i-manager Publications

i-manager's Journal on Wireless Communication Networks (JWCN)

Current Issue Vol. 13 Issue 1

Most Cited

A Review on Optimized FFT/IFFT Architectures for OFDM Systems
Balanced Unequal Clustering AlgorithmFor Wireless Sensor Network
HHT and DWT Based MIMO-OFDM for Various ModulationSchemes: A Comparative Approach
Study and Comparison of Distributed Energy Efficient Clustering Protocols in Wireless Sensor Network: A Review
Diagnosis of Anemia using Non-Invasive Anemia Detector through Parametrical Analysis

Volume 3 Issue 4 January - March 2015

Research Paper

Performance Analysis of Large MIMO-OFDM systems with Beam Forming and Maximal Ratio Combining in Rayleigh Fading Channel

Vaibhav S. Hendre* , Suvarna P. Jadhav, M. Murugan*

* Research Scholar, Electronics Engineering Department of Sathyabama University, Chennai, India

Professor, Head and Vice Principal of SRM's Valliammai Engineering College, Kattankulathur, Chennai, India.

* PG Scholar, Department of Electronics & Telecommunication Engineering, Trinity College of Engineering & Research, University of Pune, India

Hendre, V.S., Jadhav, S.P., and Murugan, M. (2015). Performance Analysis of Large MIMO-OFDM systems with Beam Forming and Maximum Ratio Combining in Rayleigh Fading Channel. i-manager's Journal on Wireless Communication Networks, 3(4), 1-7. https://doi.org/10.26634/jwcn.3.4.3173

Abstract

Multiple Input Multiple Output (MIMO) technology has important role in wireless communication systems; because it offers significant increase in data rate and link range without additional transmit power. The conventional MIMO uses 2 to 4 antennas per terminal. In order to achieve high spectral efficiency, the concept of large –MIMO is emerging. The implementation of large-MIMO undergoes complex process at receiver end in estimation and detection. The several aspects of wireless communication based feedback with multiple antennas, such as the estimation of the Channel State Information (CSI), the quantization of the CSI with a finite number of bits to enable its feedback and effect of errors in the feedback channel on the performance of the communication system are need to be considered. In this paper, the Ergodic Channel capacity calculations for large-MIMO are presented. The Bit Error Rate (BER) analysis is carried out for different modulation techniques using OFDM for the case of Multiple Input Single Output (MISO) systems using beam forming technique and for the Single Input Multiple Output (SIMO) system using Maximal Ratio Combining (MRC) technique.

References

[1]. Juan M. Romero, Juan P. Martin and Andrea J. Goldsmith , (2009). “Bit Error Rate Analysis in MIMO Channels with Fading and Interference”, IEEE Vehicular Tech. Conf., pp. 1-5. [2]. Wei Yang et al, (2013). “On the Capacity of Large- MIMO Block-Fading Channels”, IEEE Journal on Selected Areas in Communications, Vol. 31, No.2, pp. 117-132, [3]. Yong Soo Cho et al, (2010). “MIMO-OFDM Wireless Communications with MATLAB”, John Wiley & Sons (Asia) Pte Ltd., [4]. Muhammad Sana Ullah and Mohammad Jashim Uddin, (2011). “Performance Analysis of Wireless MIMO System by Using Alamouti's Scheme and Maximal Ratio Combining Technique” Int. J. of Adv. Engg Sci. and Techno. Vol. 08, No. 1, pp.19-24. [5]. Suvarna P. Jadhav, V. S.Hendre, (2013). “Performance of Maximal ratio combining (MRC) in MIMO Systems for Raleigh Fading Channel” Int. J. of Scientific and Research Puplications, Vol. 3, No. 2. [6]. David J. Love and Robert W. Heath, (2003). “Equal Gain Transmission in Multiple-Input Multiple-Output Wireless Systems”, IEEE Trans, on Commun., Vol. 51, No. 9, pp. 1-9. [7]. Shang-Ho Tsai, (2011). “An Equal Gain Transmission in MIMO Wireless Communications” IEEE Trans. on Wireless Commun., Vol. 10, No. 5, pp.1470-1479. [8]. Seok-Hwan Park, Heunchul Lee, Sang-Rim Lee and Inkyu Lee, (2007). “Low-Complexity Transmit Beamforming for MIMO Systems” IEEE Vehicular Tech. Conf., pp. 462-466. [9]. David J. Love, Robert W. Heath and Thomas Strohmer , (2003). “Grassmannian Beamforming for Multiple- InputMultiple-Output Wireless Systems”, IEEE Trans. on Information Theory, Vol. 49, No.10, pp.2735-2743. [10] Riera-Palou, F and Femenias, G., (2010). “Adaptive Frequency Diversity in MIMO-OFDM Systems based on Sopatial Multiplexing”, IEEE Int. Sympo. on Wireless Communication Systems, NewYork, pp.86-90. [11]. Poongodi. C, Ramya P. and Shanmugam. A, (2010). “BER Analysis of MIMO-OFDM System using M-QAM over rayleigh Fading Channel ”, IEEE Int. Conf. on Communication and Computational Inteligence, pp. 284-288. [12]. Sheng-Chou Lin, (2011). “Performance analysis for optimum transmission and comparison with maximal ratio transmission for MIMO systems with cochannel inter ference” Lin EURASIP Journal on Wireless Communications and Networking. [13]. Georgy Levin, (2008). “Capacity Analysis of Asymptoticaly Large MIMO Channels”, Ph.D. dessertation, University of Ottawa.

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Research Paper

Energy Efficient Data Aggregation Using Packet Driven Timing Algorithm In Wireless Sensor Network

G. Kalaiselvi* , M. Jenora**

*-** PG Scholar, Department of CSE, Govt. College of Engineering, Tirunelveli, India.

Kalaiselvi, G., and Jenora, M. (2015). Energy Efficient Data Aggregation Using Packet Driven Timing Algorithm In Wireless Sensor Network. i-manager's Journal on Wireless Communication Networks, 3(4), 8-13. https://doi.org/10.26634/jwcn.3.4.3174

Abstract

Energy in Wireless Sensor Networks (WSNs) is quite limited. Since sensor nodes are usually much dense, data sampled by sensor nodes have much redundancy, data aggregation becomes an effective method to eliminate redundancy, minimize the number of transmission, and then to save energy. Many applications can be deployed in WSNs and various sensors are embedded in nodes, the packets generated by heterogeneous sensors or different applications have different attributes. The packets from different applications cannot be aggregated. Otherwise, most data aggregation schemes employ static routing protocols, which cannot dynamically or intentionally forward packets according to network state or packet types. The spatial isolation caused by static routing protocol is unfavourable to data aggregation. To make data aggregation more efficient, in this paper, the authors introduce the concept of packet attribute, and then propose an Attribute-aware Data Aggregation (ADA) scheme consisting of a packet-driven timing algorithm and a special dynamic routing protocol. Inspired by the concept of potential in physics and pheromone in ant colony, a potential-based dynamic routing is elaborated to support an ADA strategy.

References

[1]. R.Szewczyk, A.Mainwaring, J.Polaster, and D. Culler, (2004). “An Analysis of a Large Scale Habitat Monitoring Application, ”Proc. ACM Int'l Conf. Embedded Networked Sensor Systems(SenSys). [2]. Q. Fang, F. Zhao, and L. Guibas, (2003). “Lightweight Sensing and Communication Protocols for Target Enumeration and Aggregation, ”Proc. Fourth Int'l ACM Symp. Mobile Ad Hoc Networking and Computing, [3]. D.L. Hall and J. Llinas, (1997). “An Introduction to Multisensor Data Fusion, ” Proc. IEEE, Vol. 85, No. 1, pp. 6-23. [4]. T. Clouqueur, K.K. Saluja, and P. Ramanathan, (2004). “Fault Tolerance in Collaborative Sensor Networks for Target Detection,” IEEE Trans. Computer, Vol. 53, No. 2, pp. 320- 333. [5]. X. Sheng and Y.H. Hu, (2003). “Energy Based Acoustic Source Localization”, Proc. IEEE Int'l Conf. Information Processing in Sensor Networks, pp. 285-300. [6]. M. Duarte and Y.H. Hu, (2004). “Vehicle Classification in istributed Sensor Networks,” J. Parallel and Distributed Computing, Vol. 64, No. 7, pp. 826-838. [7]. J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D.Estrin, and D. Ganesan, (2001). “Building Efficient Wireless Sensor Networks with Low-Level Naming,” Proc. ACM Symp. Operating Systems Principles, pp. 146- 159, [8]. W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, (2002). “Application-Specific Protocol Architecture for Wireless Networks, ”IEEE Trans. Wireless Comm., Vol. 1, No. 4, pp. 660-670. [9]. S. Lindsey, C. Raghavendra, and K.M. Sivalingam, (2013). “Data Gathering Algorithms in Sensor Networks Using Energy Metrics, ”IEEE Trans. Parallel and Distributed Systems, Vol. 13, No. 9, pp. 924-935, 890. [10]. O. Younis and S. Fahmy, (2004). “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor networks, ”IEEE Trans. Mobile Computing, Vol. 3, No. 4, pp. 366-379. [11]. M. Ding, X. Cheng, and G. Xue, (2003). “Aggregation Tree n Construction in Sensor Networks,” Proc. IEEE 58th Vehicular Technology Conf.,pp. 2168-2172. [12]. H.O. Tan and I. Korpeoglu, (2003). “Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks,” SIGMOD Record, Vol. 32, No. 4, pp. 66-71. [13]. R. Cristescu, B. Beferull-Lozano, and M. Vetterli, (2004). “On Network Correlated Data Gathering,” Proc. IEEE INFOCOM, pp. 2571-2582. [14]. J. Li, A. Deshpande, and S. Khuller, (2010). “On Computing Compression Trees for Data Collection in Wireless Sensor Networks,” Proc. IEEE INFOCOM. [15]. W. Zhang and G. Cao, (2004). “DCTC: Dynamic Convoy Tree-based Collaboration for Target Tracking in Sensor Networks,” Ad Hoc and Sensor Wireless Networks, Vol. 3, pp. 1689-1701. [16]. Y.-K. Kim, R. Bista, and J.-W. Chang, (2009). “A Designated Path Scheme for Energy-Efficient Data Aggregation in Wireless Sensor Networks,” Proc. IEEE Int'l Symp. Parallel and Distributed Processing with Applications, pp. 408-415. [17]. K. Fan, S. Liu, and P. Sinha, (2006). “On the Potential of Structure-Free Data Aggregation in Sensor Networks,” Proc. IEEE INFOCOM, pp. 1-12. [18]. G. Theraulaz and E. Bonabeau, (1999). “A Brief History of Stigmergy, ”Artificial Life, Vol. 5, No. 2, pp. 97-116. [19]. C. Liu and G. Cao, (2010) “Distributed Monitoring and Aggregation in Wireless Sensor Networks,” Proc. IEEE INFOCOM. [20]. W. Pu, D. Rui, and I. Akyildiz,( 2010). “Collaborative Data Compression Using Clustered Source Coding for Wireless Multimedia Sensor Networks,” Proc. IEEE INFOCOM, pp. 1-9. [21]. S.J. Park and R. Sivakumar, (2008) “Energy Efficient Correlated Data Aggregation for Wireless Sensor Networks,” Int'l J. Distributed Sensor Networks, Vol. 4, No. 1, pp. 13-17.

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Research Paper

Efficient and Secure Routing Protocol forWireless Sensor Networks through SNRBased Dynamic Clustering Mechanisms

Thangaraj K* , R. Thirumalaiselvi**

* Research Scholar, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India.

** Assistant Professor, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India

Thangaraj, K., and Selvi, R.T. (2015). Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR Based Dynamic Clustering Mechanisms. i-manager's Journal on Wireless Communication Networks, 3(4), 14-22. https://doi.org/10.26634/jwcn.3.4.3175

Abstract

Advances in Wireless Sensor Network technology have enabled small and low-cost sensors with the capability of sensing various types of physical and environmental conditions, data processing, and wireless communication. In the Wireless Sensor Network (WSN), the sensor nodes have a limited transmission range and their processing and storage capabilities as well as their energy resources are limited. An efficient and secure routing protocol for Wireless Sensor Networks through SNR-based dynamic clustering mechanisms can partition the nodes into clusters and select the Cluster Head (CH) among the nodes based on the energy, and non CH nodes join with a specific CH based on the SNR values. The clustering technique is effective in prolonging the lifetime of the WSN [3]. Single cluster head in a cluster-based replication to improve the energy consumption rate, such as clustering, efficient routing, and data aggregation using Single Clustering head is used. The simulation result demonstrates that the dual cluster heads in distributed hash table replication can improve the performances of a replica manager with respect to updates propagation in comparison to that of a single cluster head in distributed hash table replication system. The authors assume that replicas refer to identical copies of a file and replica managers are those mobile nodes that hold one or multiple replicas. Replica managers accept query requests from other mobile nodes and reply with the requested files.

References

[1]. Akyildiz F (2005), “A Survey on Wireless Mesh Networks”, IEEE Radio Communications. [2]. Basagni S (1999), “Distributed clustering algorithm for ad-hoc networks,” in Proc. I-SPAN, pp. 310–315. [3]. Banerjee S and Khuller S (2001), “A clustering scheme for hierarchical control in multi-hop wireless networks,” in Proc. IEEE INFOCOM, Anchorage, pp. 1028–1037. [4]. Diwakar M and Kumar M, “Energy-efficient cluster- ing method for data gathering in sensor networks,”. [5]. Gwalani S (2003), AODV PA: AODV with path Accumulation, Communications. IEEE International Conference Volume 1, pp 11-15. [6]. Ganesh S and Amutha (1999), “Distributed clustering algorithm for ad-hoc networks,” in Proc. I-SPAN, pp. 310–315. [7]. Kamimura J, Wakamiya N and Murata M, (2004). “Energy-efficient clustering method for data gathering in sensor networks,” Proc of workshop on Broadband Advanced Sensor Net works, San Diego, Vol. 103, pp. 31- 36. [8]. Luke Klein-Berndt –Wireless Communications Technology group - A Quick Guide to AODV Routing, http://w3.antd.nist.gov/wctg/aodv_kernel/aodv_guide.pdf [9]. Perkins C.E., Belding-Royer E, Das S.R. (2003), “Ad-Hoc on Demand Distance Vector (AODV) routing” IETF RFC 3561. [10]. The Network Simulator (NS2). website, http://www.isi.edu/nsnam/ns/ns-build.html

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Research Paper

Balanced Unequal Clustering AlgorithmFor Wireless Sensor Network

G. Vennira Selvi* , R. Manoharan**

* Research Scholar, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India.

** Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India.

Selvi, G.V., and Manoharan, R. (2015). Balanced Unequal Clustering Algorithm For Wireless Sensor Network. i-manager's Journal on Wireless Communication Networks, 3(4), 23-29. https://doi.org/10.26634/jwcn.3.4.3180

Abstract

One of the important issues of WSN (Wireless Sensor Network) is efficient utilization of limited energy resources in the battery operated sensor node. Clustering provides an efficient method for utilizing the energy efficiently and balancing the energy consumption among the sensor nodes in the networks. Existing clustering algorithms select the Cluster Head with a high residual energy and rotate the Cluster Heads at regular intervals to distribute the energy consumption among the nodes .The responsibility of Cluster Head is to gather the data from the Cluster Members and then forwarding them to the BS. It spends more energy for rotating the Cluster Head at regular interval and gathering the data from the Cluster Members. However, the energy hole problem and imbalance of energy consumptions among the nodes are not avoided in clustering. To mitigate the energy hole problem and utilize the energy efficiently, the authors have proposed a Balanced Unequal Clustering Algorithm. The simulation results prove that our algorithm is more efficient and achieves more energy savings than LEACH and HEED.

References

[1]. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam,. and E. Cayirci, (2002). “A Survey on Sensor Networks”, Communications Magazine, Vol. 40, No. 8, pp. 102-114. [2]. O. Younis and S. Fahmy, (2004). “HEED: a hybrid, energy-efficient, distributed clustering approach for Ad hoc sensor networks,” IEEE Transactions onMobile Computing, Vol. 3, No. 4, pp. 366–379. [3]. M.J. Handy, M. Haas, D. Timmermann; (2002).“Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection”; http://www.vs.inf.ethz.ch/publ/se/ IEEE_MWCN2002.pdf. [4]. S.Lindsey and C.S. Raghavendra, (2002). “PEGASIS: Powerefficient gathering in sensor information systems,” in Proceedings of IEEE Aerospace Conference, Vol. 3, pp. 3- 1125–3-1130. [5]. Chen G, Li C, Ye M, Wu J. (2009). An unequal clusterbased routing protocol in wireless sensor networks. Wireless Networks Journal, Vol. 15, No. 2, pp. 193--207. [6]. Jiguo YU, Yingying QI, Guanghui Wang, (2011). An energy-driven unequal clustering protocol for wireless sensor networks, Control Theory Appl, Vol 9, No 1, pp 133- 139. DOI 10.1007/s11768-011-0232-y. [7]. Zheng Zeng-wei, Wu Zhao-hui and Lin Huai-zhong, (2004). “An event driven clustering routing algorithm for wireless sensor networks”, in the Proceedings of IEEE/RSJ. [8]. Otgonchimeg Buyanjargal, Youngmi Kwon, (2010). “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)”, Journal of Networks, Vol. 5, No. 8. [9]. K.T. Kim and H.Y. Youn.: ( PEACH: Proxy-Enable Adaptive Clustering Hierarchy for Wireless Sensor network: Proceeding of The 2005 International Conference On Wireless Network, pp. 52-57. [10]. Kyung Tae Kim and Hee Yong Youn, (2005). “Energy- Driven Adaptive Clustering Hierarchy (EDACH) for Wireless Sensor Networks”, IFIP International Federation for Information Processing, LNCS 3823, pp. 1098 – 1107. [11]. A. Manjeshwar and D. P. Agrswal, (2001). “TEEN: A Routing Protocol for Enhanced Efficient in Wireless Sensor th Networks,” in the Proceedings of the 15 International, Parallel and Distributed Processing Symposium, IEEE, pp. 2009-2015. [12]. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, (2002). “An Application-Specific Protocol Architecture for Wireless Microsensor Networks”, IEEE Transactions on Wireless Communications, Vol. 1, No. 4, pp. 660-670.

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Research Paper

Optimally Flexible Energy Conserving Protocol forConnectionless Oriented Systems

M. Revathy* , R. Kalaimagal**

* Research Scholar (M.Phil.), Department of Computer Science, Government Arts College for Men (Autonomous), Nandanam, Chennai, India.

** Assistant Professor, Department of Computer Science, Government Arts College for men, Nandanam, Chennai.

Revathy, M., and Kalaimagal, R. (2015). Optimally Flexible Energy Conserving Protocol for Connectionless Oriented Systems. i-manager's Journal on Wireless Communication Networks, 3(4), 30-35. https://doi.org/10.26634/jwcn.3.4.3182

Abstract

Quorum-based Power-Saving (QPS) protocols have been proposed for ad hoc networks (e.g., IEEE 802.11 ad hoc mode) to increase energy efficiency and prolong the operational time of mobile stations. These protocols assign to each station a cycle pattern that specifies when the station should wake up (to transmit/receive data) and sleep (to save battery power). In all existing QPS protocols, the cycle length is either identical for all stations or is restricted to certain numbers (e.g., squares or primes). These restrictions on cycle length severely limit the practical use of QPS protocols as each individual station may want to select a cycle length that is best suited for its own need (in terms of remaining battery power, tolerable packet delay, and drop ratio). In this paper, the authors have proposed the notion of Hyper Quorum System (HQS)—a generalization of QPS that allows for arbitrary cycle lengths. We describe algorithms to generate two different classes of HQS given any set of arbitrary cycle lengths as input. They have also described how to find the optimal cycle length for a station to maximize energy efficiency, subject to certain performance constraints. Then they have presented analytical and simulation results that show the benefits of HQS-based power-saving protocols over the existing QPS protocols. The HQS protocols yield up to 41% improvement in energy efficiency under heavy traffic loads while eliminating more than 90% delay drops under light traffic loads.

References

[1]. Shan-Hung Wu, Ming-Syan Chen, Chung-Min Chen, (2014). “Optimally Adaptive Power-Saving Protocols for Ad Hoc Networks Using the Hyper Quorum System” by, IEEE , ACM, Vol. 22, No. 1. [2]. M. Anand, E. Nightingale, and J. Flinn, (2005) “Selftuning wireless network power management”, Wireless Network, Vol. 11, No. 4, pp. 451–469. [3]. P. Bernstein, V. Hadzilacos, and N. Goodman, (1987). “Concurrency Control and Recovery in Database Systems”. Reading, MA, USA: Addison- Wesley. [4]. G. Bianchi, (2000). “Performance analysis of the IEEE 802.11 distributed coordination function,” IEEE J. Sel. Areas Commun., Vol. 18, No. 3, pp. 535–547. [5] C. Chao, J. Sheu, and I. Chou, (2006). “An adaptive quorum-based energy conserving protocol for IEEE 802.11 ad hoc networks,” IEEE Trans. Mobile Comput., Vol. 5, No. 5, pp. 560–570. [6]. B. Choi and X. Shen, (2011). “Adaptive asynchronous sleep scheduling protocols for delay tolerant networks,” IEEE Trans. Mobile Computing., Vol. 10, No. 9, pp. 1283–1296. [7]. Z. Chou, (2007), “Optimal adaptive power management protocols for asynchronous wireless ad hoc networks,” in Proc. IEEE WCNC, pp. 61–65. [8]. Y. Chow and H. Teicher, (2003) “Probability Theory: Independence, Interchangeability, Martingales”. New York, NY, USA: Springer-Verlag, ISBN- 13: 978-0387239606. [9]. D. Collins, (2003). “Carrier Grade Voice Over IP”. NewYork,NY,USA:Mc- Graw-Hill. [10]. I. L. S. Committee, (1999). “Wireless LAN medium access control and physical layer specifications,” [11]. “The Network Simulator (NS-2),” [Online]. Available: http://www.isi.edu/nsnam/ns [12]. Ms. S. Kanimozhi and Mrs. M. Parameswari (2014). “Performance Analysis of Quorum Based Power Saving Protocols for Ad hoc Networks” IJSRET ISSN 2278 – 0882 Volume 3, Issue 9. pp 1264-1268. [13]. Chiung-Ying Wang, Chi-Jen Wu, Guan Nan Chen, Ren-Hung Hwang (2005). “ p-MANET: Efficient Power Saving Protocol for Multi-Hop Mobile Ad Hoc Networks” IEEE, ISBN: 0-7695-2316-1, PP.271-276.

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Research Paper

Hierarchical Topology Control and Routing Problemin Cluster-Based Wireless Sensor Networks

M. Jenora* , G. Kalaiselvi, D. Anitha*

- P.G. Student, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India.

Assistant Professor, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India.

Jenora, M., Selvi, G.K., and Anitha, D. (2015). Hierarchical Topology Control and Routing Problem in Cluster-Based Wireless Sensor Networks. i-manager's Journal on Wireless Communication Networks, 3(4), 36-42. https://doi.org/10.26634/jwcn.3.4.3183

Abstract

Data-gathering Wireless Sensor Networks (WSNs) are operated unattended over long time horizons to collect data in several applications. Typically, sensors have limited energy (e.g., an on-board battery) and are subject to the elements in the terrain. In network operations, which largely involve periodically changing network flow decisions to prolong the network lifetime, are managed remotely, and the collected data are retrieved by a user via internet. An integrated topology control and routing problem in cluster-based WSNs are analyzed to improve the network lifetime. To prolong network lifetime via efficient use of the limited energy at the sensors , a hierarchical network structure with multiple sinks at which the data collected by the sensors are gathered through the cluster heads are adopted . A Mixed Integer Linear Programming (MILP) model to optimally determine the sink and CH locations as well as the data flow in the network is considered. This model effectively utilizes both the position and the energy-level aspects of the sensors while selecting the CHs and avoids the highest-energy sensors. For the solution of the MILP model, an effective Benders Decomposition (BD) approach that incorporates an upper bound heuristic algorithm is used.

References

[1]. W. B. Heinzelman, A. Chandrakasan, and H. Balakrishnan, (2000). “Energy efficient communication protocol for wireless micro-sensor networks,” in Proc. IEEE Hawaii Int. Conf. Syst. Sci., pp. 174–185. [2]. M. Liu, J. Cao, G. Chen, and X. Wang, (2009) “An energy-aware routing protocol in wireless sensor networks,” Sensors, Vol. 9, No. 1, pp. 445–462. [3]. Chang and L. Tassiulas, (2004). “Maximum lifetime routing in wireless sensor networks,” IEEE/ACM Trans. Netw., Vol. 12, No. 4, pp.609–619. [4]. W. Wang, V. Srinivasan, and K.-C. Chua, (2008). “Extending the lifetime of wireless sensor networks through mobile relays,” IEEE/ACM Trans.Netw., Vol. 16, No. 5, pp. 1108–1120. [5]. Y. Wu, Z. Mao, S. Fahmy, and N. B. Shroff, (2010). “Constructing maximum- lifetime data-gathering forests in sensor networks,” IEEE/ACM Trans. Netw., Vol. 18, No. 5, pp. 1571–1584. [6]. Y. Xue, Y. Cui, and K. Nahrstedt, (2005). “Maximizing lifetime for data aggregation in wireless sensor networks,” Mobile Netw. Appl., Vol. 10, pp. 853–864. [7]. F. Al-Turjman, H. Hassanein, and M. Ibnkahla, (2011). “Optimized relay repositioning for wireless sensor networks applied in environmental applications,”in Proc. 7th IWCMC, Jul. , pp. 1860–1864. [8]. M. Haenggi, (2003). “Energy-balancing strategies for wireless sensor networks,” in Proc. IEEE ISCAS, Bangkok, Thailand, pp. IV-828–IV-831. [9]. P. A. Ademola, (2011). N. A. A., and A. O. A. K. K. A., ANCAEE: “A novel clustering algorithmfor energy efficiency in ireless sensor networks, ”Wireless Sensor Netw., Vol. 3, No. 9, pp. 307–312.

i-manager's Journal on Wireless Communication Networks (JWCN)

Current Issue Vol. 13 Issue 1

Most Read

Most Cited

Volume 3 Issue 4 January - March 2015

Performance Analysis of Large MIMO-OFDM systems with Beam Forming and Maximal Ratio Combining in Rayleigh Fading Channel

Vaibhav S. Hendre* , Suvarna P. Jadhav**, M. Murugan***

Hendre, V.S., Jadhav, S.P., and Murugan, M. (2015). Performance Analysis of Large MIMO-OFDM systems with Beam Forming and Maximum Ratio Combining in Rayleigh Fading Channel. i-manager's Journal on Wireless Communication Networks, 3(4), 1-7. https://doi.org/10.26634/jwcn.3.4.3173

Abstract

References

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Energy Efficient Data Aggregation Using Packet Driven Timing Algorithm In Wireless Sensor Network

G. Kalaiselvi* , M. Jenora**

*-** PG Scholar, Department of CSE, Govt. College of Engineering, Tirunelveli, India.

Kalaiselvi, G., and Jenora, M. (2015). Energy Efficient Data Aggregation Using Packet Driven Timing Algorithm In Wireless Sensor Network. i-manager's Journal on Wireless Communication Networks, 3(4), 8-13. https://doi.org/10.26634/jwcn.3.4.3174

Abstract

References

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Efficient and Secure Routing Protocol forWireless Sensor Networks through SNRBased Dynamic Clustering Mechanisms

Thangaraj K* , R. Thirumalaiselvi**

* Research Scholar, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India. ** Assistant Professor, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India

Thangaraj, K., and Selvi, R.T. (2015). Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR Based Dynamic Clustering Mechanisms. i-manager's Journal on Wireless Communication Networks, 3(4), 14-22. https://doi.org/10.26634/jwcn.3.4.3175

Abstract

References

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Balanced Unequal Clustering AlgorithmFor Wireless Sensor Network

G. Vennira Selvi* , R. Manoharan**

* Research Scholar, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India. ** Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India.

Selvi, G.V., and Manoharan, R. (2015). Balanced Unequal Clustering Algorithm For Wireless Sensor Network. i-manager's Journal on Wireless Communication Networks, 3(4), 23-29. https://doi.org/10.26634/jwcn.3.4.3180

Abstract

References

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Optimally Flexible Energy Conserving Protocol forConnectionless Oriented Systems

M. Revathy* , R. Kalaimagal**

* Research Scholar (M.Phil.), Department of Computer Science, Government Arts College for Men (Autonomous), Nandanam, Chennai, India. ** Assistant Professor, Department of Computer Science, Government Arts College for men, Nandanam, Chennai.

Revathy, M., and Kalaimagal, R. (2015). Optimally Flexible Energy Conserving Protocol for Connectionless Oriented Systems. i-manager's Journal on Wireless Communication Networks, 3(4), 30-35. https://doi.org/10.26634/jwcn.3.4.3182

Abstract

References

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Hierarchical Topology Control and Routing Problemin Cluster-Based Wireless Sensor Networks

M. Jenora* , G. Kalaiselvi**, D. Anitha***

*-** P.G. Student, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India. *** Assistant Professor, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India.

Jenora, M., Selvi, G.K., and Anitha, D. (2015). Hierarchical Topology Control and Routing Problem in Cluster-Based Wireless Sensor Networks. i-manager's Journal on Wireless Communication Networks, 3(4), 36-42. https://doi.org/10.26634/jwcn.3.4.3183

Abstract

References

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Vaibhav S. Hendre* , Suvarna P. Jadhav, M. Murugan*

* Research Scholar, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India.

** Assistant Professor, Department Of Computer Science Govt.Arts College, Nandanam, Chennai, India

* Research Scholar, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India.

** Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India.

* Research Scholar (M.Phil.), Department of Computer Science, Government Arts College for Men (Autonomous), Nandanam, Chennai, India.

** Assistant Professor, Department of Computer Science, Government Arts College for men, Nandanam, Chennai.

M. Jenora* , G. Kalaiselvi, D. Anitha*

- P.G. Student, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India.

Assistant Professor, Department of Computer Engineering, Govt. College of Engineering, Tirunelveli, Tamilnadu, India.