Abstract
In the era of Internet-of-Things (IoT), both the number of web services and the number of users invoking them are increasing everyday. These web services utilize a cloud server for access to sufficient compute resources for service delivery. A disadvantage of cloud computing is that it is known to have a high latency because of its large distance (both physical distance as well as number of hops) from the end user device. A key technique of enabling low-latency web services, called edge computing, brings the compute resources closer to the end device. Edge computing enables better resource utilization and it reduces latency. However, since there are numerous compute resources or ‘edge resources’, determining where the services should be placed becomes a new challenge. In this paper, we consider the case of public transport vehicles utilizing edge computing to reduce latency while providing such web services. We first model the dynamic service placement problem considering user mobility. We then propose two algorithms to solve this problem. The first algorithm utilizes an Integer Linear Programming (ILP) to obtain an optimal solution, albeit at the cost of scalability. We then propose a heuristic algorithm to achieve a low latency, while also scaling to large problem instances. We validate the performance of both the techniques through extensive trace-driven simulations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bahreini, T., Grosu, D.: Efficient placement of multi-component applications in edge computing systems. In: ACM/IEEE Symposium on Edge Computing, p. 5. ACM (2017)
Bhattcharya, A., De, P.: Computation offloading from mobile devices: can edge devices perform better than the cloud? In: ARMS-CC Workshop, pp. 1–6 (2016)
Deng, S., Huang, L., Taheri, J., Yin, J., Zhou, M., Zomaya, A.Y.: Mobility-aware service composition in mobile communities. IEEE TSMC Syst. 47(3), 555–568 (2017)
Farhadi, V., et al.: Service placement and request scheduling for data-intensive applications in edge clouds. In: IEEE INFOCOM, pp. 1279–1287 (2019)
Gurobi Optimization, L.: Gurobi optimizer reference manual (2019). http://www.gurobi.com
He, T., et al.: It’s hard to share: joint service placement and request scheduling in edge clouds with sharable and non-sharable resources. In: IEEE ICDCS, pp. 365–375 (2018)
Lin, L., et al.: Computation offloading toward edge computing. Proc. IEEE 107(8), 1584–1607 (2019)
MacQueen, J., et al.: Some methods for classification and analysis of multivariate observations. In: Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297 (1967)
Ouyang, T., Zhou, Z., Chen, X.: Follow me at the edge: mobility-aware dynamic service placement for mobile edge computing. IEEE J. Sel. Areas Commun. 36(10), 2333–2345 (2018). https://doi.org/10.1109/JSAC.2018.2869954
Ouyang, T., Li, R., Chen, X., Zhou, Z., Tang, X.: Adaptive user-managed service placement for mobile edge computing: an online learning approach. In: IEEE INFOCOM, pp. 1468–1476. IEEE (2019)
Pasteris, S., Wang, S., Herbster, M., He, T.: Service placement with provable guarantees in heterogeneous edge computing systems. In: IEEE INFOCOM, pp. 514–522 (2019)
Peng, Q., et al.: Mobility-aware and migration-enabled online edge user allocation in mobile edge computing. In: IEEE ICWS, pp. 91–98, July 2019
Rausch, T., Avasalcai, C., Dustdar, S.: Portable energy-aware cluster-based edge computers. In: 2018 IEEE/ACM Symposium on Edge Computing (SEC), pp. 260–272, October 2018
Rejiba, Z., Masip-Bruin, X., Marín-Tordera, E.: A survey on mobility-induced service migration in the fog, edge, and related computing paradigms. ACM Comput. Surv. 52(5), 90:1–90:33 (2019)
Selimi, M., et al.: Practical service placement approach for microservices architecture. In: IEEE/ACM CCGRID, pp. 401–410 (2017)
Skarlat, O., Nardelli, M., Schulte, S., Dustdar, S.: Towards QoS-aware fog service placement. In: IEEE ICFEC, pp. 89–96 (2017)
Tong, L., Li, Y., Gao, W.: A hierarchical edge cloud architecture for mobile computing. In: IEEE INFOCOM, pp. 1–9 (2016)
Tran, T.X., et al.: Collaborative mobile edge computing in 5g networks: new paradigms, scenarios, and challenges. IEEE Commun. Mag. 55(4), 54–61 (2017)
Urgaonkar, R., Wang, S., He, T., Zafer, M., Chan, K., Leung, K.K.: Dynamic service migration and workload scheduling in edge-clouds. Perform. Eval. 91, 205–228 (2015)
Van Brummelen, G.: Heavenly Mathematics: The Forgotten Art of Sphericaltrigonometry. Princeton University Press, Princeton (2012)
Wang, S., Guo, Y., Zhang, N., Yang, P., Zhou, A., Shen, X.S.: Delay-aware microservice coordination in mobile edge computing: A reinforcement learning approach. IEEE Trans. Mob. Comput. 1 (2019)
Wang, S., Urgaonkar, R., Zafer, M., He, T., Chan, K., Leung, K.K.: Dynamic service migration in mobile edge computing based on Markov decision process. IEEE/ACM Trans. Networking 27(3), 1272–1288 (2019)
Wang, S., Zafer, M., Leung, K.K.: Online placement of multi-component applications in edge computing environments. IEEE Access 5, 2514–2533 (2017)
Waqas, M., Niu, Y., Ahmed, M., Li, Y., Jin, D., Han, Z.: Mobility-aware fog computing in dynamic environments: understandings and implementation. IEEE Access 7, 38867–38879 (2018)
Zhao, H., Deng, S., Zhang, C., Du, W., He, Q., Yin, J.: A mobility-aware cross-edge computation offloading framework for partitionable applications. In: IEEE ICWS, pp. 193–200. IEEE (2019)
Acknowledgment
We would like to acknowledge Dr. Ansuman Banerjee, Indian Statistical Institute and Dr. Nanjangud C Narendra, Ericsson Research Bangalore for their initial discussions on this project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Mudam, R., Bhartia, S., Chattopadhyay, S., Bhattacharya, A. (2020). Mobility-Aware Service Placement for Vehicular Users in Edge-Cloud Environment. In: Kafeza, E., Benatallah, B., Martinelli, F., Hacid, H., Bouguettaya, A., Motahari, H. (eds) Service-Oriented Computing. ICSOC 2020. Lecture Notes in Computer Science(), vol 12571. Springer, Cham. https://doi.org/10.1007/978-3-030-65310-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-65310-1_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-65309-5
Online ISBN: 978-3-030-65310-1
eBook Packages: Computer ScienceComputer Science (R0)