on Signal Processing10.1109/TSP.2024.344419472(3927-3944)Online publication date: 1-Jan-2024
  • (2024)Energy-Latency Computation Offloading and Approximate Computing in Mobile-Edge Computing NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2024.336085021:3(3401-3415)Online publication date: 1-Jun-2024
  • (2024)A Survey of Computation Offloading With Task TypesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.341089625:8(8313-8333)Online publication date: 1-Aug-2024
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Information

Published In

cover image Mobile Networks and Applications
Mobile Networks and Applications  Volume 18, Issue 1
February 2013
169 pages

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 February 2013

Author Tags

  1. computation offloading
  2. energy
  3. mobile cloud computing
  4. performance
  5. survey

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Cited By

View all
  • (2024)Multiple-Time-Slot Multiple Access Binary Computation Offloading in the $K$-User CaseIEEE Transactions on Signal Processing10.1109/TSP.2024.344419472(3927-3944)Online publication date: 1-Jan-2024
  • (2024)Energy-Latency Computation Offloading and Approximate Computing in Mobile-Edge Computing NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2024.336085021:3(3401-3415)Online publication date: 1-Jun-2024
  • (2024)A Survey of Computation Offloading With Task TypesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.341089625:8(8313-8333)Online publication date: 1-Aug-2024
  • (2024)Machine learning-based computation offloading in multi-access edge computingJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2024.103090148:COnline publication date: 1-Mar-2024
  • (2024)A risk-aware and recommender distributed intrusion detection system for home robotsJournal of Information Security and Applications10.1016/j.jisa.2024.10377783:COnline publication date: 1-Jun-2024
  • (2024)Ovcosim: an open-source versatile computation offloading simulator for cloud and fog computingCluster Computing10.1007/s10586-023-04230-427:5(5647-5661)Online publication date: 1-Aug-2024
  • (2023)Reinforcement Contract Design for Vehicular-Edge Computing Scheduling and Energy Trading via Deep Q-Network With Hybrid Action SpaceIEEE Transactions on Mobile Computing10.1109/TMC.2023.332964323:6(6770-6784)Online publication date: 2-Nov-2023
  • (2023)PPO2: Location Privacy-Oriented Task Offloading to Edge Computing Using Reinforcement Learning for Intelligent Autonomous Transport SystemsIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2022.316942124:7(7599-7612)Online publication date: 1-Jul-2023
  • (2023)Offloading Using Traditional Optimization and Machine Learning in Federated Cloud–Edge–Fog Systems: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2023.323957925:2(1199-1226)Online publication date: 1-Apr-2023
  • (2023)A real-time and ACO-based offloading algorithm in edge computingJournal of Parallel and Distributed Computing10.1016/j.jpdc.2023.04.004179:COnline publication date: 1-Sep-2023
  • Show More Cited By

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