Houssemeddine Mazouzi
Abstract
Mobile Edge Computing is a promising paradigm that can provide cloud computing capabilities at the edge of the network to support low latency mobile services. The fundamental concept relies on bringing cloud computation closer to users by deploying cloudlets or edge servers, which are small clusters of servers that are mainly located on existing wireless Access Points (APs), set-top boxes, or Base Stations (BSs). In this article, we focus on computation offloading over a heterogeneous cloudlet environment. We consider several users with different energy—and latency-constrained tasks that can be offloaded over cloudlets with differentiated system and network resources capacities. We investigate offloading policies that decide which tasks should be offloaded and select the assigned cloudlet, accordingly with network and system resources. The objective is to minimize an offloading cost function, which we defined as a combination of tasks’ execution time and mobiles’ energy consumption. We formulate this problem as a Mixed-Binary Programming. Since the centralized optimal solution is NP-hard, we propose a distributed linear relaxation-based heuristic approach that relies on the Lagrangian decomposition method. To solve the subproblems, we also propose a greedy heuristic algorithm that computes the best cloudlet selection and bandwidth allocation following tasks’ offloading costs. Numerical results show that our offloading policy achieves a good solution quickly. We also discuss the performances of our approach for large-scale scenarios and compare it to state-of-the-art approaches from the literature.
- Giuseppe Bianchi. 2000. Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J. Select. Areas Comm. 18, 3 (2000), 535--547. Google Scholar
Digital Library
- Arash Bozorgchenani, Daniele Tarchi, and Giovanni Emanuele Corazza. 2017. An energy and delay-efficient partial offloading technique for fog computing architectures. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’17). IEEE, 1--6.Google ScholarCross Ref
- Aaron Carroll, Gernot Heiser. 2010. An analysis of power consumption in a smartphone. In Proceedings of the USENIX Annual Technical Conference (USENIXATC’10), Vol. 14. Boston, MA, 21--21. Google ScholarDigital Library
- Meng-Hsi Chen, Ben Liang, and Min Dong. 2016. Joint offloading decision and resource allocation for multi-user multi-task mobile cloud. In Proceedings of the IEEE International Conference on Communications (ICC’16). IEEE, 1--6.Google ScholarCross Ref
- Xu Chen, Lei Jiao, Wenzhong Li, and Xiaoming Fu. 2016. Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Netw. 24, 5 (2016), 2795--2808. Google ScholarDigital Library
- Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, and Ashwin Patti. 2011. Clonecloud: Elastic execution between mobile device and cloud. In Proceedings of the 6th European Conference on Computer Systems (EuroSys’11). ACM, 301--314. Google ScholarDigital Library
- Eduardo Cuervo, Aruna Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. 2010. MAUI: Making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys’10). ACM, 49--62. Google ScholarDigital Library
- Debessay Fesehaye, Yunlong Gao, Klara Nahrstedt, and Guijun Wang. 2012. Impact of cloudlets on interactive mobile cloud applications. In Proceedings of the 16th IEEE International Enterprise Distributed Object Computing Conference (EDOC’12). IEEE, 123--132. Google ScholarDigital Library
- Marshall L. Fisher. 2004. The Lagrangian relaxation method for solving integer programming problems. Manag. Sci. 50, 12-supplement (2004), 1861--1871. Google ScholarDigital Library
- Keke Gai, Meikang Qiu, and Hui Zhao. 2018. Energy-aware task assignment for mobile cyber-enabled applications in heterogeneous cloud computing. J. Parallel and Distrib. Comput. 111 (2018), 126--135. Google ScholarDigital Library
- Ying Gao, Wenlu Hu, Kiryong Ha, Brandon Amos, Padmanabhan Pillai, and Mahadev Satyanarayanan. 2015. Are cloudlets necessary? Technical Report CMU-CS-15-139. School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
- Songtao Guo, Bin Xiao, Yuanyuan Yang, and Yang Yang. 2016. Energy-efficient dynamic offloading and resource scheduling in mobile cloud computing. In Proceedings of the 35th IEEE International Conference on Computer Communications (INFOCOM’16), Vol. 2016-July. IEEE, 1--9.Google ScholarCross Ref
- Dong Huang, Ping Wang, and Dusit Niyato. 2012. A dynamic offloading algorithm for mobile computing. IEEE Trans. Wireless Comm. 11, 6 (2012). IEEE, 1991--1995.Google Scholar
- Mike Jia, Jiannong Cao, and Weifa Liang. 2015. Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Trans. Cloud Comput. 99 (2015).Google Scholar
- Mike Jia, Weifa Liang, Zichuan Xu, and Meitian Huang. 2016. Cloudlet load balancing in wireless metropolitan area networks. In Proceedings of the 35th IEEE International Conference on Computer Communications (INFOCOM’16), Vol. 2016-July. IEEE, 1--9.Google ScholarCross Ref
- Doyub Kim, Woojong Koh, Rahul Narain, Kayvon Fatahalian, Adrien Treuille, and James F. O’Brien. 2013. Near-exhaustive precomputation of secondary cloth effects. ACM Trans. Graph. 32, 4 (July 2013), 87:1--87:8. Google ScholarDigital Library
- Sven O. Krumke and Clemens Thielen. 2013. The generalized assignment problem with minimum quantities. Euro. J. Op. Res. 228, 1 (2013), 46--55.Google ScholarCross Ref
- Grace Lewis, Sebastián Echeverría, Soumya Simanta, Ben Bradshaw, and James Root. 2014. Tactical cloudlets: Moving cloud computing to the edge. In Proceedings of the IEEE Military Communications Conference. IEEE, 1440--1446. Google ScholarDigital Library
- Grace Alexandra Lewis. 2016. Software Architecture Strategies for Cyber-foraging Systems. Ph.D Dissertation, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
- Jia-Liang Lu and Fabrice Valois. 2006. Performance evaluation of 802.11 WLAN in a real indoor environment. In Proceedings of the IEEE International Conference on Wireless and Mobile Computing, Networking, and Communications (WiMob’06). IEEE, 140--147. Google ScholarDigital Library
- Longjie Ma, Jigang Wu, and Long Chen. 2017. DOTA: Delay bounded optimal cloudlet deployment and user association in WMANs. In Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing. IEEE Press, 196--203. Google ScholarDigital Library
- Yuyi Mao, Jun Zhang, S. H. Song, and Khaled Ben Letaief. 2016. Power-delay tradeoff in multi-user mobile-edge computing systems. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’16). IEEE, 1--6.Google ScholarCross Ref
- Antti P. Miettinen and Jukka K. Nurminen. 2010. Energy efficiency of mobile clients in cloud computing. HotCloud 10 (2010), 4--4. Google ScholarDigital Library
- Anwesha Mukherjee, Debashis De, and Deepsubhra Guha Roy. 2016. A power and latency aware cloudlet selection strategy for multi-cloudlet environment. IEEE Trans. Cloud Comput. 99 (2016), 1--14.Google ScholarCross Ref
- Yucen Nan, Wei Li, Wei Bao, Flavia C. Delicato, Paulo F. Pires, Yong Dou, and Albert Y. Zomaya. 2017. Adaptive energy-aware computation offloading for cloud of things systems. IEEE Access 5 (2017), 23,947--23,957.Google Scholar
- Yucen Nan, Wei Li, Wei Bao, Flavia C. Delicato, Paulo F. Pires, and Albert Y. Zomaya. 2018. A dynamic tradeoff data processing framework for delay-sensitive applications in cloud of things systems. J. Parallel and Distrib. Comput. 112 (2018), 53--66.Google ScholarCross Ref
- Deepsubhra Guha Roy, Debashis De, Anwesha Mukherjee, and Rajkumar Buyya. 2016. Application-aware cloudlet selection for computation offloading in multi-cloudlet environment. J. Supercomput. (2016), 1--19.Google Scholar
- Mark Ryan. 2005. Calculus Workbook for Dummies. Wiley Publishing, Inc.Google Scholar
- Swetank Kumar Saha, Pratham Malik, Selvaganesh Dharmeswaran, and Dimitrios Koutsonikolas. 2016. Revisiting 802.11 power consumption modeling in smartphones. In Proceedings of the 17th IEEE International Symposium on World of Wireless, Mobile, and Multimedia Networks (WoWMoM’16). IEEE, 1--10.Google ScholarCross Ref
- Mahadev Satyanarayanan, Grace Lewis, Edwin Morris, Soumya Simanta, Jeff Boleng, and Kiryong Ha. 2013. The role of cloudlets in hostile environments. IEEE Pervas. Comput. 12, 4 (2013), 40--49. Google ScholarDigital Library
- Jiafu Tang, Chongjun Yan, Xiaoqing Wang, and Chengkuan Zeng. 2014. Using Lagrangian relaxation decomposition with heuristic to integrate the decisions of cell formation and parts scheduling considering intercell moves. IEEE Trans. Automat. Sci. Eng. 11, 4 (2014), 1,110--1,121.Google ScholarCross Ref
- Song Wu, Chao Niu, Jia Rao, Hai Jin, and Xiaohai Dai. 2017. Container-based cloud platform for mobile computation offloading. In Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS’17). IEEE, 123--132.Google ScholarCross Ref
- Zichuan Xu, Weifa Liang, Wenzheng Xu, Mike Jia, and Song Guo. 2016. Efficient algorithms for capacitated cloudlet placements. IEEE Trans. Parallel Distrib. Systems 27, 10 (2016), 2,866--2,880. Google ScholarDigital Library
- Hong Yao, Changmin Bai, Muzhou Xiong, Deze Zeng, and Zhangjie Fu. 2017. Heterogeneous cloudlet deployment and user-cloudlet association toward cost-effective fog computing. Concurr. Comput.: Practice and Exper. 29, 16 (2017).Google Scholar
- Chongyu Zhou, Chen-Khong Tham, and Mehul Motani. 2017. Online auction for truthful stochastic offloading in mobile cloud computing. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’17). IEEE, 1--6.Google ScholarCross Ref
- Qiliang Zhu, Baojiang Si, Feifan Yang, and You Ma. 2017. Task offloading decision in fog computing system. China Comm. 14, 11 (2017), 59--68.Google ScholarCross Ref
Index Terms
- DM2-ECOP: An Efficient Computation Offloading Policy for Multi-user Multi-cloudlet Mobile Edge Computing Environment
Recommendations
A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms: Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet
Sending data to the cloud for analysis was a prominent trend during the past decades, driving cloud computing as a dominant computing paradigm. However, the dramatically increasing number of devices and data traffic in the Internet-of-Things (IoT) era ...
Maximizing Mobiles Energy Saving Through Tasks Optimal Offloading Placement in two-tier Cloud
MSWIM '18: Proceedings of the 21st ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile SystemsIn this paper, we focus on tasks offloading over two tiered mobile cloud computing environment. We consider several users with energy constrained tasks that can be offloaded over cloudlets or on a remote cloud with differentiated system and network ...
Maximizing mobiles energy saving through tasks optimal offloading placement in two-tier cloud: A theoretical and an experimental study
AbstractIn this paper, we focus on tasks offloading over two tiered mobile edge computing environment. We consider several users with energy constrained tasks that can be offloaded over edge clouds (cloudlets) or on a remote cloud with ...
Comments