ABSTRACT
Internet of Things (IoT) plays a major role in connecting the physical world with the cyber world through new services and seamless interconnection between heterogeneous devices. Such heterogeneous devices tend to generate a massive volume of Big Data. However, exploiting green schemes for IoT is still a challenge since IoT attains a large scale and becomes more multifaceted, the current trends of analyzing Big Data are not directly applicable to it. Similarly, achieving green IoT through the use of 5G also poses new challenges when it comes to transferring huge volume of data in an efficient way. To address the challenges above, this paper presents a scheme for human- enabled green IoT in 5G network. Green IoT is achieved by grouping mobile nodes in a cluster. Also, a mobility management model is designed that helps in triggering efficient handover and selecting optimal networks based on multi-criteria decision modeling. Afterward, we design a network architecture that integrates green IoT with 5G network. Moreover, the 5G network architecture is supported by proposed protocol stack, which maps Internet Protocol (IP), Medium Access Protocol (MAC), and Location identifiers (LOC). The proposed scheme is also implemented using C programming language to validate mobility model in 5G, regarding cost, energy, and Quality of Service.
- Huang, Jun, Yu Meng, Xuehong Gong, Yanbing Liu, and Qiang Duan. "A novel deployment scheme for the green internet of things." Internet of Things Journal, IEEE 1, no. 2 (2014): 196--205. Google ScholarCross Ref
- Atzori L, Iera A, Morabito G. The internet of things: A survey. Computer networks. 2010 Oct 28;54(15):2787--805 Google ScholarDigital Library
- Xiang, Liu, Jun Luo, Chenwei Deng, Athanasios V. Vasilakos, and Weisi Lin. "DECA: Recovering fields of physical quantities from incomplete sensory data." In Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2012 9th Annual IEEE Communications Society Conference on, pp. 182--190. IEEE, 2012. Google ScholarCross Ref
- Jelicic, Vana, Michele Magno, Davide Brunelli, Giacomo Paci, and Luca Benini. "Context-adaptive multimodal wireless sensor network for energy-efficient gas monitoring." Sensors Journal, IEEE 13, no. 1 (2013): 328--338. Google ScholarCross Ref
- Wang, Li-Chun, and Suresh Rangapillai. "A survey on green 5G cellular networks." In Signal Processing and Communications (SPCOM), 2012 International Conference on, pp. 1--5. IEEE, 2012. Google ScholarCross Ref
- Palattella M, Dohler M, Grieco A, Rizzo G, Torsner J, Engel T, Ladid L. "Internet of Things in the 5G Era: Enablers, Architecture and Business Models." IEEE Journal on Selected Areas in Communications, vol. 34, no. 3, march 2016. Google ScholarCross Ref
- M. Khan and K. Han, "A Vertical Handover Management Scheme based on Decision Modelling in Heterogeneous Wireless Networks," IETE Technical Review, Vol. 32, no. 6, pp. 402--412, 2015. Google ScholarCross Ref
- M. Khan and K. Han, "A Survey of Context Aware Vertical Handover Management Schemes in Heterogeneous Wireless Networks," Wireless Personal Communications, vol. 85, no. 4, pp. 2273--2293, 2015. Google ScholarDigital Library
- Ericsson, A. B. "Sustainable energy use in mobile communications." white paper, EAB-07:02l80l Uen Rev C (2007).Google Scholar
- Zhou J, Li M, Liu L, She X, Chen L. Energy source aware target cell selection and coverage optimization for power saving in cellular networks. InGreen Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) 2010 Dec 18 (pp. 1--8). IEEE. Google ScholarDigital Library
- Han, Tao, and Nirwan Ansari. "ICE: Intelligent cell breathing to optimize the utilization of green energy." Communications Letters, IEEE 16, no. 6 (2012): 866--869. Google ScholarCross Ref
- Han, Tao, and Nayeem Ansari. "Optimizing cell size for energy saving in cellular networks with hybrid energy supplies." In Global Communications Conference (GLOBECOM), 2012 IEEE, pp. 5189--5193. IEEE, 2012.Google Scholar
- Abdullah, Saad, and Kun Yang. "An energy-efficient message scheduling algorithm in Internet of Things environment." In Wireless Communications and Mobile Computing Conference (IWCMC), 2013 9th International, pp. 311--316. IEEE, 2013. Google ScholarCross Ref
- Zhang, Jingyao, Srikrishna Iyer, Patrick Schaumont, and Yaling Yang. "Simulating power/energy consumption of sensor nodes with flexible hardware in wireless networks." In Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2012 9th Annual IEEE Communications Society Conference on, pp. 112--120. IEEE, 2012. Google ScholarCross Ref
- J Liang, Jia-Ming, Jen-Jee Chen, Hung-Hsin Cheng, and Yu-Chee Tseng. "An energy-efficient sleep scheduling with QoS consideration in 3GPP LTE-advanced networks for internet of things." Emerging and Selected Topics in Circuits and Systems, IEEE Journal on 3, no. 1 (2013): 13--22.Google ScholarCross Ref
- Ben Nacef, Ahmed, S. Senouci, Yacine Ghamri-Doudane, and André-Luc Beylot. "Ecar: An energy/channel aware routing protocol for cooperative wireless sensor networks." In Personal Indoor and Mobile Radio Communications (PIMRC), 2011 IEEE 22nd International Symposium on, pp. 964--969. IEEE, 2011.Google Scholar
- Xu, Mingdong, and Henry Leung. "A joint fusion, power allocation and delay optimization approach for wireless sensor networks." Sensors Journal, IEEE 11, no. 3 (2011): 737--744. Google ScholarCross Ref
- Trestian, R., Ormond, O., and Muntean, G. M. "Energy-Quality-Cost Tradeoff in a Multimedia-Based Heterogeneous Wireless Network Environment." Broadcasting, IEEE Transactions on, 59.2 (2013). Page(s): 340--357.Google ScholarCross Ref
- Ahmad, Awais, Sohail Jabbar, Anand Paul, and Seungmin Rho. "Mobility aware energy efficient congestion control in mobile wireless sensor network." International Journal of Distributed Sensor Networks 2014 (2014). Google ScholarCross Ref
- 3GPP TS 22.368 V11.0.0, "Service Requirements for Machine-Type Communications," Dec. 2010.Google Scholar
- Nguyen-Vuong, Quoc-Thinh, Nazim Agoulmine, and Yacine Ghamri-Doudane. "A user-centric and context-aware solution to interface management and access network selection in heterogeneous wireless environments." Computer Networks 52, no. 18 (2008): 3358--3372. Google ScholarDigital Library
- Aziz, Danish, and Rolf Sigle. "Improvement of LTE handover performance through interference coordination." In Vehicular Technology Conference, 2009. VTC Spring 2009. IEEE 69th, pp. 1--5. IEEE, 2009. Google ScholarCross Ref
- Patouni, Eleni, Nancy Alonistioti, and Lazaros Merakos. "Modeling and performance evaluation of reconfiguration decision making in heterogeneous radio network environments." Vehicular Technology, IEEE Transactions on 59, no. 4 (2010): 1887--1900. Google ScholarCross Ref
Index Terms
- Human enabled green IoT in 5G networks
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