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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 1 Issue 4 January - March 2013

Article

Application Of Live Streaming Video In Multimedia Technology

M. Saranya*

Assistant Professor, Karpaga Vinayaga College of Engineering and Technology, Tamil Nadu, India.

Saranya, M. (2013). Application Of Live Streaming Video In Multimedia Technology, i-manager’s Journal on Wireless Communication Networks. 1(4), 1-4. https://doi.org/10.26634/jwcn.1.4.2192

Abstract

Streaming video from the server is being an everlasting problem for all of us till now. The videos cannot be seen from the server so easily by the user. The user has to wait for the videos to buffer, which is the streaming process. If more than two persons are watching the same video at the same time, user may face so much of buffering problem, clarity in the video content also. The problem occurs because each individual user does not have their individual path to the server, which they use. This problem can be overcome by the concept of subway tunnel. “Subway tunnel” which means that a secondary path is created to the user from the server they use. So if the bandwidth of the user’s path cannot withstand with the content, the user can take the subway path to transfer the video content. Bit streaming method is used for streaming the video content from the server. This method helps us to stream the video content without any loss in the content of the video & quality. By this way the users (i.e., multiple users) can able to overcome the problem of streaming videos from the server.

References

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[2]. Borko Furht (2008). “Encyclopaedia of multimedia” France 2008.

[3]. Mark W. Curran “Sell your music! how to profitably sell your own recordings online”

[4]. WEI Jian-dong, (2006). “Automatic Deformation Monitoring System Based on Georobot,” Bulletin of Surveying and Mapping, 12, 2006, pp.41 -43.

[5]. Chang H.; Jamin, S.; Wang W.; Alcatel-Lucent Bell Labs, Holmdel, NJ, USA (2010). ”Live Streaming With Receiver-Based Peer Division Multiplexing Networking”, Proceeding of IEEE/ACM, AUGUST 2010.

[6]. LIU Shaotang, PAN Guorong, LIANG Yubao, LIAO Zhongping, and LI weixiao, (2009). “GIS-Based Tunnel Deformation Monitoring System”. Proceedings of the First International Workshop on Education Technology and Computer Science. Vol. 3. 7-8 March 2009, pp. 553-555.

[7]. LIU Shao-tang, XIAO Hai-wen and ZHAO Zhan-yang, (2007). “Deflection Monitoring of Box Girders of Hang-Zhou Bay Bridge,” Proceedings of the International Conference on Health Monitoring of Structure, Material and Environment, 2007.

[8]. Ou Jinping, (2003). “Some recent advances of intelligent health monitoring systems for civil infrastructures in mainland China,” Proc of the First International Conference on Structural Health monitoring and Intelligent Infrastructure. 2003, pp. 131-144.

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Research Paper

HARAQ-Routing Table for On-Chip Congestion Control

N. Swethapriyanka* , G. Rajesh**

*-** Associate Professor, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

Swethapriyanka, N., and Rajesh, G. (2013). Haraq-Routing Table For On-Chip Congestion Control, i-manager’s Journal on Wireless Communication Networks. 1(4), 5-11. https://doi.org/10.26634/jwcn.1.4.2188

Abstract

When the Message latency increases in Networks-On-Chip Performance of the channel decreases due to congestion. In Mesh topology, minimal methods can distribute messages over two directions at each switch, but in high traffic loads this methods are inefficient. We present a non-minimal methods can overcome this blocking problem in high traffic loads and reduce the waiting time of messages by delivering them via alternative paths called HARAQ.To avoid creating cycles in network, the algorithm define all allowed turns including 180-degree turns on a single channel. To select a less congestion path from output channel to the destination region based on local and global information in the learning method.

References

[1]. HARAQ: Congestion-Aware Learning Model for Highly Adaptive Routing Algorithm in On-chip Network

[2]. M. Daneshtalab, et al., “Memory-Efficient On-Chip Network with Adaptive Interfaces”, IEEE Transaction on Computer-Aided Design of Integrated Circuits and Systems, Vol. 31, No. 1, pp. 146-159, Jan 2012.

[3]. M. Dehyadegari, et al., “An Adaptive Fuzzy Logic-based Routing Algorithm for Networks-on-Chip,” in Proceedings of 13th IEEE/NASAESA International Conference on Adaptive Hardware and Systems (AHS), pp. 208-214, 2011.

[4]. G. Ascia, et al., “Implementation and Analysis of a New Selection Strategy for Adaptive Routing in Networks-on-Chip,” IEEE Transaction on Computers, v.57, I.6, pp. 809-820, 2008.

[5]. P. Gratz, et al., “Regional Congestion Awareness for Load Balance in Networks-on-Chip,” in Proc. HPCA, pp. 203-214, 2008.

[6]. S. Ma, et al., “DBAR: an efficient routing algorithm to support multiple concurrent applications in networks-on-chip”, in Proc. of ISCA, 2011, pp.413-424.

[7]. F. Chaix, et al., “A fault-tolerant deadlock-free adaptive routing for On Chip interconnects,” in Proc. of DATE, pp. 1-4, 2011.

[8]. Z. Zhang, et al., “A reconfigurable routing algorithm for a fault-tolerant 2d-mesh network-on-chip”, in Proc. of DAC, 2008.

[9]. S. Jovanovic, C. Tanougast, et al., “A New Deadlock-Free Fault-Tolerant Routing Algorithm For NoC Interconnections”, in Proc. of FPLA, pp.326- 331, 2009.

[10]. J. Wu and D. Wang, “Fault-tolerant And Deadlock-free Routing in 2-D Meshes Using Rectilinear-Monotone Polygonal Fault Blocks”, in Proc. Of parallel Algorithms Appl., pp.99-111, 2005.

[11]. D. Fick, A. DeOrio, et al., “A Highly Resilient Routing Algorithm for FaultTolerant NoCs”, in Proc. of DATE, pp. 21-26, 2009.

[12]. C. Feng, ,et al. “A reconfigurable fault-tolerant deflection routing algorithm based on reinforcement learning for network-on-chip”, in Proc. of NoCArc, pp.11-16 , 2010.

[13]. K.P. Fan, C.T. King, “Turn Grouping for Multicast in Wormhole-Routed Mesh Networks Supporting the Turn Model”, Journal of Supercomputing, V.16, No.3, pp. 237-260, 2000.

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Research Paper

Minimum Spanning Tree based Protocol for Heterogeneous Wireless Sensor Networks

Gaurav Bathla*

Department of Computer Science and Engg., Thapar University, Patiala.

Bathla, G. (2013). Minimum Spanning Tree Based Protocol For Heterogeneous Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 1(4), 12-23. https://doi.org/10.26634/jwcn.1.4.2189

Abstract

Potential use of wireless sensor networks (WSNs) can be seen in various fields like disaster management, battle field surveillance and border security surveillance since last few years. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but some nodes may be of different energy to prolong the lifetime of a WSN and its reliability. In this paper an attempt is made to calculate energy required for all the nodes to be placed in the network in the same structure as was defined under MSMTP protocol in bottom up fashion i.e. energy of all nodes is initialized to zero & after each round transmission & receiving energy required is added to energy of each node. After completing certain number of rounds required energy of each node can be deduced.

References

[1]. Abbasi, A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer communications , 30 (14), 2826--2841.

[2]. Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad hoc networks , 3 (3), 325--349.

[3]. Akyildiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer networks , 38 (4), 393--422.

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[5]. Bathla, G., & Khan, G. (2011). Energy-Efficient Routing Protocol for Homogeneous Wireless Sensor Networks. International Journal on Cloud Computing: Services and Architecture (IJCCSA) , 1 (1).

[6]. Bokareva, T., Hu, W., Kanhere, S., Ristic, B., Gordon, N., Bessell, T., et al. (2006). Wireless sensor networks for battlefield surveillance. Proceedings of the land warfare conference.

[7]. Corchado, J., Bajo, J., Tapia, D., & Abraham, A. (2010). Using heterogeneous wireless sensor networks in a telemonitoring system for healthcare. Information Technology in Biomedicine, IEEE Transactions on , 14 (2), 234--240.

[8]. Dasgupta, K., Kalpakis, K., & Namjoshi, P. (2003). An efficient clustering-based heuristic for data gathering and aggregation in sensor networks. Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE, 3, pp. 1948--1953.

[9]. de Freitas, E., Heimfarth, T., Pereira, C., Ferreira, A., Wagner, F., & Larsson, T. (2009). Evaluation of coordination strategies for heterogeneous sensor networks aiming at surveillance applications. Sensors, 2009 IEEE, (pp. 591--596).

[10]. Duan, C., & Fan, H. (2007). A distributed energy balance clustering protocol for heterogeneous wireless sensor networks. Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on, (pp. 2469--2473).

[11]. Duarte-Melo, E., & Liu, M. (2002). Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks. Global Telecommunications Conference, 2002. GLOBECOM'02. IEEE, 1, pp. 21--25.

[12]. Elbhiri, B., Saadane, R., & Aboutajdine, D. (n.d.). Stochastic Distributed Energy-E cient Clustering (SDEEC) for heterogeneous wireless sensor networks.

[13]. Gupta, G., & Younis, M. (2003). Fault-tolerant clustering of wireless sensor networks. Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE, 3, pp. 1579--1584.

[14]. Gupta, G., & Younis, M. (2003). Load-balanced clustering of wireless sensor networks. Communications, 2003. ICC'03. IEEE International Conference on, 3, pp. 1848--1852.

[15]. Hart, J., & Martinez, K. (2006). Environmental Sensor Networks: A revolution in the earth system science? Earth-Science Reviews , 78 (3), 177--191.

[16]. Heinzelman, W., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on, (pp. 10--pp).

[17]. Hou, Y., Shi, Y., Sherali, H., & Midkiff, S. (2005). On energy provisioning and relay node placement for wireless sensor networks. Wireless Communications, IEEE Transactions on , 4 (5), 2579--2590.

[18]. Kumar, D., Aseri, T., & Patel, R. (2009). Analysis on deployment cost and network performance for heterogeneous wireless sensor networks. International Journal of Computer science and Information Technology (IJCSIT). v1 i2 .

[19]. Kumar, D., Aseri, T., & Patel, R. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications , 32 (4), 662--667.

[20]. Li, X. et.al. (2007). A Routing Protocol for Balancing Energy Consumption in Heterogeneous Wireless Sensor Networks. In Mobile Ad-Hoc and Sensor Networks (Vol. 4864, pp. 79-88). Springer Berlin Heidelberg.

[21]. Liang, Y., & Feng, Y. (2009). An Energy-Aware Routing Algorithm for Heterogeneous Wireless Sensor Networks. Hybrid Intelligent Systems, 2009. HIS'09. Ninth International Conference on, 2, pp. 275--278.

[22]. Lindsey, S., & Raghavendra, C. (2002). PEGASIS: Power-efficient gathering in sensor information systems. Aerospace conference proceedings, 2002. IEEE, 3, pp. 3--1125.

[23]. Lu, K., Qian, Y., & Hu, J. (2006). A framework for distributed key management schemes in heterogeneous wireless sensor networks. Performance, Computing, and Communications Conference, 2006. IPCCC 2006. 25th IEEE International, (pp. 7--pp).

[24]. Lu, X., Spear, M., Levitt, K., & Wu, S. (2008). ibubble: Multi-keyword routing protocol for heterogeneous wireless sensor networks. INFOCOM 2008. The 27th Conference on Computer Communications. IEEE, (pp. 968--976).

[25]. Manjeshwar, A., & Agrawal, D. (2002). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. Proceedings of the 16th International Parallel and Distributed Processing Symposium, (p. 48).

[26]. Manjeshwar, A., & Agrawal, D. (2001). TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. Proceedings of the 15th International Parallel \& Distributed Processing Symposium, (p. 189).

[27]. Marin-Perianu, R., Scholten, J., Havinga, P., & Hartel, P. (2008). Cluster-based service discovery for heterogeneous wireless sensor networks. International Journal of Parallel, Emergent and Distributed Systems , 23 (4), 325--346.

[28]. Paruchuri, V., Durresi, A., & Barolli, L. (2005). Energy aware routing protocol for heterogeneous wireless sensor networks. Database and Expert Systems Applications, 2005. Proceedings. Sixteenth International Workshop on, (pp. 133--137).

[29]. Qing, L., Zhu, Q., & Wang, M. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer communications , 29 (12), 2230--2237.

[30]. R. Shorey, A. A. (2006). Mobile, Wireless snd sensor networks. IEEE Press, John Wiley & Sons.

[31]. R?mer, K., Kasten, O., & Mattern, F. (2002). Middleware challenges for wireless sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review, 6 (4), 59--61.

[32]. Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks.

[33]. Varma, S., Nigam, N., & Tiwary, U. (2008). Base station initiated dynamic routing protocol for Heterogeneous Wireless Sensor Network using clustering. Wireless Communication and Sensor Networks, 2008. WCSN 2008. Fourth International Conference on, (pp. 1--6).

[34]. Wu, C.-H., & Chung, Y.-C. (2007). Heterogeneous wireless sensor network deployment and topology control based on irregular sensor model. Springer.

[35]. Xiaoya, L., Daoping, H., & Jian, Y. (2007). Energy efficient routing protocol based on residual energy and energy consumption rate for heterogeneous wireless sensor networks. Control Conference, 2007. CCC 2007. Chinese, (pp. 587--590).

[36]. Yarvis, M., Kushalnagar, N., Singh, H., Rangarajan, A., Liu, Y., & Singh, S. (2005). Exploiting heterogeneity in sensor networks. INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE, 2, pp. 878--890.

[37]. Younis, M., Youssef, M., & Arisha, K. (2003). Energy-aware management for cluster-based sensor networks. Computer Networks , 43 (5), 649--668.

[38]. Yu, L., Wang, N., Zhang, W., & Zheng, C. (2007). Deploying a heterogeneous wireless sensor network. Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on, (pp. 2588--2591).

[39]. Zhou, H., Wu, Y., Hu, Y., & Xie, G. (2010). A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks. Computer Communications , 33 (15), 1843--1849.

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Research Paper

Bit Error Rate (BER) performance analysis of DSSS-FEC coherent and non-coherent MFSK under Rayleigh and Rician fading channels

T.A. Shanmugasundaram* , Alamelu Nachiappan**

* Research Scholar, Sathyabama University, Chennai, India.

** Associate Professor, Pondicherry Engineering College, Pondicherry, India.

Shanmugasundaram, T.A., and Nachiappan, A. (2013). Bit Error Rate (BER) Performance Analysis Of DSSS-FEC Coherent And Non-Coherent MFSK Under Rayleigh And Rician Fading Channels , i-manager’s Journal on Wireless Communication Networks. 1(4), 24-29. https://doi.org/10.26634/jwcn.1.4.2191

Abstract

Forward Error Correction is an efficient technique to correct, preferably burst errors, caused over several blocks of transmitted data. Besides this, narrowband interference (NBI) is an unavoidable major cause for transmission errors in wireless communication, which is much severe in unlicensed band like ISM band. It is needed to spread the encoded data before being modulated to overcome both burst errors and interference. Direct Sequence Spread Spectrum (DSSS) is a good support for wireless networks with nodes preferred to consume less power due to its less implementation complexity. This paper is the simulated comparative analysis of BER performance of FEC coded coherent and non-coherent M-ary FSK under the impact of both Rayleigh and Rician fading channels. BCH, RS, Cyclic and Linear Block codes are used in this simulation. Simulation results show that, RS Encoder – Decoder pair gives good BER performance over Rayleigh fading channel, especially with integer inputs and its performance should be enhanced for Rician fading channel.

References

[1]. Massoud Malek, (1998). “Coding Theory - Bose-Chaudhuri- Hocquengham (BCH) Codes”, www.mcs.csueastbay.edu/~malek/Class/Bch.pdf?.

[2]. Jack Keil Wolf, (1998). “An Introduction to Reed-Solomon Codes”, www.ece.tamu.edu/~hpfister/courses/ ecen604/rspoly.pdf?.

[3]. R.M. Buehrer, (2010). “Classification of Forward Error Correction Codes” IEEE Globecom 2010.

[4]. Ling-Pei Kung, “Introduction to Error Correcting Codes”, pubs.media.mit.edu/pubs/papers/ecc.pdf.

[5]. Sanjeev Kumar, Ragini Gupta, (2011). “Performance Comparison of Different Forward Error Correction Coding Techniques for Wireless Communication Systems”, IJCST Vol. 2, Issue 3, September 2011.

[6]. Sudhir Kumar Sunkara, (2005). “Performance of Coherent Direct Sequence Spread Spectrum Frequency Shift Keying”, Master's Thesis, November 2005.

[7]. Hongxiang Li, (2004). “Performance of multi tone direct sequence spread spectrum in the presence of imperfect carrier synchronization”, Master's Thesis, August 2004.

[8]. Guillermo Fernández S., Adolfo Espinoza P., (2001). “Direct Sequence and Frequency Hopping Spread Spectrum Systems, understanding differences between both schemes”, www.ingeborda.com.ar/biblioteca/ Biblioteca%20Internet/.../ID008.pdf?.

[9]. Erol Seke. “Spread Spectrum”, www2.ogu.edu.tr/~eseke/com/DC_SS.pdf?.

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Research Paper

Balanced Energy Consumption Approach For Deployment Of Clusters In A WSN

Debajyoti Pal*

Assistant Professor, Camellia Institute of Technology, Kolkata, India.

Pal, D. (2013). Balanced Energy Consumption Approach For Deployment Of Clusters In A WSN, i-manager’s Journal on Wireless Communication Networks. 1(4), 30-34. https://doi.org/10.26634/jwcn.1.4.2190

Abstract

In this paper we aim to deploy the clusters of a Wireless Sensor Network in such a way so that it leads to a balanced energy consumption. First, we discuss about the radio energy dissipation model [1] that is already in place and the corresponding protocols which are used. Thereafter, we focus on the protocols which are already in practice in such a system, outlining their major disadvantages. Later on, we propose a methodology/algorithm that improves the overall energy consumption which is supported by the results of the experiments carried out by the simulations. Finally, a comparative analysis is done over the results obtained by our algorithm and those which existed previously.

References

[1]. Zahariev, Plamen Z., Georgi V. Hristov, and Ivanka D. Tsvetkova. (2012). "An approach towards balanced energy consumption in hierarchical cluster-based wireless sensor networks." Information Technology Interfaces (ITI), Proceedings of the ITI 2012 34th International Conference on. IEEE, 2012.

[2]. G. Samarakdakis, I. Matta, A. Bestavros, Sep: (2004). A Stable Election Protocol For heterogeneous Wireless Sensor Networks, Proc of Int'l Workshop on SANPA, 2004.

[3]. Wang, Wei, (2011). et al. "A balanced energy consumption solution for wireless sensor networks with failure clusters." Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on. Vol. 4. IEEE, 2011.

[4]. W. Heizelman, A. Chandrakasan, H. Balakrishnan, (2000). Energy Efficient Communication Protocol for Wireless Microsensor Networks, Proc of the 33rd Hawaii International Conference on System Sciences (HICSS-33), 2000.

[5]. Kochhal, Manish, Loren Schwiebert, and Sandeep Gupta. (2003). "Role-based hierarchical self organization for wireless ad hoc sensor networks." Proc of the 2nd ACM international conference on Wireless sensor networks and applications. ACM, 2003.

[6]. Marcelloni, Francesco, and Massimo Vecchio. (2010). "Enabling energy-efficient and lossy-aware data compression in wireless sensor networks by multi-objective evolutionary optimization." Information Sciences 180.10 (2010): 1924-1941.

[7]. El Hajj, Wasim, and Dionysios Adviser-Kountanis. (2006). A distributed hierarchical energy-efficient scheme for large scale mobile wireless ad hoc networks. Western Michigan University, 2006.

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

Current Issue Vol. 13 Issue 1

Most Read

Most Cited

Volume 1 Issue 4 January - March 2013

Application Of Live Streaming Video In Multimedia Technology

M. Saranya*

Assistant Professor, Karpaga Vinayaga College of Engineering and Technology, Tamil Nadu, India.

Saranya, M. (2013). Application Of Live Streaming Video In Multimedia Technology, i-manager’s Journal on Wireless Communication Networks. 1(4), 1-4. https://doi.org/10.26634/jwcn.1.4.2192

Abstract

References

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HARAQ-Routing Table for On-Chip Congestion Control

N. Swethapriyanka* , G. Rajesh**

*-** Associate Professor, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

Swethapriyanka, N., and Rajesh, G. (2013). Haraq-Routing Table For On-Chip Congestion Control, i-manager’s Journal on Wireless Communication Networks. 1(4), 5-11. https://doi.org/10.26634/jwcn.1.4.2188

Abstract

References

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Minimum Spanning Tree based Protocol for Heterogeneous Wireless Sensor Networks

Gaurav Bathla*

Department of Computer Science and Engg., Thapar University, Patiala.

Bathla, G. (2013). Minimum Spanning Tree Based Protocol For Heterogeneous Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 1(4), 12-23. https://doi.org/10.26634/jwcn.1.4.2189

Abstract

References

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Bit Error Rate (BER) performance analysis of DSSS-FEC coherent and non-coherent MFSK under Rayleigh and Rician fading channels

T.A. Shanmugasundaram* , Alamelu Nachiappan**

* Research Scholar, Sathyabama University, Chennai, India. ** Associate Professor, Pondicherry Engineering College, Pondicherry, India.

Shanmugasundaram, T.A., and Nachiappan, A. (2013). Bit Error Rate (BER) Performance Analysis Of DSSS-FEC Coherent And Non-Coherent MFSK Under Rayleigh And Rician Fading Channels , i-manager’s Journal on Wireless Communication Networks. 1(4), 24-29. https://doi.org/10.26634/jwcn.1.4.2191

Abstract

References

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Balanced Energy Consumption Approach For Deployment Of Clusters In A WSN

Debajyoti Pal*

Assistant Professor, Camellia Institute of Technology, Kolkata, India.

Pal, D. (2013). Balanced Energy Consumption Approach For Deployment Of Clusters In A WSN, i-manager’s Journal on Wireless Communication Networks. 1(4), 30-34. https://doi.org/10.26634/jwcn.1.4.2190

Abstract

References

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* Research Scholar, Sathyabama University, Chennai, India.

** Associate Professor, Pondicherry Engineering College, Pondicherry, India.