David Schuster
Marc Hesenius
ABSTRACT
Multi-access Edge Computing moves computation resources closer to the user and is a core component of future mobile networks. To ensure performance, applications must migrate through the network for optimal component deployment. Simulations come in handy to demonstrate how applications can be distributed depending on user movement but also require modeling user behavior. This paper describes our ongoing work in this area.
- Arshdeep Bahga and Vijay Krishna Madisetti. 2011. Synthetic Workload Generation for Cloud Computing Applications. J. Softw. Eng. Appl. 4, 7 (2011), 396–410. https://doi.org/10.4236/jsea.2011.47046Google Scholar
Cross Ref
- Robert Gazda, Michel Roy, Jim Blakley, Aly Sakr, and Rolf Schuster. 2021. Towards Open and Cross Domain Edge Emulation – The AdvantEDGE Platform. In 2021 IEEE/ACM Symposium on Edge Computing (SEC). 339–344. https://doi.org/10.1145/3453142.3493518Google Scholar
- Wei-jen Hsu, Kashyap Merchant, Haw-wei Shu, Chih-hsin Hsu, and Ahmed Helmy. 2005. Weighted Waypoint Mobility Model and Its Impact on Ad Hoc Networks. SIGMOBILE Mob. Comput. Commun. Rev. 9, 1 (jan 2005), 59–63. https://doi.org/10.1145/1055959.1055968Google ScholarDigital Library
- ITU-T. 2015. IMT Vision - Framework and overall objectives of the future development of IMT for 2020 and beyond. Recommendation M.2083-0. International Telecommunication Union, Geneva.Google Scholar
- David B. Johnson and David A. Maltz. 1996. Dynamic Source Routing in Ad Hoc Wireless Networks. Springer US, Boston, MA, 153–181. https://doi.org/10.1007/978-0-585-29603-6_5Google Scholar
- Andrea Ribeiro and Sofia Rute C.2011. A Survey on Mobility Models for Wireless Networks. Technical Report SITI-TR-11-01.Google Scholar
- Cagatay Sonmez, Atay Ozgovde, and Cem Ersoy. 2017. EdgeCloudSim: An environment for performance evaluation of Edge Computing systems. In 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). 39–44. https://doi.org/10.1109/FMEC.2017.7946405Google ScholarCross Ref
- Wenxiao Zhang, Sikun Lin, Farshid Hassani Bijarbooneh, Hao-Fei Cheng, Tristan Braud, Pengyuan Zhou, Lik-Hang Lee, and Pan Hui. 2022. EdgeXAR: A 6-DoF Camera Multi-Target Interaction Framework for MAR with User-Friendly Latency Compensation. Proc. ACM Hum.-Comput. Interact. 6, EICS, Article 152 (2022), 24 pages. https://doi.org/10.1145/3532202Google ScholarDigital Library
Index Terms
- Towards Modeling User Behavior in Multi-access Edge Computing
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