Sustainability Analysis for Fog Nodes With Renewable Energy Supplies

There is a growing interest in the use of renewable energy sources to power fog networks in order to mitigate the detrimental effects of conventional energy production. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a fog node powered by renewable energy sources is studied. We develop a generic analytical model to study the energy sustainability of fog nodes powered by renewable energy sources, by generalizing the leaky bucket model to shape and police traffic source for rate-based congestion control in high-speed fog networks. Based on the closed-form solutions of energy buffer analysis, i.e., the energy depletion probability and mean energy length, we study the energy sustainability in two special but real-happening scenarios. The experimental results show that with proper design the leaky bucket model effectively reflects the energy sustainability of data traffic in fog networks. Numerical results also reveal that the model performance is sensitive to certain traffic source characteristics in fog networks.

[1]  D. Mitra,et al.  Stochastic theory of a data-handling system with multiple sources , 1982, The Bell System Technical Journal.

[2]  Hao Liang,et al.  Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption , 2016, IEEE Internet of Things Journal.

[3]  W. Marsden I and J , 2012 .

[4]  Mischa Schwartz,et al.  Broadband integrated networks , 1996 .

[5]  Xin-Ping Guan,et al.  Energy-aware and QoS-aware load balancing for HetNets powered by renewable energy , 2016, Comput. Networks.

[6]  Giuseppe Piro,et al.  When Renewable Energy Meets LoRa: A Feasibility Analysis on Cable-Less Deployments , 2018, IEEE Internet of Things Journal.

[7]  Wanlei Zhou,et al.  FogRoute: DTN-Based Data Dissemination Model in Fog Computing , 2017, IEEE Internet of Things Journal.

[8]  Martin Reisslein,et al.  Ethernet PONs: a survey of dynamic bandwidth allocation (DBA) algorithms , 2004, IEEE Communications Magazine.

[9]  Nanying Yin,et al.  Analysis of the Leaky Bucket Algorithm for ON-OFF Data Sources , 1993, J. High Speed Networks.

[10]  John Frank Charles Kingman,et al.  The single server queue in heavy traffic , 1961, Mathematical Proceedings of the Cambridge Philosophical Society.

[11]  Xuemin Shen,et al.  Optimal Reliability in Energy Harvesting Industrial Wireless Sensor Networks , 2016, IEEE Transactions on Wireless Communications.

[12]  Jianhua Li,et al.  Latency estimation for fog-based internet of things , 2017, 2017 27th International Telecommunication Networks and Applications Conference (ITNAC).

[13]  Albert Y. Zomaya,et al.  Distribution Based Workload Modelling of Continuous Queries in Clouds , 2017, IEEE Transactions on Emerging Topics in Computing.

[14]  Luis Rodero-Merino,et al.  Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.

[15]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[16]  Mohammed Moness,et al.  A Survey of Cyber-Physical Advances and Challenges of Wind Energy Conversion Systems: Prospects for Internet of Energy , 2016, IEEE Internet of Things Journal.

[17]  Tao Jiang,et al.  Carbon-Aware Energy Cost Minimization for Distributed Internet Data Centers in Smart Microgrids , 2014, IEEE Internet of Things Journal.

[18]  George F. Reed,et al.  Use of Coefficient of Variation in Assessing Variability of Quantitative Assays , 2002, Clinical and Vaccine Immunology.

[19]  Wolfgang Fischer,et al.  The Markov-Modulated Poisson Process (MMPP) Cookbook , 1993, Perform. Evaluation.

[20]  H. Vincent Poor,et al.  Sustainability Analysis and Resource Management for Wireless Mesh Networks with Renewable Energy Supplies , 2014, IEEE Journal on Selected Areas in Communications.

[21]  Kamaruzzaman Sopian,et al.  A review of photovoltaic systems size optimization techniques , 2013 .

[22]  Tran Dinh Hieu,et al.  Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks , 2016, Sensors.

[23]  Ivan Stojmenovic,et al.  An overview of Fog computing and its security issues , 2016, Concurr. Comput. Pract. Exp..

[24]  Tao Zhang,et al.  Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.

[25]  Debasis Mitra,et al.  Stochastic fluid models in the analysis of access regulation in high speed networks , 1991, IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record.

[26]  Gerd Niestegge,et al.  The ‘leaky bucket’ policing method in the ATM (asynchronous transfer mode) network , 1990 .

[27]  D. Goodin The cambridge dictionary of statistics , 1999 .

[28]  Ken-ichi Sato,et al.  Performance Limitation of Leaky Bucket Algorithm for Usage Parameter Control and Bandwidth Allocation Methods , 1992 .

[29]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[30]  Moshe Sidi,et al.  On the performance of bursty and modulated sources subject to leaky bucket rate-based access control schemes , 1994, IEEE Trans. Commun..

[31]  Rajkumar Buyya,et al.  Fog Computing: A Taxonomy, Survey and Future Directions , 2016, Internet of Everything.

[32]  Albert Y. Zomaya,et al.  The Next Grand Challenges: Integrating the Internet of Things and Data Science , 2018, IEEE Cloud Computing.