Weitere Artikel dieser Ausgabe durch Wischen aufrufen
In recent years, smart grid (SG) applications have been proven a sophisticated technology of immense aptitude, comfort and efficiency not only for the power generation sectors but also for other industrial purposes. The term SG is used to describe a set of systems customized to rapidly and automatically monitor user demand, restore power, isolate faults and maintain stability for more efficient transmission, generation and delivery of electric power. Nevertheless, the quality of service (QoS) guarantee is essential to maintain the networking technology used in different stages and communication of the SG for efficient distribution, which may be drastically obstructed as the sensors of the application increases. Undoubtedly, receiving and transmitting of this information requires two-way, high speed, reliable and secure communication infrastructure. In this paper, we have proposed a scheduling approach guarantees the efficient utilization of existing network resources that satisfy the sensors’ demands sufficiently. The proposed approach is based on hierarchical adaptive weighting method, which helps to overcome the issues of studied scheduling approach and intended to aid SG sensors applications, based on its QoS demands. We have employed four enabler SG applications for remote power control, namely demand response, advanced metering infrastructure, video surveillance and wide area situational awareness applications for the implementation of the remote-power substation controlling. Moreover, the cooperative game theory technique has been incorporated into a solution for the optimal estimation and allocation of bandwidth among different sensors. The results have been evaluated in terms of throughput, fairness index and spectral efficiency and results have been compared with the well-known scheduling approaches such as exponential/proportional fairness (EXP/PF), best channel quality indicator (Best-CQI) and exponential rules (EXP-Rule). The results demonstrated that the proposed approach is providing a better performance in terms fairness index by 25, 66 and 68% compared to EXP/PF, EXP/RULE and Best-CQI, respectively.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
Yates, R. D. (1995). A framework for uplink power control in cellular radio systems. IEEE Journal on Selected Areas in Communications, 13, 1341–1347. CrossRef
Hu, J., Leung, V. C., Yang, K., Zhang, Y., Gao, J., & Yang, S. (2016). Smart grid inspired future technologies. New York: Springer.
Tuballa, M. L., & Abundo, M. L. (2016). A review of the development of Smart Grid technologies. Renewable and Sustainable Energy Reviews, 59, 710–725. CrossRef
Garau, M., Anedda, M., Desogus, C., Ghiani, E., Murroni, M., & Celli, G. (2017). A 5G cellular technology for distributed monitoring and control in smart grid. In 2017 IEEE international symposium on broadband multimedia systems and broadcasting (BMSB) (pp. 1–6).
Pandey, R. K., & Misra, M. (2016). Cyber security threats—Smart grid infrastructure. In Power systems conference (NPSC), 2016 national (pp. 1–6).
Garau, M., Celli, G., Ghiani, E., Pilo, F., & Corti, S. (2017). Evaluation of smart grid communication technologies with a co-simulation platform. IEEE Wireless Communications, 24, 42–49. CrossRef
Qamar, F., Abbas, T., Hindia, M. N., Dimyati, K. B., Noordin, K. A. B., & Ahmed, I. (2017). Characterization of MIMO propagation channel at 15 GHz for the 5G spectrum. In 2017 IEEE 13th Malaysia international conference on communications (MICC) (pp. 265–270).
Hajjawi, A., Ismail, M., Abdullah, N. F., & Ramli, N. (2015). A novel scheduling algorithm based class-service using game theory for LTE network. In 2015 IEEE 12th Malaysia international conference on communications (MICC) (pp. 351–355).
Webster, R., Munasinghe, K., & Jamalipour, A. (2016). Optimized resource allocation in LTE networks incorporating delay-sensitive Smart Grid traffic. In 2016 IEEE international conference on smart grid communications (SmartGridComm) (pp. 423–428).
Trabelsi, S., Belghith, A., Zarai, F., & Obaidat, M. S. (2015). Performance evaluation of a decoupled-level with QoS-aware downlink scheduling algorithm for LTE networks. In 2015 IEEE international conference on data science and data intensive systems (DSDIS). (pp. 696–704).
Iosif, O., & Banica, I. (2011). On the analysis of packet scheduling in downlink 3GPP LTE system. CTRQ, 2011, 106.
Qamar, F., Siddiqui, M. H. S., Dimyati, K., Noordin, K. A. B., & Majed, M. B. (2017). Channel characterization of 28 and 38 GHz MM-wave frequency band spectrum for the future 5G network. In 2017 IEEE 15th student conference on research and development (SCOReD) (pp. 291–296).
Mushtaq, A.-S., Haider, A.-Z., Orest, L., & Mykhailo, K. (2015). Improving QoS in MAX C/I scheduling using resource allocation type 1 of LTE. In 2015 13th international conference on experience of designing and application of CAD systems in microelectronics (CADSM) (pp. 12–14).
Miki, N., & Takemoto, T. (2015). Investigation on resource selection scheme based on proportional fair criteria. In 2015 international conference on information and communication technology convergence (ICTC) (pp. 220–223).
Hajjawi, A., & Ismail, M. (2015). A scheduling algorithm based self-learning technique for smart grid communications over 4G networks. Journal of Communications, 10, 876–881.
Iturralde, M., Yahiya, T. A., Wei, A., & Beylot, A.-L. (2011). Performance study of multimedia services using virtual token mechanism for resource allocation in LTE networks. In 2011 IEEE vehicular technology conference (VTC Fall) (pp. 1–5).
Nasralla, M. M., & Martini, M. G. (2013). A downlink scheduling approach for balancing QoS in LTE wireless networks. In 2013 IEEE 24th international symposium on personal indoor and mobile radio communications (PIMRC) (pp. 1571–1575).
Samia, D., & Ridha, B. (2015). A new scheduling algorithm for real-time communication in LTE networks. In 2015 IEEE 29th international conference on advanced information networking and applications workshops (WAINA) (pp. 267–271).
Li, Y.-P., Hu, B.-J., Zhu, H., Wei, Z.-H., & Gao, W. (2016). A delay priority scheduling algorithm for downlink real-time traffic in LTE networks. In Information technology, networking, electronic and automation control conference, IEEE, 2016 (pp. 706–709).
Mohsenian-Rad, A.-H., Wong, V. W., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010). Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1, 320–331. CrossRef
Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., et al. (2011). Smart grid technologies: Communication technologies and standards. IEEE Transactions on Industrial Informatics, 7, 529–539. CrossRef
Jorguseski, L., Zhang, H., Chrysalos, M., Golinski, M., & Toh, Y. (2017). LTE delay assessment for real-time management of future smart grids. In Smart grid inspired future technologies: First international conference, SmartGIFT 2016, Liverpool, UK, May 19–20, 2016, revised selected papers (pp. 204–213).
Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and challenges of wireless sensor networks in smart grid. IEEE Transactions on Industrial Electronics, 57, 3557–3564. CrossRef
Markkula, J., & Haapola, J. (2017). Ad hoc LTE method for resilient smart grid communications. Wireless Personal Communications, 98(4), 3355–3375. CrossRef
Ajiboye, S. O., Birch, P., Chatwin, C., & Young, R. (2015). Hierarchical video surveillance architecture: A chassis for video big data analytics and exploration. In IS&T/SPIE Electronic Imaging, 2015. (pp. 94070k-1–9040k-10).
Chiu, A., Ipakchi, A., Chuang, A., Qiu, B., Brooks, D., & Koch, E., et al. (2009). Framework for integrated demand response (DR) and distributed energy resources (DER) models. NAESB and UCAIug.
Mohagheghi, S., Stoupis, J., Wang, Z., Li, Z., & Kazemzadeh, H. (2010). Demand response architecture: Integration into the distribution management system. In 2010 first IEEE international conference on smart grid communications (SmartGridComm) (pp. 501–506).
Reid, M., Levy, R., & Silverstein, A. (2010). Coordination of energy efficiency and demand response. Ernest Orlando Lawrence Berkeley National Laboratory, Charles Goldman.
Motegi, N., Piette, M. A., Watson, D. S., Kiliccote, S. & Xu, P. (2007). Introduction to commercial building control strategies and techniques for demand response. Lawrence Berkeley National Laboratory LBNL-59975.
Elma, O., & Selamoğullari, U. S. (2017). An overview of demand response applications under smart grid concept. In 2017 4th international conference on electrical and electronic engineering (ICEEE) (pp. 104–107).
Siano, P. (2014). Demand response and smart grids: A survey. Renewable and Sustainable Energy Reviews, 30, 461–478. CrossRef
Alcaraz, C., & Lopez, J. (2014). WASAM: A dynamic wide-area situational awareness model for critical domains in Smart Grids. Future Generation Computer Systems, 30, 146–154. CrossRef
Mohassel, R. R., Fung, A., Mohammadi, F., & Raahemifar, K. (2014). A survey on advanced metering infrastructure. International Journal of Electrical Power and Energy Systems, 63, 473–484. CrossRef
Abbas, T., Qamar, F., Ahmed, I., Dimyati, K., & Majed, M. B. (2017). Propagation channel characterization for 28 and 73 GHz millimeter-wave 5G frequency band. In 2017 IEEE 15th student conference on research and development (SCOReD) (pp. 297–302).
Erol-Kantarci, M., & Mouftah, H. T. (2015). Energy-efficient information and communication infrastructures in the smart grid: A survey on interactions and open issues. IEEE Communications Surveys and Tutorials, 17, 179–197. CrossRef
Yigit, M., Gungor, V. C., Tuna, G., Rangoussi, M., & Fadel, E. (2014). Power line communication technologies for smart grid applications: A review of advances and challenges. Computer Networks, 70, 366–383. CrossRef
He, W., & Da Xu, L. (2014). Integration of distributed enterprise applications: A survey. IEEE Transactions on Industrial Informatics, 10, 35–42. CrossRef
Kuzlu, M., Pipattanasomporn, M., & Rahman, S. (2014). Communication network requirements for major smart grid applications in HAN, NAN and WAN. Computer Networks, 67, 74–88. CrossRef
Chakir, M., Kamwa, I., & Le Huy, H. (2014). Extended C37. 118.1 PMU algorithms for joint tracking of fundamental and harmonic phasors in stressed power systems and microgrids. IEEE Transactions on Power Delivery, 29, 1465–1480. CrossRef
Hindia, M. N., Reza, A. W., Noordin, K. A., & Chayon, M. H. R. (2015). A novel LTE scheduling algorithm for green technology in smart grid. PLoS ONE, 10, e0121901. CrossRef
Usman, A., & Shami, S. H. (2013). Evolution of communication technologies for smart grid applications. Renewable and Sustainable Energy Reviews, 19, 191–199. CrossRef
Hu, H., Kaleshi, D., Doufexi, A., & Li, L. (2015). Performance analysis of IEEE 802.11 af standard based neighbourhood area network for smart grid applications. In 2015 IEEE 81st vehicular technology conference (VTC Spring) (pp. 1–5).
Aldhaibani, J. A., Yahya, A., Ahmad, R., Omar, N., & Ali, Z. G. (2013). Effect of relay location on two-way DF and AF relay for multi-user system in LTE-A cellular networks. In Business engineering and industrial applications colloquium (BEIAC), 2013 IEEE (pp. 380–385).
Scheme, B. T. (2009). LTE: The evolution of mobile broadband. IEEE Communications Magazine, 45, 44–51.
Qamar, F., Dimyati, K. B., Hindia, M. N., Noordin, K. A. B., & Al-Samman, A. M. (2017). A comprehensive review on coordinated multi-point operation for LTE-A. Computer Networks, 123, 19–37. CrossRef
Lee, S.-B., Pefkianakis, I., Meyerson, A., Xu, S., & Lu, S. (2009). Proportional fair frequency-domain packet scheduling for 3GPP LTE uplink. In INFOCOM 2009, IEEE (pp. 2611–2615).
Hajjawi, A., Ismail, M., & Yuwono, T. (2015). Implementation of three scheduling algorithms in the smart grid communications over 4G networks. In 2015 international conference on space science and communication (IconSpace) (pp. 28–32).
Kalalas, C., Thrybom, L., & Alonso-Zarate, J. (2016). Cellular communications for smart grid neighborhood area networks: A survey. IEEE Access, 4, 1469–1493. CrossRef
Feng, F., Peng, F., Yan, B., Lin, S., & Zhang, J. (2017) QoS-based LTE downlink scheduling algorithm for smart grid communication. In 2017 IEEE 9th international conference on communication software and networks (ICCSN) (pp. 548–552).
Capozzi, F., Piro, G., Grieco, L. A., Boggia, G., & Camarda, P. (2013). Downlink packet scheduling in LTE cellular networks: Key design issues and a survey. IEEE Communications Surveys and Tutorials, 15, 678–700. CrossRef
Udeshi, D., & Qamar, F. (2014). Quality analysis of epon network for uplink and downlink design. Asian Journal of Engineering, Sciences and Technology, 4, 10–17.
Rebekka, B., & Malarkodi, B. (2014). Performance evaluation of resource allocation schemes in LTE downlink. In 2014 International conference on electronics and communication systems (ICECS) (pp. 1–4).
Basukala, R., Ramli, H. M., & Sandrasegaran, K. (2009) Performance analysis of EXP, PF and M-LWDF in downlink 3GPP LTE system. In First Asian Himalayas international conference on internet, 2009. AH-ICI 2009 (pp. 1–5).
Hindia, M. N., Reza, A. W., & Noordin, K. A. (2015). A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network. International Journal of Distributed Sensor Networks, 11, 604752. CrossRef
Wang, J., Xia, C., Wang, Y., Ding, S., & Sun, J. (2012). Spatial prisoner’s dilemma games with increasing size of the interaction neighborhood on regular lattices. Chinese Science Bulletin, 57, 724–728. CrossRef
Ma, Z.-Q., Xia, C.-Y., Sun, S.-W., Wang, L., Wang, H.-B., & Wang, J. (2011). Heterogeneous link weight promotes the cooperation in spatial prisoner’s dilemma. International Journal of Modern Physics C, 22, 1257–1268. CrossRef
Iturralde, M., Wei, A., Ali-Yahiya, T., & Beylot, A.-L. (2013). Resource allocation for real time services in LTE networks: Resource allocation using cooperative game theory and virtual token mechanism. Wireless Personal Communications, 72, 1415–1435. CrossRef
Hajjawi, A., Ismail, M., & Abdullah, N. F. (2016). A scheduling scheme for smart grid and mobile users over LTE networks. In International conference on advances in electrical, electronic and systems engineering (ICAEES) (pp. 421-426).
O’Neill, B. (1982). A problem of rights arbitration from the Talmud. Mathematical Social Sciences, 2, 345–371. CrossRef
Procaccia, A. D., Shah, N., & Tucker, M. L. (2014). On the structure of synergies in cooperative games. In AAAI (pp. 763–769).
Andrews, J. G., Gupta, A. K., & Dhillon, H. S. (2016) A primer on cellular network analysis using stochastic geometry. arXiv preprint arXiv:1604.03183.
Taylor, H. M., & Karlin, S. (2014). An introduction to stochastic modeling. New York: Academic Press.
Dargie, W., & Schill, A. (2011). Stability and performance analysis of randomly deployed wireless networks. Journal of Computer and System Sciences, 77, 852–860. CrossRef
ElSawy, H., Hossain, E., & Haenggi, M. (2013). Stochastic geometry for modeling, analysis, and design of multi-tier and cognitive cellular wireless networks: A survey. IEEE Communications Surveys and Tutorials, 15, 996–1019. CrossRef
Dobkin, D., & Silver, D. (1990). Applied computational geometry: Towards robust solutions of basic problems. Journal of Computer and System Sciences, 40, 70–87. CrossRef
Lucarini, V. (2009). Symmetry-break in Voronoi tessellations. Symmetry, 1, 21–54. CrossRef
Guo, X., & Song, P. (2010). Simulink based LTE system simulator, M. Sci. thesis, Chalmers University of Technology, Goteborg, Sweden.
Kauser, N., Saw, J., & Gelbman, P. (2011). System and method for cell planning in a wireless communication network. Google Patents.
Shi, W., Zhu, Z., Zhang, M., & Ansari, N. (2013). On the effect of bandwidth fragmentation on blocking probability in elastic optical networks. IEEE Transactions on Communications, 61, 2970–2978. CrossRef
ETSI, T. (2000). 125 211 V3. 1.1 universal mobile telecommunications system (UMTS). Physical channels and mapping of transport channels onto physical channels (FDD) (3GPP TS 25.211 version 6.1. 0 Release 6) (pp. 0000–0001).
Singh, Y. (2012). Comparison of okumura, hata and cost-231 models on the basis of path loss and signal strength. International Journal of Computer Applications, 59, 37–41. CrossRef
Nguyen, S. C., Sandrasegaran, K., & Madani, F. M. J. (2011). Modeling and simulation of packet scheduling in the downlink LTE-advanced. In 2011 17th Asia-Pacific conference on communications (APCC) (pp. 53–57).
Sandrasegaran, K., Patachaianand, R., & Madani, F. M. (2010). Joint delay-aware opportunistic scheduling algorithm with reduced feedback to exploit multiuser diversity. In 2010 International conference on computer applications and industrial electronics (ICCAIE) (pp. 432–437).
Chung, W. G., Lim, E., Yook, J. G., & Park, H. K. (2007). Calculation of spectral efficiency for estimating spectrum requirements of IMT-advanced in Korean mobile communication environments. ETRI Journal, 29, 153–161. CrossRef
- Enabling remote-control for the power sub-stations over LTE-A networks
MHD Nour Hindia
Mohammad B. Majed
Tharek Abd Rahman
Iraj S. Amiri
- Springer US
- Telecommunication Systems
Modelling, Analysis, Design and Management
Print ISSN: 1018-4864
Elektronische ISSN: 1572-9451