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OPTIMAL ENERGY DISTRIBUTION WITH ENERGY PACKET NETWORKS

Published online by Cambridge University Press:  29 January 2019

Yunxiao Zhang
Yunxiao Zhang*
Affiliation:
Department of Electrical and Electronic Engineering Imperial College London, SW7 2AZ, London E-mail: [email protected]
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Abstract

We use the Energy Packet Network (EPN) to investigate an optimal energy distribution problem for the computer-communication system which is powered by intermittent renewable energy sources. The objective is to find an optimal energy distribution to minimize the proposed cost function which computes penalty costs caused by the overall average response time of jobs and the energy loss. In this EPN system, we consider the energy can be lost through storage leakages, or due to empty workstations which will consume energy even no job needs to be processed. Related numerical examples with different sets of parameter values are presented in the paper to evaluate the system performance and to examine the obtained analytical solution. Then a special case is considered to study the optimal system performance when the total energy harvesting rate is sufficiently large.

Keywords

energy distributionenergy harvestingenergy packet networkG-networksoptimizationproduct-form solutionrenewable energy
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 35 , Special Issue 1: Learning, Optimization, and Theory of G-Networks , January 2021 , pp. 75 - 91
Copyright
Copyright © Cambridge University Press 2019

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References

1.Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M.Q., & Pentikousis, K. (2010). Energy-efficient cloud computing. The Computer Journal 53(7): 1045–1051.CrossRefGoogle Scholar
2.Bi, H. & Abdelrahman, O.H. (2018). Energy-aware navigation in large-scale evacuation using g-networks. Probability in the Engineering and Informational Sciences 32(3): 340–352.CrossRefGoogle Scholar
3.Bocharov, P., D'Apice, C., Gavrilov, E., & Pechinkin, A. (2004). Product form solution for g-networks with dependent service. RAIRO - Operations Research 38(2): 105–119.CrossRefGoogle Scholar
4.Caglayan, M.U. (2017). G-networks and their applications to machine learning, energy packet networks and routing: Introduction to the special issue. Probability in the Engineering and Informational Sciences 31(4): 381–395.CrossRefGoogle Scholar
5.Dimitriou, I., Alouf, S., & Jean-Marie, A. (2015). A markovian queueing system for modeling a smart green base station. European Workshop on Performance Engineering. Springer, 3–18.CrossRefGoogle Scholar
6.Fourneau, J.-M. (2016). G-networks of unreliable nodes. Probability in the Engineering and Informational Sciences 30(3): 361–378.CrossRefGoogle Scholar
7.Fourneau, J.-M. (2018). Mean value analysis of closed g-networks with signals. Computer Performance Engineering - 15th European Workshop, EPEW, 2018, Paris, France, October 29-30, 2018, Proceedings, 46–61. [Online]. Available: https://doi.org/10.1007/978-3-030-02227-3_4.CrossRefGoogle Scholar
8.Fourneau, J.-M. & Gelenbe, E. (2017). G-networks with adders. Future Internet 9(3): 34–ff.CrossRefGoogle Scholar
9.Fourneau, J.-M. & Wolter, K. (2016). Some applications of multiple classes g-networks with restart. Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Kraków, Poland, October 27-28, 2016, Proceedings, 126–133. [Online]. Available: https://doi.org/10.1007/978-3-319-47217-1_14.CrossRefGoogle Scholar
10.Fourneau, J.-M., Wolter, K., Reinecke, P., Krauß, T., & Danilkina, A. (2013). Multiple class g-networks with restart. ACM/SPEC International Conference on Performance Engineering, ICPE'13, Prague, Czech Republic - April 21–24, 2013, 39–50. [Online]. Available: http://doi.acm.org/10.1145/2479871.2479880.Google Scholar
11.Fourneau, J., Marin, A., & Balsamo, S. (2016). Modeling energy packets networks in the presence of failures. In 24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016, London, United Kingdom, September 19–21, 2016, 144–153.CrossRefGoogle Scholar
12.Gelenbe, E. (1990). Réseaux neuronaux aléatoires stables. Comptes rendus de l'Académie des sciences. Série 2, Mécanique, Physique, Chimie, Sciences de l'univers, Sciences de la Terre 310(3): 177–180.Google Scholar
13.Gelenbe, E. (1993). G-networks by triggered customer movement. Journal of applied probability 30(3): 742–748.CrossRefGoogle Scholar
14.Gelenbe, E. (1993). G-networks with signals and batch removal. Probability in the Engineering and Informational Sciences 7(3): 335–342.CrossRefGoogle Scholar
15.Gelenbe, E. (1994). G-networks: a unifying model for neural and queueing networks. Annals of Operations Research 48(5): 433–461.CrossRefGoogle Scholar
16.Gelenbe, E. (2007). Dealing with software viruses: a biological paradigm. Information Security Technical Report 12(4): 242–250.CrossRefGoogle Scholar
17.Gelenbe, E. (2007). Steady-state solution of probabilistic gene regulatory networks. Physical Review E, 76(3), 031903.CrossRefGoogle ScholarPubMed
18.Gelenbe, E. (2007). A diffusion model for packet travel time in a random multi-hop medium. ACM Transactions on Sensor Networks 3(2): 111–128.CrossRefGoogle Scholar
19.Gelenbe, E. (2011). Energy packet networks: Ict based energy allocation and storage. In GreeNets. Springer, 186–195.Google Scholar
20.Gelenbe, E. (2012). Energy packet networks: Adaptive energy management for the cloud. Proceedings of the 2Nd International Workshop on Cloud Computing Platforms. NY, USA: ACM, 1:1–1:5.Google Scholar
21.Gelenbe, E. (2014). Adaptive management of energy packets. IEEE 38th Annual Computer Software and Applications Conference, COMPSAC Workshops 2014, Vasteras, Sweden, July 21–25, 2014, 1–6.CrossRefGoogle Scholar
22.Gelenbe, E. & Abdelrahman, O.H. (2018). An energy packet network model for mobile networks with energy harvesting. Nonlinear Theory and Its Applications, IEICE 9(3): 1–15.CrossRefGoogle Scholar
23.Gelenbe, E. & Caseau, Y. (2015). The impact of information technology on energy consumption and carbon emissions. Ubiquity, 2015: 1.CrossRefGoogle Scholar
24.Gelenbe, E. & Ceran, E.T. (2015). Central or distributed energy storage for processors with energy harvesting. Sustainable Internet and ICT for Sustainability, 2015. IEEE, 1–3.CrossRefGoogle Scholar
25.Gelenbe, E. & Ceran, E.T. (2016). Energy packet networks with energy harvesting. IEEE Access 4, 1321–1331.CrossRefGoogle Scholar
26.Gelenbe, E. & Fourneau, J.-M. (2002). G-networks with resets. Performance Evaluation 49(1): 179–191.CrossRefGoogle Scholar
27.Gelenbe, E. & Labed, A. (1998). G-networks with multiple classes of signals and positive customers. European Journal of Operational Research 108, 293–305.CrossRefGoogle Scholar
28.Gelenbe, E. & Lent, R. (2003). A power-aware routing algorithm. SIMULATION SERIES 35(4): 502–507.Google Scholar
29.Gelenbe, E. & Lent, R. (2004). Power-aware ad hoc cognitive packet networks. Ad Hoc Networks 2(3): 205–216.CrossRefGoogle Scholar
30.Gelenbe, E. & Lent, R. (2013). Energy-qos trade-offs in mobile service selection. Future Internet 5(2): 128–139.CrossRefGoogle Scholar
31.Gelenbe, E. & Mahmoodi, T. (2011). Energy-aware routing in the cognitive packet network. ENERGY 2011, The First International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies, 7–12.Google Scholar
32.Gelenbe, E. & Marin, A. (2015). Interconnected wireless sensors with energy harvesting. Analytical and Stochastic Modelling Techniques and Applications - 22nd International Conference, ASMTA 2015, Albena, Bulgaria. Proceedings, 87–99.CrossRefGoogle Scholar
33.Gelenbe, E. & Morfopoulou, C. (2010). A framework for energy-aware routing in packet networks. The Computer Journal 54(6): 850–859.CrossRefGoogle Scholar
34.Gelenbe, E. & Morfopoulou, C. (2011). A framework for energy-aware routing in packet networks. The Computer Journal 54(6): 850–859.CrossRefGoogle Scholar
35.Gelenbe, E. & Schassberger, R. (1992). Stability of product form g-networks. Probability in the Engineering and Informational Sciences, 6(3): 271–276.CrossRefGoogle Scholar
36.Gómez-Corral, A. (2002). On a tandem g-network with blocking. Advances in Applied Probability 34(3): 626–661.CrossRefGoogle Scholar
37.Gorbil, G. & Gelenbe, E. (2011). Opportunistic communications for emergency support systems. Procedia Computer Science 5, 39–47.CrossRefGoogle Scholar
38.Guruacharya, S. & Hossain, E. (2018). Self-sustainability of energy harvesting systems: concept, analysis, and design. IEEE Transactions on Green Communications and Networking 2(1): 175–192.CrossRefGoogle Scholar
39.Harrison, P.G. (2003). G-networks with propagating resets via RCAT. SIGMETRICS Performance Evaluation Review 31(2): 3–5. [Online]. Available: http://doi.acm.org/10.1145/959143.959144CrossRefGoogle Scholar
40.Harrison, P.G. & Pitel, E. (1995). Response time distributions in tandem g-networks. Journal of Applied Probability 32(1): 224–246.CrossRefGoogle Scholar
41.Kadioglu, Y.M. (2017). Finite capacity energy packet networks. Probability in the Engineering and Informational Sciences 31(4): 477–504.CrossRefGoogle Scholar
42.Kadioglu, Y.M., & Gelenbe, E. (2018). Product-form solution for cascade networks with intermittent energy. IEEE Systems Journal, 1–10. doi: 10.1109/JSYST.2018.2854838.Google Scholar
43.Leite, S.C. & Fragoso, M.D. (2008). Diffusion approximation of state-dependent g-networks under heavy traffic. Journal of Applied Probability 45(2): 347–362.CrossRefGoogle Scholar
44.Liu, Q., Mak, T., Luo, J., Luk, W., & Yakovlev, A. (2011). Power adaptive computing system design in energy harvesting environment. Embedded Computer Systems, 2011, International Conference on, IEEE 33–40.CrossRefGoogle Scholar
45.Marin, A. (2016). Product-form in g-networks. Probability in the Engineering and Informational Sciences 30(3): 345–360.CrossRefGoogle Scholar
46.Matalytski, M. (2018). Finding expected revenues in g-network with multiple classes of positive and negative customers. Probability in the Engineering and Informational Sciences, 1–16.Google Scholar
47.Matalytski, M. & Kopats, D. (2017). Finding expected revenues in g-network with signals and customers batch removal. Probability in the Engineering and Informational Sciences 31(4): 561–575.CrossRefGoogle Scholar
48.Mohd, A., Ortjohann, E., Schmelter, A., Hamsic, N., & Morton, D. (2008). Challenges in integrating distributed energy storage systems into future smart grid. 2008 IEEE International Symposium on Industrial Electronics, 1627–1632.CrossRefGoogle Scholar
49.Ozel, O., Tutuncuoglu, K., Yang, J., Ulukus, S., & Yener, A. (2011). Transmission with energy harvesting nodes in fading wireless channels: optimal policies. IEEE Journal on Selected Areas in Communications 29(8): 1732–1743.CrossRefGoogle Scholar
50.Takahashi, R. & Hikihara, T. (2013). Design and experimental verification of power packet generation system for power packet dispatching system. American Control Conference, 2013. IEEE, 4368–4373.CrossRefGoogle Scholar
51.Takahashi, R., Takuno, T., & Hikihara, T. (2012). Estimation of power packet transfer properties on indoor power line channel. Energies 5(7): 2141–2149.CrossRefGoogle Scholar
52.Takahashi, R., Tashiro, K., & Hikihara, T. (2015). Router for power packet distribution network: design and experimental verification. IEEE Transactions on Smart Grid 6(2): 618–626.CrossRefGoogle Scholar
53.Ulukus, S., Yener, A., Erkip, E., Simeone, O., Zorzi, M., Grover, P., & Huang, K. (2015). Energy harvesting wireless communications: a review of recent advances. IEEE Journal on Selected Areas in Communications 33(3): 360–381.CrossRefGoogle Scholar
54.Vazquez, S., Lukic, S.M., Galvan, E., Franquelo, L.G., & Carrasco, J.M. (2010). Energy storage systems for transport and grid applications. IEEE Transactions on Industrial Electronics 57(12): 3881–3895.CrossRefGoogle Scholar
55.Wang, L. & Gelenbe, E. (2018). Adaptive dispatching of tasks in the cloud. IEEE Transactions on Cloud Computing 6(1): 33–45.CrossRefGoogle Scholar
56.Yang, J. & Ulukus, S. (2012). Optimal packet scheduling in an energy harvesting communication system. IEEE Transactions on Communications 60(1): 220–230.CrossRefGoogle Scholar
57.Yin, Y. (2017). Optiaml energy for energy packet networks. Probability in the Engineering and Informational Sciences 31(4): 516–539.CrossRefGoogle Scholar