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Mobility-Based Resource Allocation and Provisioning in Fog and Edge Computing Paradigms: Review, Challenges, and Future Directions

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Mobile Edge Computing

Abstract

Fog and Edge related computing paradigms promise to deliver exciting services in the Internet of Things (IoT) networks. The devices in such paradigms are highly dynamic and mobile, which presents several challenges to ensure service delivery with the utmost level of quality and guarantee. Achieving effective resource allocation and provisioning in such computing environments is a difficult task. Resource allocation and provisioning are one of the well-studied domains in the Cloud and other distributed paradigms. Lately, there have been several studies that have tried to explore the mobility of end devices in-depth and address the associated challenges in Fog and Edge related computing paradigms. But, the research domain is yet to be explored in detail. As such, this chapter reflects the current state-of-the-art of the methods and technologies used to manage the resources to support mobility in Fog and Edge environments. The chapter also highlights future research directions to efficiently deliver smart services in real-time environments.

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References

  1. Sneha Tammishetty, T Ragunathan, Sudheer Kumar Battula, B Varsha Rani, P RaviBabu, RaghuRamReddy Nagireddy, Vedika Jorika, and V Maheshwar Reddy. Iot-based traffic signal control technique for helping emergency vehicles. In Proceedings of the First International Conference on Computational Intelligence and Informatics, pages 433–440. Springer, 2017.

    Google Scholar 

  2. KC Ujjwal, Saurabh Garg, James Hilton, Jagannath Aryal, and Nicholas Forbes-Smith. Cloud computing in natural hazard modeling systems: Current research trends and future directions. International Journal of Disaster Risk Reduction, page 101188, 2019.

    Google Scholar 

  3. Hamidreza Arasteh, Vahid Hosseinnezhad, Vincenzo Loia, Aurelio Tommasetti, Orlando Troisi, Miadreza Shafie-khah, and Pierluigi Siano. Iot-based smart cities: a survey. In 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), pages 1–6. IEEE, 2016.

    Google Scholar 

  4. Flavio Bonomi, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pages 13–16, 2012.

    Google Scholar 

  5. Sudheer Kumar Battula, Saurabh Garg, James Montgomery, and Byeong Ho Kang. An efficient resource monitoring service for fog computing environments. IEEE Transactions on Services Computing, 2019.

    Google Scholar 

  6. Jürgo S Preden, Kalle Tammemäe, Axel Jantsch, Mairo Leier, Andri Riid, and Emine Calis. The benefits of self-awareness and attention in fog and mist computing. Computer, 48(7):37–45, 2015.

    Google Scholar 

  7. Ranesh Kumar Naha, Saurabh Garg, Dimitrios Georgakopoulos, Prem Prakash Jayaraman, Longxiang Gao, Yong Xiang, and Rajiv Ranjan. Fog computing: Survey of trends, architectures, requirements, and research directions. IEEE access, 6:47980–48009, 2018.

    Google Scholar 

  8. Sonia Shahzadi, Muddesar Iqbal, Tasos Dagiuklas, and Zia Ul Qayyum. Multi-access edge computing: open issues, challenges and future perspectives. Journal of Cloud Computing, 6(1):30, 2017.

    Google Scholar 

  9. Minh-Quang Tran, Duy Tai Nguyen, Van An Le, Duc Hai Nguyen, and Tran Vu Pham. Task placement on fog computing made efficient for iot application provision. Wireless Communications and Mobile Computing, 2019, 2019.

    Google Scholar 

  10. Maurizio Capra, Riccardo Peloso, Guido Masera, Massimo Ruo Roch, and Maurizio Martina. Edge computing: A survey on the hardware requirements in the internet of things world. Future Internet, 11(4):100, 2019.

    Google Scholar 

  11. Hasan Ali Khattak, Hafsa Arshad, Saif ul Islam, Ghufran Ahmed, Sohail Jabbar, Abdullahi Mohamud Sharif, and Shehzad Khalid. Utilization and load balancing in fog servers for health applications. EURASIP Journal on Wireless Communications and Networking, 2019(1):91, 2019.

    Google Scholar 

  12. Pavel Mach and Zdenek Becvar. Mobile edge computing: A survey on architecture and computation offloading. IEEE Communications Surveys & Tutorials, 19(3):1628–1656, 2017.

    Article  Google Scholar 

  13. Yonal Kirsal, Glenford Mapp, and Fragkiskos Sardis. Using advanced handover and localization techniques for maintaining quality-of-service of mobile users in heterogeneous cloud-based environment. Journal of Network and Systems Management, 27(4):972–997, 2019.

    Article  Google Scholar 

  14. Ranesh Kumar Naha, Saurabh Garg, Andrew Chan, and Sudheer Kumar Battula. Deadline-based dynamic resource allocation and provisioning algorithms in fog-cloud environment. Future Generation Computer Systems, 104:131–141, 2020.

    Google Scholar 

  15. Cheol-Ho Hong and Blesson Varghese. Resource management in fog/edge computing: a survey on architectures, infrastructure, and algorithms. ACM Computing Surveys (CSUR), 52(5):1–37, 2019.

    Article  Google Scholar 

  16. Mostafa Ghobaei-Arani, Alireza Souri, and Ali A Rahmanian. Resource management approaches in fog computing: A comprehensive review. Journal of Grid Computing, pages 1–42, 2019.

    Google Scholar 

  17. Ju Ren, Hui Guo, Chugui Xu, and Yaoxue Zhang. Serving at the edge: A scalable iot architecture based on transparent computing. IEEE Network, 31(5):96–105, 2017.

    Article  Google Scholar 

  18. Haijun Zhang, Na Liu, Xiaoli Chu, Keping Long, Abdol-Hamid Aghvami, and Victor CM Leung. Network slicing based 5g and future mobile networks: mobility, resource management, and challenges. IEEE communications magazine, 55(8):138–145, 2017.

    Google Scholar 

  19. Argyrios G Tasiopoulos, Onur Ascigil, Ioannis Psaras, and George Pavlou. Edge-map: Auction markets for edge resource provisioning. In 2018 IEEE 19th International Symposium on” A World of Wireless, Mobile and Multimedia Networks”(WoWMoM), pages 14–22. IEEE, 2018.

    Google Scholar 

  20. Mengting Liu, F Richard Yu, Yinglei Teng, Victor CM Leung, and Mei Song. Distributed resource allocation in blockchain-based video streaming systems with mobile edge computing. IEEE Transactions on Wireless Communications, 18(1):695–708, 2018.

    Google Scholar 

  21. Yangzhe Liao, Liqing Shou, Quan Yu, Qingsong Ai, and Quan Liu. Joint offloading decision and resource allocation for mobile edge computing enabled networks. Computer Communications, 2020.

    Google Scholar 

  22. Muhammad Waqas, Yong Niu, Manzoor Ahmed, Yong Li, Depeng Jin, and Zhu Han. Mobility-aware fog computing in dynamic environments: Understandings and implementation. IEEE Access, 7:38867–38879, 2018.

    Article  Google Scholar 

  23. Shreya Ghosh, Jaydeep Das, and Soumya K Ghosh. Locator: A cloud-fog-enabled framework for facilitating efficient location based services. In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), pages 87–92. IEEE, 2020.

    Google Scholar 

  24. S Babu and Sanjay Kumar Biswash. Fog computing–based node-to-node communication and mobility management technique for 5g networks. Transactions on Emerging Telecommunications Technologies, 30(10):e3738, 2019.

    Google Scholar 

  25. Jindou Xie, Yunjian Jia, Zhengchuan Chen, and Liang Liang. Mobility-aware task parallel offloading for vehicle fog computing. In International Conference on Artificial Intelligence for Communications and Networks, pages 367–379. Springer, 2019.

    Google Scholar 

  26. Shashank Shekhar, Ajay Chhokra, Hongyang Sun, Aniruddha Gokhale, Abhishek Dubey, Xenofon Koutsoukos, and Gabor Karsai. Urmila: Dynamically trading-off fog and edge resources for performance and mobility-aware iot services. Journal of Systems Architecture, page 101710, 2020.

    Google Scholar 

  27. Dongyu Wang, Zhaolin Liu, Xiaoxiang Wang, and Yanwen Lan. Mobility-aware task offloading and migration schemes in fog computing networks. IEEE Access, 7:43356–43368, 2019.

    Article  Google Scholar 

  28. John Paul Martin, A Kandasamy, and K Chandrasekaran. Mobility aware autonomic approach for the migration of application modules in fog computing environment. Journal of Ambient Intelligence and Humanized Computing, pages 1–20, 2020.

    Google Scholar 

  29. Anwesha Mukherjee, Deepsubhra Guha Roy, and Debashis De. Mobility-aware task delegation model in mobile cloud computing. The Journal of Supercomputing, 75(1):314–339, 2019.

    Google Scholar 

  30. Shreya Ghosh, Anwesha Mukherjee, Soumya K Ghosh, and Rajkumar Buyya. Mobi-iost: mobility-aware cloud-fog-edge-iot collaborative framework for time-critical applications. IEEE Transactions on Network Science and Engineering, 2019.

    Google Scholar 

  31. José Santos, Tim Wauters, Bruno Volckaert, and Filip De Turck. Resource provisioning in fog computing: From theory to practice. Sensors, 19(10):2238, 2019.

    Google Scholar 

  32. Luiz F Bittencourt, Javier Diaz-Montes, Rajkumar Buyya, Omer F Rana, and Manish Parashar. Mobility-aware application scheduling in fog computing. IEEE Cloud Computing, 4(2):26–35, 2017.

    Google Scholar 

  33. Tarik Taleb, Konstantinos Samdanis, Badr Mada, Hannu Flinck, Sunny Dutta, and Dario Sabella. On multi-access edge computing: A survey of the emerging 5g network edge cloud architecture and orchestration. IEEE Communications Surveys & Tutorials, 19(3):1657–1681, 2017.

    Article  Google Scholar 

  34. Jianbing Ni, Kuan Zhang, Xiaodong Lin, and Xuemin Sherman Shen. Securing fog computing for internet of things applications: Challenges and solutions. IEEE Communications Surveys & Tutorials, 20(1):601–628, 2017.

    Google Scholar 

  35. Rodrigo Roman, Javier Lopez, and Masahiro Mambo. Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems, 78:680–698, 2018.

    Google Scholar 

  36. Sathish Kumar Mani and Iyapparaja Meenakshisundaram. Improving quality-of-service in fog computing through efficient resource allocation. Computational Intelligence, 2020.

    Google Scholar 

  37. Yalan Wu, Jigang Wu, Long Chen, Gangqiang Zhou, and Jiaquan Yan. Fog computing model and efficient algorithms for directional vehicle mobility in vehicular network. IEEE Transactions on Intelligent Transportation Systems, 2020.

    Google Scholar 

  38. Min Chen, Wei Li, Giancarlo Fortino, Yixue Hao, Long Hu, and Iztok Humar. A dynamic service migration mechanism in edge cognitive computing. ACM Transactions on Internet Technology (TOIT), 19(2):1–15, 2019.

    Article  Google Scholar 

  39. Yuanguo Bi, Guangjie Han, Chuan Lin, Qingxu Deng, Lei Guo, and Fuliang Li. Mobility support for fog computing: An sdn approach. IEEE Communications Magazine, 56(5):53–59, 2018.

    Article  Google Scholar 

  40. Fei Zhang, Guangming Liu, Bo Zhao, Xiaoming Fu, and Ramin Yahyapour. Reducing the network overhead of user mobility–induced virtual machine migration in mobile edge computing. Software: Practice and Experience, 49(4):673–693, 2019.

    Google Scholar 

  41. Juyong Lee, Daeyoub Kim, and Jihoon Lee. Zone-based multi-access edge computing scheme for user device mobility management. Applied Sciences, 9(11):2308, 2019.

    Google Scholar 

  42. Zeineb Rejiba, Xavier Masip-Bruin, and Eva Marin-Tordera. A user-centric mobility management scheme for high-density fog computing deployments. In 2019 28th International Conference on Computer Communication and Networks (ICCCN), pages 1–8. IEEE, 2019.

    Google Scholar 

  43. Qinglan Peng, Yunni Xia, Zeng Feng, Jia Lee, Chunrong Wu, Xin Luo, Wanbo Zheng, Hui Liu, Yidan Qin, and Peng Chen. Mobility-aware and migration-enabled online edge user allocation in mobile edge computing. In 2019 IEEE International Conference on Web Services (ICWS), pages 91–98. IEEE, 2019.

    Google Scholar 

  44. Hongyue Wu, Shuiguang Deng, Wei Li, Jianwei Yin, Xiaohong Li, Zhiyong Feng, and Albert Y Zomaya. Mobility-aware service selection in mobile edge computing systems. In 2019 IEEE International Conference on Web Services (ICWS), pages 201–208. IEEE, 2019.

    Google Scholar 

  45. Miodrag Forcan and Mirjana Maksimović. Cloud-fog-based approach for smart grid monitoring. Simulation Modelling Practice and Theory, 101:101988, 2020.

    Article  Google Scholar 

  46. Jorge Pereira, Leandro Ricardo, Miguel Luís, Carlos Senna, and Susana Sargento. Assessing the reliability of fog computing for smart mobility applications in vanets. Future Generation Computer Systems, 94:317–332, 2019.

    Article  Google Scholar 

  47. Shiyuan Tong, Yun Liu, Mohamed Cheriet, Michel Kadoch, and Bo Shen. Ucaa: User-centric user association and resource allocation in fog computing networks. IEEE Access, 8:10671–10685, 2020.

    Article  Google Scholar 

  48. Tao Ouyang, Zhi Zhou, and Xu Chen. Follow me at the edge: Mobility-aware dynamic service placement for mobile edge computing. IEEE Journal on Selected Areas in Communications, 36(10):2333–2345, 2018.

    Article  Google Scholar 

  49. Xiaoge Huang, Ke Xu, Chenbin Lai, Qianbin Chen, and Jie Zhang. Energy-efficient offloading decision-making for mobile edge computing in vehicular networks. EURASIP Journal on Wireless Communications and Networking, 2020(1):35, 2020.

    Google Scholar 

  50. Chao Yang, Yi Liu, Xin Chen, Weifeng Zhong, and Shengli Xie. Efficient mobility-aware task offloading for vehicular edge computing networks. IEEE Access, 7:26652–26664, 2019.

    Article  Google Scholar 

  51. Anwesha Mukherjee, Debashis De, and Soumya K Ghosh. Fogioht: A weighted majority game theory based energy-efficient delay-sensitive fog network for internet of health things. Internet of Things, page 100181, 2020.

    Google Scholar 

  52. Mohammad Aazam, Khaled A Harras, and Sherali Zeadally. Fog computing for 5g tactile industrial internet of things: Qoe-aware resource allocation model. IEEE Transactions on Industrial Informatics, 15(5):3085–3092, 2019.

    Google Scholar 

  53. Lingyun Lu, Tian Wang, Wei Ni, Kai Li, and Bo Gao. Fog computing-assisted energy-efficient resource allocation for high-mobility mimo-ofdma networks. Wireless Communications and Mobile Computing, 2018, 2018.

    Google Scholar 

  54. Gaolei Li, Jun Wu, Jianhua Li, Kuan Wang, and Tianpeng Ye. Service popularity-based smart resources partitioning for fog computing-enabled industrial internet of things. IEEE Transactions on Industrial Informatics, 14(10):4702–4711, 2018.

    Article  Google Scholar 

  55. S Babu and Sanjay Kumar Biswash. Fog computing–based node-to-node communication and mobility management technique for 5g networks. Transactions on Emerging Telecommunications Technologies, 30(10):e3738, 2019.

    Google Scholar 

  56. Hongwen Hui, Chengcheng Zhou, Xingshuo An, and Fuhong Lin. A new resource allocation mechanism for security of mobile edge computing system. IEEE Access, 7:116886–116899, 2019.

    Article  Google Scholar 

  57. Bin Xiang, Jocelyne Elias, Fabio Martignon, and Elisabetta Di Nitto. Joint network slicing and mobile edge computing in 5g networks. In ICC 2019-2019 IEEE International Conference on Communications (ICC), pages 1–7. IEEE, 2019.

    Google Scholar 

  58. Soraia Oueida, Yehia Kotb, Moayad Aloqaily, Yaser Jararweh, and Thar Baker. An edge computing based smart healthcare framework for resource management. Sensors, 18(12):4307, 2018.

    Google Scholar 

  59. Mu Zhang, Song Wang, and Qing Gao. A joint optimization scheme of content caching and resource allocation for internet of vehicles in mobile edge computing. Journal of Cloud Computing, 9(1):1–12, 2020.

    Google Scholar 

  60. Xinyu Huang, Lijun He, and Wanyue Zhang. Vehicle speed aware computing task offloading and resource allocation based on multi-agent reinforcement learning in a vehicular edge computing network. arXiv preprint arXiv:2008.06641, 2020.

    Google Scholar 

  61. Kai Lin, Sameer Pankaj, and Di Wang. Task offloading and resource allocation for edge-of-things computing on smart healthcare systems. Computers & Electrical Engineering, 72:348–360, 2018.

    Article  Google Scholar 

  62. Quan Yuan, Haibo Zhou, Jinglin Li, Zhihan Liu, Fangchun Yang, and Xuemin Sherman Shen. Toward efficient content delivery for automated driving services: An edge computing solution. IEEE Network, 32(1):80–86, 2018.

    Google Scholar 

  63. Anwesha Mukherjee, Debashis De, and Soumya K Ghosh. Fogioht: A weighted majority game theory based energy-efficient delay-sensitive fog network for internet of health things. Internet of Things, page 100181, 2020.

    Google Scholar 

  64. Yaoxue Zhang, Ju Ren, Jiagang Liu, Chugui Xu, Hui Guo, and Yaping Liu. A survey on emerging computing paradigms for big data. Chinese Journal of Electronics, 26(1):1–12, 2017.

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Information and Communication Technology, College of Sciences and Engineering, University of Tasmania, Hobart, TAS, Australia

    Sudheer Kumar Battula, Ranesh Kumar Naha, Ujjwal KC, Khizar Hameed, Saurabh Garg & Muhammad Bilal Amin

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  1. Sudheer Kumar Battula
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  2. Ranesh Kumar Naha
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  3. Ujjwal KC
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  4. Khizar Hameed
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  5. Saurabh Garg
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  6. Muhammad Bilal Amin
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Correspondence to Sudheer Kumar Battula .

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Editors and Affiliations

  1. Department of Computer Science, Mahishadal Raj College, Mahishadal, West Bengal, India

    Anwesha Mukherjee

  2. Centre of Mobile Cloud Computing Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Debashis De

  3. Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, West Bengal, India

    Soumya K. Ghosh

  4. Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

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Battula, S.K., Naha, R.K., KC, U., Hameed, K., Garg, S., Amin, M.B. (2021). Mobility-Based Resource Allocation and Provisioning in Fog and Edge Computing Paradigms: Review, Challenges, and Future Directions. In: Mukherjee, A., De, D., Ghosh, S.K., Buyya, R. (eds) Mobile Edge Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-69893-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-69893-5_11

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