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A Comprehensive Analysis on Mobile Edge Computing: Joint Offloading and Resource Allocation Perspective

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Machine Learning and Big Data Analytics (ICMLBDA 2022)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 401))

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Abstract

The exponential growth of distributed IoT devices and mobile applications is the driving force for the smart world solutions. Cloud, cloudlets and mobile edge computing are the promising solutions for ubiquitous and on-demand user applications at the edge device. Edge computing is the current industry requirement to provide low latency services. Offloading techniques play a phenomenal role in edge computing environment in terms of dynamic decision making on task execution location that depends on the delay, size of the task and many other factors. Hence, offloading strategies in mobile edge computing are a vast research area which needs more focus. This paper focused on various offloading strategies and their comparison as this study gives a valuable start to fellow researchers who are interested in offloading techniques in mobile edge computing.

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References

  1. CISCO (2020) Cisco Annual Internet Report (2018–2023).White Paper. Source: https://www.cisco.com/c/en/us/solutions/ollateral/executiveperspectives/annualinternet-report/white-paper-c11741490.pdf.

  2. Vanathi Arunachalam, Nagamalleswara Rao Nallamothu, “Load Balancing in RPL to Avoid Hotspot Problem for Improving Data Aggregation in IoT” in International Journal of Intelligent Engineering & Systems, vol. 14, no. 1, 2021 https://doi.org/10.22266/ijies2021.0228.49.

  3. Z. Zhao et al., “A Novel Framework of Three-Hierarchical Offloading Optimization for MEC in Industrial IoT Networks,” in IEEE Transactions on Industrial Informatics, vol. 16, no. 8, pp. 5424–5434, Aug. 2020, https://doi.org/10.1109/TII.2019.2949348.

  4. J. Guo, H. Zhang, L. Yang, H. Ji and X. Li, “Decentralized Computation Offloading in Mobile Edge Computing Empowered Small-Cell Networks,” 2017 IEEE Globecom Workshops (GC Wkshps), 2017, pp. 1–6, https://doi.org/10.1109/GLOCOMW.2017.8269049.

    Article  Google Scholar 

  5. Q. Pham, T. Leanh, N. H. Tran, B. J. Park and C. S. Hong, “Decentralized Computation Offloading and Resource Allocation for Mobile-Edge Computing: A Matching Game Approach,” in IEEE Access, vol. 6, pp. 75868–75885, 2018, https://doi.org/10.1109/ACCESS.2018.2882800.

  6. Y. Mao, J. Zhang and K. B. Letaief, “Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices,” in IEEE Journal on Selected Areas in Communications, vol. 34, no. 12, pp. 3590–3605, Dec. 2016, https://doi.org/10.1109/JSAC.2016.2611964.

  7. T. X. Tran and D. Pompili, “Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks,” in IEEE Transactions on Vehicular Technology, vol. 68, no. 1, pp. 856–868, Jan. 2019, https://doi.org/10.1109/TVT.2018.2881191.

  8. Y. Mao, J. Zhang and K. B. Letaief, “Joint Task Offloading Scheduling and Transmit Power Allocation for Mobile-Edge Computing Systems,” 2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017, pp. 1–6, https://doi.org/10.1109/WCNC.2017.7925615.

    Article  Google Scholar 

  9. Y. Mao, J. Zhang, S. H. Song and K. B. Letaief, “Stochastic Joint Radio and Computational Resource Management for Multi-User Mobile-Edge Computing Systems,” in IEEE Transactions on Wireless Communications, vol. 16, no. 9, pp. 5994–6009, Sept. 2017, https://doi.org/10.1109/TWC.2017.2717986.

  10. Q. Tang, R. Xie, F. R. Yu, T. Huang and Y. Liu, “Decentralized Computation Offloading in IoT Fog Computing System With Energy Harvesting: A Dec-POMDP Approach,” in IEEE Internet of Things Journal, vol. 7, no. 6, pp. 4898–4911, June 2020, https://doi.org/10.1109/JIOT.2020.2971323.

  11. Y. Sun, T. Wei, H. Li, Y. Zhang and W. Wu, “Energy-Efficient Multimedia Task Assignment and Computing Offloading for Mobile Edge Computing Networks,” in IEEE Access, vol. 8, pp. 36702–36713, 2020, https://doi.org/10.1109/ACCESS.2020.2973359.

  12. M. I. A. Zahed, I. Ahmad, D. Habibi and Q. V. Phung, “Green and Secure Computation Offloading for Cache-Enabled IoT Networks,” in IEEE Access, vol. 8, pp. 63840–63855, 2020, https://doi.org/10.1109/ACCESS.2020.2982669.

  13. Z. Li, C. Du and S. Chen, “HIQCO: A Hierarchical Optimization Method for Computation Offloading and Resource Optimization in Multi-Cell Mobile-Edge Computing Systems,” in IEEE Access, vol. 8, pp. 45951–45963, 2020, https://doi.org/10.1109/ACCESS.2020.2977988.

  14. Y. Guo et al., “Intelligent Offloading Strategy Design for Relaying Mobile Edge Computing Networks,” in IEEE Access, vol. 8, pp. 35127–35135, 2020, https://doi.org/10.1109/ACCESS.2020.2972106.

  15. H. Chen, D. Zhao, Q. Chen and R. Chai, “Joint Computation Offloading and Radio Resource Allocations in Small-Cell Wireless Cellular Networks,” in IEEE Transactions on Green Communications and Networking, vol. 4, no. 3, pp. 745–758, Sept. 2020, https://doi.org/10.1109/TGCN.2020.2976932.

  16. K. Wang et al., “Joint Offloading and Charge Cost Minimization in Mobile Edge Computing,” in IEEE Open Journal of the Communications Society, vol. 1, pp. 205–216, 2020, https://doi.org/10.1109/OJCOMS.2020.2971647.

  17. X. Lyu et al., “Selective Offloading in Mobile Edge Computing for the Green Internet of Things,” in IEEE Network, vol. 32, no. 1, pp. 54–60, Jan.-Feb. 2018, https://doi.org/10.1109/MNET.2018.1700101.

  18. L. Liu, X. Qin, Z. Zhang and P. Zhang, “Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems,” in IEEE Access, vol. 8, pp. 38248–38261, 2020, https://doi.org/10.1109/ACCESS.2020.2976048.

  19. N. Kiran, C. Pan, S. Wang and C. Yin, “Joint resource allocation and computation offloading in mobile edge computing for SDN based wireless networks,” in Journal of Communications and Networks, vol. 22, no. 1, pp. 1–11, Feb. 2020, https://doi.org/10.1109/JCN.2019.000046.

  20. X. Chen, L. Jiao, W. Li and X. Fu, “Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing,” in IEEE/ACM Transactions on Networking, vol. 24, no. 5, pp. 2795–2808, October 2016, https://doi.org/10.1109/TNET.2015.2487344.

  21. Y. Geng, Y. Yang and G. Cao, “Energy-Efficient Computation Offloading for Multicore-Based Mobile Devices,” IEEE INFOCOM 2018 – IEEE Conference on Computer Communications, 2018, pp. 46–54, https://doi.org/10.1109/INFOCOM.2018.8485875.

  22. J. Zhao, Q. Li, Y. Gong and K. Zhang, “Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks,” in IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 7944–7956, Aug. 2019, https://doi.org/10.1109/TVT.2019.2917890.

  23. C. Wang, F. R. Yu, C. Liang, Q. Chen and L. Tang, “Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing,” in IEEE Transactions on Vehicular Technology, vol. 66, no. 8, pp. 7432–7445, Aug. 2017, https://doi.org/10.1109/TVT.2017.2672701.

  24. S. Bi and Y. J. Zhang, “Computation Rate Maximization for Wireless Powered Mobile-Edge Computing With Binary Computation Offloading,” in IEEE Transactions on Wireless Communications, vol. 17, no. 6, pp. 4177–4190, June 2018, https://doi.org/10.1109/TWC.2018.2821664.

  25. H. Sun, F. Zhou and R. Q. Hu, “Joint Offloading and Computation Energy Efficiency Maximization in a Mobile Edge Computing System,” in IEEE Transactions on Vehicular Technology, vol. 68, no. 3, pp. 3052–3056, March 2019, https://doi.org/10.1109/TVT.2019.2893094.

  26. J. Ren, G. Yu, Y. Cai, Y. He and F. Qu, “Partial Offloading for Latency Minimization in Mobile-Edge Computing,” GLOBECOM 2017 – 2017 IEEE Global Communications Conference, 2017, pp. 1–6, https://doi.org/10.1109/GLOCOM.2017.8254550.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jawaharlal Nehru Technological University Kakinada, Kakinada, Andhra Pradesh, India

    Antharaju K. Chakravarthy & N. Ramakrishnaiah

  2. Department of Information Technology, Aditya Engineering College (A), Surampalem, Andhra Pradesh, India

    Antharaju K. Chakravarthy

  3. Jawaharlal Nehru Technological University Kakinada, Kakinada, Andhra Pradesh, India

    Antharaju K. Chakravarthy & T. Rama Reddy

  4. Department of Computer Science and Engineering, Aditya Engineering College (A), Surampalem, Andhra Pradesh, India

    T. Rama Reddy

Authors
  1. Antharaju K. Chakravarthy
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  2. T. Rama Reddy
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  3. N. Ramakrishnaiah
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science & Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Rajiv Misra

  2. Cardiff University, Cardiff, UK

    Rana Omer

  3. Dept. of EE Engineering, University of London, London, UK

    Muttukrishnan Rajarajan

  4. Dept. of ECE, National University of Singapore, Singapore, Singapore

    Bharadwaj Veeravalli

  5. Dept. of Computer Science, Central University of Rajasthan, Tehsil Kishangarh, Rajasthan, India

    Nishtha Kesswani

  6. Dept. of CSE, Indian Institute of Information Technology, Kota, Jawahar Lal Nehru Marg, Rajasthan, India

    Priyanka Mishra

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Chakravarthy, A.K., Rama Reddy, T., Ramakrishnaiah, N. (2023). A Comprehensive Analysis on Mobile Edge Computing: Joint Offloading and Resource Allocation Perspective. In: Misra, R., Omer, R., Rajarajan, M., Veeravalli, B., Kesswani, N., Mishra, P. (eds) Machine Learning and Big Data Analytics. ICMLBDA 2022. Springer Proceedings in Mathematics & Statistics, vol 401. Springer, Cham. https://doi.org/10.1007/978-3-031-15175-0_1

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