CFP last date
20 May 2024
Reseach Article

An Energy Computation in Distributed Computing Environment through Bellman-Ford Algorithm

by Kamlesh Kumar Verma, Vipin Saxena
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 2
Year of Publication: 2016
Authors: Kamlesh Kumar Verma, Vipin Saxena
10.5120/ijca2016909675

Kamlesh Kumar Verma, Vipin Saxena . An Energy Computation in Distributed Computing Environment through Bellman-Ford Algorithm. International Journal of Computer Applications. 142, 2 ( May 2016), 1-6. DOI=10.5120/ijca2016909675

@article{ 10.5120/ijca2016909675,
author = { Kamlesh Kumar Verma, Vipin Saxena },
title = { An Energy Computation in Distributed Computing Environment through Bellman-Ford Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 2 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number2/24865-2016909675/ },
doi = { 10.5120/ijca2016909675 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:49.623274+05:30
%A Kamlesh Kumar Verma
%A Vipin Saxena
%T An Energy Computation in Distributed Computing Environment through Bellman-Ford Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 2
%P 1-6
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the current scenario, energy optimization for the electrical components used in the hand-held devices is a broad area of research. Energy principle for information technology contains its own specific energy behavior. The energy costs in server centre are now compatibility to the cost of hardware devices and other compare devices. In the processor device system, heat existing is a major cause of limiting changes in the performance evaluation. In laptop, scanners, computers, cell phones, printers, i-pods, and other digital devices, which are portable, reduced the power consumption converts into the battery long life manner. The energy consumption is now presenting challenges as a performance measure in computers, processing the task execution time. The energy is linked with the execution time capacity, where comparable patterns have been recognized by a combination of hardware devices, software devices, and algorithms. In this paper, the design of energy-efficient computer systems is proposed by the use of Bellman-ford algorithmic approach. A model is proposed for finding the performance of the system. Computed results are depicted in the form of tables and graphs.

References
  1. Lange, C., Kosiankowski, D., Weidmann, R., Gladish, A., “Energy Consumption of Telecommunication Networks and Related Improvement Options”. pp. 285-295 (2011).
  2. Bolla, R., et al. “Energy Efficiency In The Future internet:: A Survey of Existing Approaches and Trends In Energy Aware Fixed Network Infrastructures”,pp. 233– 44, 2011.
  3. Tseng, Po-Kai., and Chung, Wei-Ho., “Near Optimal Link On/Off Scheduling and Weight Assignment For Minimizi IP Network Energy Consumption”.Computer Comm. pp. 729–737, 2012.
  4. Ballga, Jayant.,Ayre,Robert., Hinton, Kerry.,and S.Tucker, Rodney., “ Energy Consumption in Wired and Wirelessaccess Networks”. Energy Efficiency in Communicationspp.70-77, IEEE Communications Magazine, 2011.
  5. Gaona, E., Titos, R., Fernández, J., Acacio, M. E., Fernández , J., “ On The Design Of Energy EfficientHardware Transactional Memory System”. Concurrencyand Computation:Practice and Experience, Published,2012
  6. Chiaraviglio, Luca., et al. “Modelling Sleep Mode GainsIn Energy-Aware Networks”. pp. 3051–3066, Computer Networks, 2013.
  7. Castane, Gabriel G., Llopis, Pablo., Carretero, Jesús.,“ E-Mc2: A Formal Framework For Energy Modelling In Cloud Computing”. Simulation Modelling Practice and Theory pp. 56–75, 2013.
  8. Schien, Daniel., Shabajee, Paul., et al., “ Modeling andAssessing Variability in Energy Consumption During the Use Stage of Online Multimedia Services”. Journal of Industrial Ecology Information and Communication Technology (ICT), 2013.
  9. Lin, Gongqi., Soh, Sieteng., Chin, Kwan-Wu., Lazarescu, Mihai.,“Efficient Heuristics For Energy-Aware Routing In Networks with Bundled Link”.Computer Networks pp. 1774–1788, 2013.
  10. Andrews, Matthew., Fernandez Anta, Antonio., Zhang, Lisa., et al., “ Routing and Scheduling for Energy and Delay Minimization in the Power down Model”. pp. 226- 237, 2013.
  11. Anbazhagan, Rajesh., and Rangaswamy, Nakkeeran., “Investigations on Enhanced Power Saving Mechanism for IEEE 802.16m Network with Heterogeneous Traffic” Journal of Network and Computer Applications, 2014.
  12. Lewis, Adam., Ghosh, Soumik., and Tzeng, N.-F., “Run-Time energy Consumption Estimation Based on Workload in Server Systems”. University of Louisiana, Lafayette, Louisiana 70504.
  13. Bilal, Kashif., Khalid,Osman.,Alvarez,Enrique., Hameed, Abdul., et, al. “A Taxonomy and Survey On Green Data Center Networks”. Future GenerationComputer Systems, pp. 189–208, 2014.
  14. Niewiadomska - Szynkiewicz, Ewa., Sikora, Andrzej., Arabas, Piotr., et al. “ Dynamic Power Management In Energy-Aware Computer Networks and Data Intensive ComputingSystem”.Future Generation Computer Systemspp. 284–296, 2014.
  15. Galinina, Olga., Andreev, Sergey., Turlikov, Andrey., Koucheryavy, Yevgeni., “ Optimizing Energy Efficiencyof A Multi – Radio Mobile Device In Heterogeneous Beyond - 4G Networks”. Performance Evaluation, pp. 18– 41, 2014.
  16. Fang, Weiwei., Li, Yangchun., Zhang, Huijing., Xiong, Naixue., et al. “ On The Throughput - Energy Trade off For Data Transmission between Cloud and Mobile Devices”. Information Sciences, pp 79–93, 2014.
  17. Alzamil, Ibrahim., Djemame, Karim., et al., “ Energy- Aware Profiling for Cloud Computing Environments”. Electronic Notes in Theoretical Computer Science pp. 91–108, 2015.
  18. Prem Bianzino, Aruna., Claude, Chaudet., Rossi, Dario., et al., “A Step Towards Energy Efficient Wired NetworkNetworks”, Green Networking, 2013.
  19. Niewiadomska - Szynkiewicz, Ewa., Sikora, Andrzej., Arabas, Piotr., et al. “ Control System For Reducing Energy Consumption In Backbone Computer Network”. Concurrency Computat., pp. 1738–1754 , 2013.
  20. Sivaraman, V., Reviriego, P., Zhao, Z., Sánchez-Macián, A., Vishwanath, A., et al. “An experimental Power profile of Energy Efficient Ethernet Switches”. Computer Communications, pp. 110–118, Computer Comm, 2014.
  21. Tekbiyik, Neyre., and Uysal - biyikoglu, Elif., “ EnergyEfficient Wireless Unicast Routing Alternatives for Machine-To-Machine Networks”. Journal of Networkand Computer Applications pp.1587–1614, 2011.
  22. Bolla, Raffaele., Bruschi, Roberto., Jaramillo Ortiz, Olga Maria., Rubaldo, Mirko., “ Burst2Save : Reducing Network – Induced Energy Consumption in the HomeEnvironment”. Computer Communications pp. 37–46, 2014.
  23. Jiang, Dingde., Xu, Zhengzheng., Wenpan Li.,et al., “Topology Control - Based Collaborative Multicast Routing Algorithm With Mini. Energy Consumption”.International Journal Of Comm. Systems, 2014.
  24. Hashimoto, Masafumi., Go, Hasegawa., Masayuki, Murata., “ An Analysis Of Energy Consumption For TCP Data Transfer With Burst Transmission Over A Wireless LAN”. International Journal of Commun. Systems”. Int. J. Commun. Syst, 2014.
  25. Vardalis, Dimitris., Tsaoussidis, Vassilis.,“ ExploitingThe Potential of DTN for Energy Efficient Internetworking”.The Journal of Systems and software , pp. 91–103, 2014.
  26. Coroama, Vlad C., Hilty, Lorenz M., “Assessing Internet Energy Intensity: A Review of Methods and Results”. Environmental Impact Assessment Review, pp. 63–68, 2014.
  27. Coiro, Angelo., Chiaraviglio, Luca., Cianfrani, Antonio., et al. “ Reducing Power Consumption In Backbone IPNetworks Through Table Lookup Bypass.” Computer Networks, pp. 125–142, 2014.
  28. Bonetto, Edoardo.,Finamore, Alessandro.,Mellia, Marco., Fiandra, Riccardo., “ Energy Efficiency In Access and Aggregation Networks:From Current Traffic to Potential Savings.” Computer Networks, pp. 151– 166, 2014.
  29. Fatih Tuysuz, Mehmet., “An Energy-Efficient Qos - Based Network Selection Scheme Over Heterogeneous WLAN – 3G Networks”, Computer Networks, pp.113– 133, 2014.
  30. Ahmed, Ejaz., Buyya, Rajkumar., Akhunzada, Adnan., Gani, Abdullah., et al. “ Network centric Performance Analysis Of Runtime Application Migration In MobileCloud Computing”. Simulation Modelling Practice and Theory, pp. 42–56, 2015.
  31. David, Howard., Fallin, Chris., Gorbatov, Eugene., Hanebutte, Ulf. R., Mutlu, Onur., “ Memory Power Management via Dynamic Voltage/Frequency Scaling”, ICAC’11, ACM 978-1-4503-0607.
Index Terms

Computer Science
Information Sciences

Keywords

Energy Optimization Wired Networks Topology Packet Routing QoS Bellman-ford Algorithm Optimization Techniques.