Abstract
With the increasing number of connected devices, sensors, data generated need to be analyzed. The current cloud computing model, which concentrate on computing and storage resources in a few large data centers, will inevitably lead to excessive network load, end-to-end service latency, and overall power consumption. This leads to the creation of new network architectures that extend computing and storage capabilities to the edge of the network, close to end-users. The emerging problem is how to efficiently deploy the services to the system that satisfies service resource requirements and QoS constraints while maximizing resource utilization.
In this paper, we investigate the problem of IoT services deployment in Cloud Fog system to provide IoT services with minimal energy consumption. We formulate the problem using a Linear Programming (LP) model to maximize the operational time of Cloud-Fog system as well as the IoT services specific requirements [1]. We propose a new heuristic algorithm to simplify the problem. We compare the lifetime of the proposed algorithm with the optimal solution solved by Linear Programming. The experimental results show that our proposed solution is very close to optimum solutions in terms of energy efficiency.
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References
Dastjerdi, A.V., Gupta, H., Calheiros, R.N., Ghosh, S.K., Buyya, R.: Fog computing: principles, architectures, and applications. In: Internet of Things, pp. 61–75. Elsevier, Amsterdam (2016)
Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, pp. 13–16. ACM (2012)
Hajibaba, M., Gorgin, S.: A review on modern distributed computing paradigms: cloud computing, jungle computing and fog computing. J. Comput. Inf. Technol. 22(2), 69–84 (2014)
Chang, R., et al.: An energy efficient routing mechanism for wireless sensor networks. In: Proceedings of the 20th International Conference on Advanced Information Networking and Applications (AINA 2006) (2006)
Tung, N.T.: Energy-efficient routing algorithms in wireless sensor networks. Ph.D. thesis, Monash University, Australia (2009)
Tung, N.T., Thanh Binh, H.T.: Base station location -aware optimization model of the lifetime of wireless sensor networks. Mobile Netw. Appl. (MONET), May 2016. https://doi.org/10.1007/s11036-015-0614-3
Tung, N.T., Nguyen, V.D.: Optimizing the operating time of wireless sensor network. EURASIP J. Wirel. Commun. Netw. (2013). https://doi.org/10.1186/1687-1499-2012-348, ISSN: 1687-1499
LourthuHepziba, M.M., Balamurugan, K., Vijayaraj, M.: Maximization of lifetime and reducing power consumption in wireless sensor network using protocol. Int. J. Soft Comput. Eng. 2(6), 90–95 (2013)
Paschalidis, I.C., Wu, R.: Robust maximum lifetime routing and energy allocation in wireless sensor networks. Int. J. Distrib. Sens. Netw. 2012(523787), 14 (2012)
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Thanh Tung, N. (2021). Optimizing the Operational Time of IoT Devices in Cloud-Fog Systems. In: Vinh, P.C., Rakib, A. (eds) Context-Aware Systems and Applications, and Nature of Computation and Communication. ICCASA ICTCC 2020 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 343. Springer, Cham. https://doi.org/10.1007/978-3-030-67101-3_12
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DOI: https://doi.org/10.1007/978-3-030-67101-3_12
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