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A Framework for Dynamic Power Management at Network Level

by Kamlesh Kumar Verma, Vipin Saxena
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 139 - Number 8
Year of Publication: 2016
Authors: Kamlesh Kumar Verma, Vipin Saxena
10.5120/ijca2016909244

Kamlesh Kumar Verma, Vipin Saxena . A Framework for Dynamic Power Management at Network Level. International Journal of Computer Applications. 139, 8 ( April 2016), 34-39. DOI=10.5120/ijca2016909244

@article{ 10.5120/ijca2016909244,
author = { Kamlesh Kumar Verma, Vipin Saxena },
title = { A Framework for Dynamic Power Management at Network Level },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 139 },
number = { 8 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume139/number8/24513-2016909244/ },
doi = { 10.5120/ijca2016909244 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:40:25.600641+05:30
%A Kamlesh Kumar Verma
%A Vipin Saxena
%T A Framework for Dynamic Power Management at Network Level
%J International Journal of Computer Applications
%@ 0975-8887
%V 139
%N 8
%P 34-39
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the current scenario of computing, distributing is gaining popularity as many of users are connected with their handheld device across the globe. The connected device generally emits the energy which is of different categories and it is major challenge to optimize the entire energy of the system. The present paper proposes a frame work for the dynamic power management for completion of tasks in minimum time frame which are routed from one node to another node across the network. For this purpose, a step topological network is selected at the application level of the model. Computed results are depicted for the dynamic power management in the forms of graphs.

References
  1. Hwang, C-H. and Wu, A. “A Predictive System Shutdown Method for Energy Saving of Event Driven Computation”. Proceedings International Conference on Computer Aided Design, San Jose, California, pp. 28–32, IEEE Xplore Digital Library 1997.
  2. Benini, L., Paleologo, G., Bogliolo, A., De Micheli G., “Policy Optimization for Dynamic Power Management”. IEEE Trans Comput Aided Des pp. 813–833, 1999.
  3. Qiu Q, Wu., and Q, Pedram M.,“Stochastic Modelling of a Power-Managed System Construction and Optimization”. IEEE Trans Comput Aided Des pp 1200–1217, 2001.
  4. Simunic, T., Benini, L., Glynn, P., De, Micheli G.“Event-Driven Power Management”. IEEE Trans Comput Aided Des, pp 840–857, 2001.
  5. Bhat, UN. “Elements of Applied Stochastic Processes”. Wiley–Inter Science, 2002.
  6. Irani, S., Shukla, S., Gupta, R.,” Competitive Analysis of Dynamic Power Management Strategies for Systems with Multiple Powers Saving States”. Proceedings Design and Test in Europe, pp. 117–123, 2002.
  7. Sorber, J., Banerjee, N., Corner, M., Rollins S, Turducken.,“Hierarchical Power Management for Mobile Devices”. Proc Mobi Systems, Jun Seattle (WA). pp. 261–274, 2002.
  8. Ren, Z., Krogh, BH., Marculescu, R., “Hierarchical Adaptive Dynamic Power Management”. IEEE Trans. Comput. , pp 409–420, 2005.
  9. Theocharous, G., Mannor, S, Shah., N, Gandhi., P, Kveton., B, Siddiqi., Yu, CH.,“Machine Learning for A adaptive Power Management”. Intel Technol J, pp 299–312, 2006.
  10. Jun, H., Ammar, M., Corner, M., Zegura, E., “Hierarchical power management in disruption Tolerant Networks with Traffic-Aware Optimization”. Proceedings SIGCOMM Workshop on Chants, Paris, France, pp. 245–252, 2006.
  11. Chelius, Guillaume., Fleury, Eric., Mignon,Thierry., “Lower and Upper Bounds for Minimum Energy Broadcast and Sensing Problems in Sensor Networks”. The International Journal of Parallel, Emergent and Distributed Systems, Vol. 21, No. 6, pp 405–422. www.tandfonline.com, December 2006.
  12. Huang, Yangcheng., Bhatti, Saleem., Sørensen, SørenAksel., “The Impact of Topology Update Strategies on the Performance of a Proactive MANET Routing Protocol”. Int. J. of Parallel, Emergent and Distributed Systems Vol. 23, No. 6, pp 47–460, http://www.tandfonline.com, December 2008.
  13. Cao, Zhenwei., Easterling, David., “Power Saving Experiments for Large-Scale Global Optimisation”. International Journal of Parallel, Emergent and Distributed Systems Vol. 25, No. 5, pp 381–400, http://www.tandfonline.com, October 2010.
  14. Gouvy, Nicolas., Hamouda, Essia., Mitton, Nathalie., Simplot-Ryl, David., “Minimising Energy Consumption through Mobility with Connectivity Preservation in Sensor Networks”. International Journal of Parallel, Emergent and Distributed Systems Vol. 27, No. 6, pp 521–540, www.tandfonline.com, December 2012.
  15. Elavarasan, R., and Steffi, Perpectual A., “Energy Efficient Data Collections Structure for Wireless Sensor Networks”. International Journal of Science and Research (IJSR), ISSN 2319--7064, Volume 3 Issue 4, April 2014
  16. Bruschi, Roberto., Lago, Paolo., Lombardo, Alfio., Schembra, Giovanni.,“Modeling Power Management in Networked Devices”. Computer Communications. pp 95–109, www.elsevier.com/locate/com, 2014.
  17. Sharma, Rashmi., and Nitin. “Entropy, a New Dynamics Governing Parameter in Real Time Distributed System: A Simulation Study”. Int. J. of Parallel, Emergent and Distributed Systems,Vol. 29, No. 6, pp 562–586, www.tandfonline.com/loi/gpaa20,2014.
  18. Balachennaiah, P., Suryakalavathi, M., Nagendra, Palukuru.,“Optimizing Real Power Loss and Voltage Stability Limit of a Large Transmission Network using Firefly Algorithm”. Engineering Science and Technology, ttp://www.elsevier.com/locate/jestch,2015.
  19. Quwaider, Muhanna d., Al-Alyyoub, Mahmoud., Jararweh, Yaser., Duwairi, Rehab., “Experimental Framework for Mobile Cloud Computing System”. Procedia Computer Science 52, pp 1147 – 1152, www.sciencedirect.com,2015.
  20. Lyu, Yongqiang., Yan, Fanxi., Chen, Yu., Wang,Dan., Agoulmine,Nazim.,“High-Performance Scheduling Model for Multisensor Gateway of Cloud Sensor System-Based Smart- Living”. Information Fusion,pp 42–56, www.elsevier.com/locate/inffus,2015.
  21. Hn, Song. Li., Xin, bin., Liu, Zhixin., Guan, Xinping., “Distributed Hierarchical Game- Based Algorithm for Downlink Power Allocation in OFDMA Femto Cell Networks”.Computer Networks, pp 1–13, www.elsevier.com/locate/comnet,2015.
  22. Moety,Farah., Lahoud, Samer., Cousin,Bernard., Khawam,Kinda.,“Optimization Models for the Joint Power – Delay Minimization Problem in Green Wireless Access Networks.”
  23. Huang, Zh en., Chen, Jinbang., Lin, Yisong., You, Pengfei., Peng, Yuxing.,“Minimizing Data Redundancy for High Reliable Cloud Storage Systems”. Computer Networks pp 164–177, www.elsevier.com/locate/ comnet, 2015.
  24. A., Hassan., Hanan, A., Mohamed, Shimaa., M Sheta, Walaa., “Scalability and Communication Performance of HPC on Azure Cloud”. Egyptian Informatics Journal, www.sciencedirect.com, 2015.
  25. Agostini n, Lara. Filippini, Roberto. Nosella, Anna., “Management and Performance of Strategic Multipartner SME networks”. Int. J. Production Economics pp 376–390, www.elsevier.com/locate/ijpe, 2015.
  26. Alonso, M., Coll, S., Martínez , J.M ., Santonja, V., P, López., “ Power Consumption Management in Fat-Tree inter Connection Networks”. Parallel Computing pp 59–80, www.elsevier.com/locate/parco,2015.
  27. Zdraveski, Vladimir., Todorovski, Mirko., Kocarev, Ljupco., “ Dynamic Intelligent Load Balancing in Power Distribution Networks”. Electrical Power and Energy Systems pp 157–162, www.elsevier.com/ locate/ijepes, 2015.
  28. Krzysztof, Walkowiak., Michał, Woźniak., Mirosław, Klinkowski., Wojciech, Kmiecik., “Optical Networks for Cost-Efficient and Scalable Provisioning of Big Data Traffic”. Inter J. of Parallel, Emergent and Distributed Systems,Vol. 30, No. 1, pp 15–28, www.tandfonline.com/action/journalInformation , 2015.
  29. Al-Ayyoub, Mahmoud., et al. “Optimizing Expansion Strategies for Ultrascale Cloud Computing Data Centers.” Simulation Modelling Practice and Theory pp 15–29, www.elsevier.com/locate/simpat,2015.
  30. Jiang, Tao., et al. “Towards Secure and Reliable Cloud Storage Against Data Re-Outsourcing”.Future Generation Computer Systems, pp 86–94, www.elsevier.com/ locate/fgcs, 2015.
  31. Mershad N, Khaleel., Artail, Hassan., Saghir, Mazen., Hajj, Hazem., Awad, Mariette., “A Mathematical Model to Analyze the Utilization of a Cloud Data Center Middleware”. Journal of Network and Computer Applications, pp 399–415,www.elsevier.com/locate/ jnca, 2016.
  32. Alkhanak, EhabNabie., Peck Lee,Sai., Rezaei, Reza., Parizi, Reza Meimandi., “Cost Optimization Approaches for Scientific Work Flow Scheduling in Cloud and Grid Computing :A Review, Classifications and Open Issues”. The Journal of Sys. and Software, pp 1–26, www.elsevier.com/locate/jss,2016.
  33. He, Li., and Li, Furong., “A Fast Diagnosis Algorithm for Interconnection Network in High Performance Computers”.International Journal of Parallel, Emergent and Distributed Systems, Vol.31, No.1, pp 3446, www.tandfonline.com/action/journalInformation, 2016.
  34. Banditwattanawong, Thepparit., Masdisornchote, Masawee., Thayopas, Putchong.,“Multi-Provider Cloud Computing Network Infrastructure Optimization”.Future Generation Computer Systems, pp 116–128, www.elsevier.com/locate /fgcs,2016.
  35. Serrano, Damián., et al. “SLA Guarantees for Cloud Services”. Future Generation Computer Systems, pp 233–246, www.elsevier.com/locate/fgcs,2016.
Index Terms

Computer Science
Information Sciences

Keywords

Step Network System Energy Consumption Dynamic Power Management Application Level System Level Hardware Component Level. Distributed Computing.

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