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Enhancing Energy Consumption in Wireless Communication Systems using Weighted Sum Approach


  • Department of Computer Science, Faculty of Science Semlalia, Cadi Ayyad University, Morocco
  • Department of Physics, Faculty of Science Semlalia, Cadi Ayyad University, Morocco


Collaborative communication technologies have known a great development that allows achieving various communications. However, the uncontrolled selection of the communication technology spent more energy. The main goal of this paper is minimizing the energy consumed in accessing to data by users. To do so, we propose to integrate an efficient weighted sum selection approach in order to choice the suitable communication system that can be used by user. This smart selection considered a number of essential criteria. Implementation results confirmed that the proposed approach is more efficient than the traditional process of communication.


Green Communication, 4G, Multi-Criteria Selection, Wireless, Weighted Sum.

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  • Keshav K, Indukuri VR, Venkataram P. Energy Efficient Scheduling in 4G Smart Phones for Mobile Hotspot Application. National Conference on Communications, NCC, 2012.
  • Kalic G, Bojic I, Kusek M. Energy Consumption in Android Phones When Using Wireless Communication Technologies. MIPRO, Proceedings of the 35th International Convention, 2012. p. 754–9.
  • Gross C, Kaup F, Stingl D, Richerzhagen D, Hausheer D, Steinmetz R. EnerSim: An Energy Consumption Model for Large-Scale Overlay Simulators. In Proceedings - Conference on Local Computer Networks, LCN. 2013. p. 252–5.
  • Kwon YW, Tilevich E. Reducing the Energy Consumption of Mobile Applications Behind the Scenes. IEEE International Conference on Software Maintenance; 2013. p. 170–9.
  • Vergara EJ, Nadjm-Tehrani S. Energy Box: A Trace-Driven Tool for Data Transmission Energy Consumption Studies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).2013. p. 19–34.
  • Balasubramanian N, Balasubramanian A, Venkataramani A. Energy onsumption in Mobile Phones: A Measurement Study and Implications for Network Applications. Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference - IMC’09, 2009. p. 280–93.
  • Sheng X, Tang J, Zhang W. Energy-Efficient Collaborative Sensing with Mobile Phones. In Proceedings - IEEE INFOCOM, 2012. p. 1916–24.
  • Damasevicius R, Stuikys V, Toldinas J. Methods for Measurement of Energy Consumption in
  • Mobile Devices. Metrology and Measurement Systems.2013; 20(3):419–30.
  • Perälä PHJ, Barbuzzi A, Boggia G,Pentikousis K. Theory and Practice of RRC State Transitions in UMTS Networks. IEEE Broadband Wireless Access Workshop, Hawaii, USA:2009.
  • Han H, Yu J, Zhu H, Chen Y. Energy-Efficient Engine for Frame Rate Adaptation on Smartphones. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems - SenSys’13,2013. p. 1–14.
  • Xiao Y, Savolainen P, Karppanen A, Siekkinen M, Ylä-Jääski A. Practical Power Modeling of Data Transmission over 802.11g for Wireless Applications. Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, Germany: 2010.
  • Zhang L, Tiwana B, Qian Z, Wang Z, Dick RP, Mao ZM, Yang L. Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphones. In International Conference on Hardware-Software Codesign and System Synthesis, Scottsdale, USA: 2010.
  • Harjula E, Kassinen O, Ylianttila M. Energy Consumption Model for Mobile Devices in 4G and WLAN networks IEEE Consumer Communications and Networking Conference (CCNC), 2012 Jan 14-17.
  • Miranda P, Siekkinen M, Waris H. TLS and Energy Consumption on a Mobile Device: A Measurement Study. IEEE Computers and Communications (ISCC),2011 June 28-1 July.
  • Abbas N, Taleb S, Hajj H, Dawy Z. A Learning-Based Approach for Network Selection in WLAN/4G Heterogeneous Network. in Third International Conference on Communications and Information Technology (ICCIT), 2013 Jun 19-21.
  • Le. Wang, Manner J. Energy Consumption Analysis of WLAN, 2G and 3G interfaces. In Proceedings - IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM. Computing, CPSCom;2010. Dec 18-20.
  • Ravi A, Peddoju SK. Mobility Managed Energy Efficient Android Mobile Devices Using Cloudlet. Students’ Technology Symposium (TechSym), IEEE.2014 Feb. 28-March 2.
  • Wang Y, Zhang L, An H, Xu B, Xi G. Power Consumption Testing and Optimization for Mobile Router Based on Data Aggregation and Compression. 16th International Symposium on Wireless Personal Multimedia Communications (WPMC), 2013 16th International Symposium on ,2013 Jun 24-27.
  • Christensen S, Agrwal R , Carvalho E, Cioffi JM. Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design. IEEE Transactions on Wireless Communications, 2008. p. 4792–9.


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