i-manager Publications

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

Current Issue Vol. 12 Issue 1

5G Wireless Communication Systems: Performance Analysis and Optimization using Massive MIMO Technology
Performance Optimization of 5G NR Technology for Industrial Automation
A Comparative Analysis of SDON and Traditional Optical Networks in Elastic Optical Environments
A Review of Techniques for Minimizing Energy Consumption and Enhancing Lifespan in Wireless Sensor Networks
NodeMCU and Wireless Sensor Networks in Agriculture: A Review of Environmental Parameter Sensing

Most Cited

Volume 2 Issue 3 October - December 2013

Research Paper

Cooperative Spectrum Sharing Protocol with Selective Relay System in Cognitive Radio Network

N. Elayabharathi* , M.Poonguzhali, B. Pradeep Raja*, K.Yalini****

--Department of ECE, Narasu's Sarathy Institute of Technology, Salem

Department of ECE, College of Engineering, Anna University, Chennai.

Elayabharathi, N., Raja, B.P., Yalini, K., and Poonguzhali, M. (2013). Cooperative Spectrum Sharing Protocol with selective Relay System in Cognitive Radio Network, i-manager’s Journal on Wireless Communication Networks. 2(3), 1-7. https://doi.org/10.26634/jwcn.2.3.2553

Abstract

Cognitive Radio Network (CRN) and Cooperative Communication provides a new environment in wireless network which can effectively improve the spectrum efficiency of future wireless network. In this paper, a two phase protocol based cooperative relaying for a secondary user along with decode-and-forward (DF) and amplify-and-forward (AF) relaying system is proposed. In the proposed protocol, a dynamic queuing algorithm is used to access and manage the spectrum from a Primary User (PU) to the Secondary Users (SU) without any conflicts between the cognitive users (CR) or Secondary Users (SU) for accessing the same available spectrum. A Multi Behaviour Node System (MBNS) is used to achieve better outage performance for the secondary system when it fails from a relay selection. The proposed scheme achieves the effective spectrum sharing and hence the overall system performance is improved. The simulation result shows the improvement over DF and AF relaying system.

References

[1]. K.B. letaief and W.Zhang, (2009). “Cooperative Communication for Cognitive radio networks,” Proc. IEEE, Vol. 97, No.5, app. 878-893, May.

[2]. IamF.Akyildiz*, Won-yeol Lee, Kaushik R. Chowdhury (2007). Broadband wireless Networking Laboratory, School of Electrical and computer Enginnering, Georgia Institute of Technology, Atlanta, GA 30332, United States.

[3]. I.F. Akyildiz, W.-Y. Lee, .C. vurun, M. Shantidev, (2006). Next generation/dynamic spectrum access/ Cognitive radio wireless networks: a survey, Computer Networks Journal (Elsevier), 50 2127-2159.

[4]. S. Haykin, (2005). Cognitive radio: brain-empowered wireless communications, IEEE Journal on selected areas in communications, 23 (2), 201-220.

[ [5]. Xiaowen Gong, ChandrashekharThejaswi PS, Junshan Zhang, and H. Vincent Poor: (2012). Opportunistic Cooperative Networking: To Relay or Not To Relay? IEEE Journal on Selected Areas in Communications, Vol. 30, No. 2, February.

[6]. DonglinHu, Shiwen and Mao (2010). - Dept. ECE, Auburn University, Auburn: Cooperative Relay in Cognitive Radio Networks: Decode-and-Forward or Amplify-and- Forward?AL 36849-5201, IEEE Communications Society subject matter experts for publication in IEEE Globecom.

[7]. A. Sendonaris, E. Erkip, and B. Aazhang, (2003). “User Cooperation Diversity PartI: System Description,” IEEE Transactions on Communications, Vol. 51, No. 11, Nov.

[8]. R. Mahapatra, (2009). “Energy Consumption Analysis in Link Adaptive Cognitive Radio Network,” Proc. IEEE International Symposium on Advanced Networks and Telecommunication Systems.

[9]. J. N. Laneman, D. N. C. Tse, and G. W. Wornell, ( “Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior,” IEEE Trans. Inform. Theory, Vol. 50, No. 12, pp. 3062-3080, Dec.

10]. Liu, Y.X., D. Zhang and S. Guan, (2010). An efficient power allocation algorithm for relay assisted cognitive radio network. Proceedings of International Conference on Wireless Communications.

[11]. M. Naeem, K. Illanko, Ashok K. Karmokar, A. Anpalagan and M. Jaseemuddin (2013). in Decode and Forward Relaying for Green Cooperative Cognitive Radio Systems. IEEE Wireless Communications and Network Conference.

[12]. Zhang Y, Xu Y Y, Cai Y M. (2009). Power allocation for non-orthogonal decode-and-forward cooperation protocol, Sci China Ser F-InfSci, 52: 1037–1042.

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Research Paper

Mobile- Microcontroller Based Wireless Communication For The Control Of Appliances Integrated With Their Automation

K.V.N. Kavitha* , Shashank Chaurasia**

*-** School of Electronics Engineering, VIT University, Vellore, India.

Kavitha, K.V.N., and Chaurasia, S. (2013). Mobile- Microcontroller Based Wireless Communication For The Control Of Appliances Integrated With Their Automation, i-manager’s Journal on Wireless Communication Networks. 2(3), 8-13. https://doi.org/10.26634/jwcn.2.3.2554

Abstract

System designed here is for automation of home appliances using Dual Tone Multi Frequency (DTMF) technology. This also aims at providing an interfered and continuous control over many household devices. The user module has many buttons, each referring to the device that needs activation. An encoder (i.e. the transmitter phone) encodes the required information and transmits with the help of a FM transmitter. The FM receiver (i.e. receiver phone) receives the modulated signal and demodulates it using a demodulator and the required information is determined by the DTMF decoder. Following this method the required action is achieved. Such a system is very useful in this busy modern world, where everything is being sought for automation. Also included here, is a microcontroller based counter to count the number of people in a room and accordingly alter the lighting arrangements in the room. This satisfies the continuous need for automation of appliances in today’s tech-savvy world. Also this circuit proves to be of great help if one wants to know the number of people present in a room in order to avoid congestion.

References

[1]. Dhananjay Gadre, (2000). “Programming and Customizing the AVR Microcontroller”, McGraw-Hill, 2000.

[2]. Muhammad Ali Mazidi, “AVR Microcontroller and Embedded Systems: Using Assembly and C”, Pearson Education.

[3]. Rahat Ali Khan Langah, Asad Ali Shailkh, “DTMF Pager System: The Upcoming Technology”

[4]. Armando Roy Delgado, Rich Picking and Vic Grout Centre for Applied Internet Research (CAIR), University of Wales, NEWI, Wrexham, “Home Automation Systems with Different Network Technologies”.

[5]. Renato Jorge Caleira Nunes, IST – Technical University of Lisbon / INESC-ID, “Home Automation - A Step towards Better Energy Management.”

[6]. Yun Chan Cho and Jae Wook Jeon, (2008). “Remote Robot control System based on DTMF of Mobile Phone” IEEE International Conference INDIN 2008, July 2008.

[7]. Faisal Baig, Saira Beg and Muhammad Fahad Khan, (2013). ”Zigbee Based Home Appliances Controlling Through Spoken Commands Using Handheld Devices” Federal Urdu University of Arts, Science and Technology, Islamabad, Pakistan, International Journal of Smart Home Vol. 7, No. 1, January, 2013.

[8]. Prof. M. B. Salunke, Darshan Sonar, Nilesh Dengle , Sachin Kangude, Dattatraya Gawade, (2013). ”Home Automation Using Cloud Computing and Mobile Devices” IOSR Journal of Engineering (IOSRJEN) e-ISSN: 2250-3021, p-ISSN: 2278-8719 Vol. 3, Issue 2 (Feb. 2013).

[9]. R. Sharma, K. Kumar, and S. Viq, (2006). “DTMF Based Remote Control System,” IEEE International Conference ICIT 2006, pp. 2380-2383, December 2006.

[10]. Oppenheim, Alan V. and Schafer, Ronald W. (1989). Digital Signal Processing. Prentice-Hall of India, 1989.

[11]. Atmega 32A datasheet, http://www.atmel.in/ Images/doc8155.pdf8870 Data sheet , http://www.clare.com/datasheets/8870-01.pdf.

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Research Paper

Analysing the Effect of Cluster Strategies in Multicast Traffic using TAM Protocol for Ad-hoc Networks

Deepakraj S* , Thamilselvan R.**

* M.E., Department of Information Technology, Kongu Engineering College, Erode.

** Associate Professor, Kongu Engineering College, Erode.

Deepakraj, S., and Thamilselvan, R. (2013). Analysing The Effect of Cluster Strategies In Multicast Traffic Using TAM Protocol for Ad-Hoc Networks. i-manager’s Journal on Wireless Communication Networks, 2(3), 14-19. https://doi.org/10.26634/jwcn.2.3.2555

Abstract

Ad-hoc networks generally play a vital role in emerging technologies. The limited communication and computation resources, the unguaranteed connectivity to trusted authorities make known security solutions for wired networks. A novel Tiered Authentication scheme for Multicast traffic (TAM) has large scale of ad-hoc networks. Nodes are grouped into the cluster. Cross-cluster multicast traffic includes a Message Authentication Code (MAC) that is based on set of keys. Each cluster uses unique subset of keys. TAM is combination of secret information asymmetry and the time information asymmetry for inter cluster and intra cluster networks. The topologies used are flat, spanning tree, balanced tree to reduce bandwidth overhead and delivery delay. These topologies are compared for numerical and analytical results that demonstrate the advantage of TAM.

References

[1]. Azarderskhsh R & Reyhani-Masoleh A, (2011), “Secure clustering and symmetric key establishment in heterogeneous wireless sensor networks,” EURASIP J. Wireless Communication. Network, Vol., article ID 893592.

[2]. Hanaoka G, Nishioka T, Zheng Y, & Imai H, (2012), “A hierarchical non interactive key-sharing scheme with low memory size and high resistance against collusion attacks,” Computer J., Vol. 45, No. 3, pp. 293–303.

[3]. Mohamed Younis, Osama Farrag, & Bryan Althouse, (2012), “TAM: A Tiered Authentication of Multicast Protocol for Ad-Hoc Networks,” IEEE Transactions on Network and Service Management, Vol. 9, no. 1.

[4]. Ngai E C H & Lyu M R, (2006), “An authentication service based on trust and clustering in wireless ad hoc networks: description and security evaluation,” in Proceeding. IEEE International Conf. Sensor Networks, Ubiquitous, Trustworthy Computing.

[5]. Perrig, Canetti R, Song D, & Tygar D, (2002), “Efficient authentication and signing of multicast streams over lossy channels,” in Proceeding. IEEE Symposium Security Privacy.

[6]. Royer E M & Perkins C, (2002), “Multicast ad-hoc ondemand distance vector (MAODV) routing,” Internet Draft, University of California, Charles E. Perkins Nokia Research Center.

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Research Paper

Survey of Adaptive scheme for QoS in Wireless Sensor Networks

Sivaranjini. R* , K. Sakthisudhan**

* Assistant Professor, Dept of ECE, M.Kumarasamy College of Engineering, Karur.

** Assistant Professor, Dept of ECE, Bannari AmmaN Institute of Technology, Sathyamangalam.

Sivaranjini, R., and Sakthisudhan, K. (2013). Survey of Adaptive Scheme for Qos in Wireless Sensor Networks, i-manager’s Journal on Wireless Communication Networks. 2(3), 20-27. https://doi.org/10.26634/jwcn.2.3.2556

Abstract

Accurate data extraction is difficult; it is often too costly to obtain all sensor readings, as well as not necessary in the sense that the readings themselves only represent samples of the true state of the world. Clustering and prediction techniques, which exploit spatial and temporal correlation among the sensor data, provide opportunities for reducing the energy consumption of continuous sensor data collection and to achieve network energy efficiency and stability. So as we propose an adaptive scheme to control power-aware data collection in wireless sensor networks by integrating adaptively enabling/disabling prediction scheme. Our framework is clustering based. A cluster head represents all sensor nodes in the cluster and collects data values from them. Our framework is general enough to incorporate many advanced features and we show how sleep/awake scheduling can be applied, which takes our framework approach to designing a practical algorithm for data aggregation: it avoids the need for rampant node-to-node propagation of aggregates, but rather it uses faster and more efficient cluster-to-cluster propagation. To the best of our knowledge, this is the first work adaptively enabling/disabling prediction scheme for clustering-based continuous data collection in sensor networks. When a cluster node fails because of energy depletion we need to choose alternative cluster for that particular region. Our proposed models, analysis, and framework are validated via simulation and comparison with competing techniques in order to achieve better energy efficiency and QoS.

References

[1]. http://db.lcs.mit.edu/labdata/labdata.html, 2010.

[2]. D. Chu, A. Deshpande, J.M. Hellerstein, and W. Hong, (2006). “Approximate Data Collection in Sensor Networks Using Probabilistic Models,” Proc. IEEE Int'l Conf. Data Eng.(ICDE),

[3]. Crossbow, (2003). “MICA2 Wireless Measurement System Datasheet,”

[4]. B. Gedik, L. Liu, and P.S. Yu, (2007). “ASAP: An Adaptive Sampling Approach to Data Collection in Sensor, Computing, Vol. 18, No. 12, pp. 1766-1783,

[5]. S. Goel and T. Imielinski, (2001). “Prediction-Based Monitoring in Sensor Networks: Taking Lessons from MPEG,” ACM SIGCOMM Computer Comm. Rev., Vol. 31, No. 5, pp. 82-98,

[6]. W.B. Heinzelman, A.P. Chandrakasan, and H. Balakrishnan, (2002). “An Application-Specific Protocol Architecture for Wireless Microsensor Networks, ” IEEE Trans. Wireless Comm., Vol. 1, No. 4, pp. 660-670, Oct.

[7]. W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, (2000). “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proc. Hawaii Int'l Conf. System Sciences,

[8]. S. Hussain and A.W. Matin, (2006). “Hierarchical Cluster- Based Routing in Wireless Sensor Networks,” Proc. Int'l Conf. Information Processing in Sensor Networks (IPSN),

[9]. H. Jiang and S. Jin, (2006). “Scalable and Robust Aggregation Techniques for Extracting Statistical Information in Sensor Networks,” Proc. IEEE Int'l Conf. Distributed Computing Systems (ICDCS),

[10]. H. Jiang and S. Jin, (2008). “Leap: Localized Energy- Aware Prediction for Data Collection in Wireless Sensor Networks,” Proc. IEEE Int'l Conf. Mobile Ad Hoc and Sensor Systems (MASS),

[11]. H. Jiang, W. Liu, D. Wang, C. Tian, X. Bai, X. Liu, Y. Wu, and W. Liu, (2009). “Case: Connectivity-Based Skeleton Extraction in Wireless Sensor Networks,” Proc. IEEE INFOCOM,

[12]. H. Jiang, W. Liu, D. Wang, C. Tian, X. Bai, X. Liu, Y. Wu, and W. Liu, (2010). “Connectivity-Based Skeleton Extraction in Wireless Sensor Networks,” IEEE Trans. Parallel and Distributed Systems, Vol. 21, No. 5, pp. 710-721,

[13]. J. Koshy, I. Wirjawan, R. Pandey, and Y. Ramin, (2008). “Balancing Computation and Communication Costs: The Case for Hybrid Execution in Sensor Networks,” Ad Hoc Networks, Vol. 6, pp. 1185- 1200,

“Balancing Computation and Communication Costs: The Case for Hybrid Execution in Sensor Networks,” Ad Hoc Networks, Vol. 6, pp. 1185- 1200, [14]. F. Kuhn, T. Moscibroda, and R. Wattenhofer, ( “Initializing Newly Deployed Ad Hoc and Sensor Networks,” Proc. ACM MOBICOM,

[15]. S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, (2005). “Tinydb: An Acquisitional Query Processing System for Sensor Networks,” ACM Trans. Database Systems, Vol. 30, No. 1, pp. 122- 173,

[16]. S.M. McConnell and D.B. Skillicorn, (2005). “A Distributed Approach for Prediction in Sensor Networks,” Proc. SIAM Int'l Conf. Data Mining Workshop Sensor Networks,

[17]. A. Meka and A.K. Singh, (2006). “Distributed Spatial Clustering in Sensor Networks,” Proc. Int'l Conf. Extending Database Technology (EDBT),

[18]. M. Pourahmadi, (2001). Foundations of Time Series Analysis and Prediction Theory. John Wiley and Sons,

[19]. C.M. Sadler and M. Martonosi, (2006). “Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks,” Proc. Int'l Conf. Embedded Networked Sensor Systems (SenSys),

[20]. B. Sheng, Q. Li, W. Mao, and W. Jin, (2007). “Outlier Detection in Sensor Networks,” Proc. ACM MOBIHOC,

[21]. A. Silberstein, R. Braynard, G. Filpus, G. Puggioni, A. Gelfand, K. Munagala, and J. Yang, (2007). “Data-Driven Processing in Sensor Networks,” Proc. Conf. Innovative Data Systems Research (CIDR),

[22]. A. Silberstein, K. Munagala, and J. Yang, (2006). “Energy-Efficient Monitoring of Extreme Values in Sensor Networks,” Proc. ACM SIGMOD,

[23]. M. Tahir and R. Farrell, (2009). “Optimal Communication-Computation Tradeoff for Wireless Multimedia Sensor Network Lifetime Maximization,” Proc. IEEE Wireless Comm. and Network Conf. (WCNC),

[24]. D. Tulone and S. Madden, (2006). “An Energy-Efficient Querying Framework in Sensor Networks for Detecting Node Similarities,” Proc. IEEE/ACM Int'l Conf. Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM),

[25] A. Wang and A. Chandrakasan,(2002) ( “Energy- Efficient DSPs for Wireless Sensor Networks,” IEEE Signal Processing Magazine, Vol. 19, No. 4, pp. 68-78, July.

[26]. Y. Xu and W.-C. Lee, (2003). “On Localized Prediction for Power Efficient Object Tracking in Sensor Networks,” Proc. IEEE Int'l Conf. Distributed Computing Systems (ICDCS),

[27]. O. Younis and S. Fahmy, (2004). “HEED: A Hybrid Energy-Efficient Distributed Clustering for Adhoc Sensor Networks,” Proc. IEEE INFOCOM,

[28]. O. Younis, M. Krunz, and S. Ramasubramanian, (2006). “Node Clustering in Wireless Sensor Networks: Recent Developments and Deployment Challenges,” IEEE Network, Vol. 20, No. 3, pp. 20-25, May/ June.

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Research Paper

Devotees Tracking Using GPS and ISP

S.Sudha* , L.Gowthami**

*-** M.E Student, Embedded System Technologies, KSR IET, Tiruchengode, India.

Sudha, S., and Gowthami, L. (2013). Devotees Tracking Using GPS and ISP, i-manager’s Journal on Wireless Communication Networks. 2(3), 28-32. https://doi.org/10.26634/jwcn.2.3.2557

Abstract

Every day, lakhs of devotees gather in Tirupathi.. Tracking the movement of such a large number of people is crucial to the devotees them-selves and the authorities managing the whole event. This letter reports a real-time devotee tracking system that has been designed and implemented. The system relies on a dedicated delay-tolerant wireless sensor network (WSN). This WSN is interfaced to the Internet through gateway(s) available from an internet service provider (ISP) . Energy efficiency, robustness, and reliability are key factors in the design of the system. Each devotee is given a mobile sensor unit which includes a GPS chip, a microcontroller, and antennas. A network of fixed units is installed in the Holy area for receiving and forwarding data. Periodically, each mobile unit sends its user identification (UID), latitude, longitude, and a time stamp. A central server maps the latitude and longitude information on a geographical information system (GIS). The developed system can be used to track a specific or a group of devotees.

References

[1]. F. Abdessemed, (2011). “An Integrated System for Tracking and Control Pilgrims Shuttle Buses”, 14th International IEEE conference on Intelligent Transportation Systems, 2011.

[2]. El-Hoiydi, (2002). “Aloha with preamble sampling for sporadic traffic in ad hoc wireless sensor networks,” presented at the IEEE Int. Conf. Commun., New York, Apr. 28–May 2 2002.

[3]. Haleem M.A , C. N. Mathur, and K. P. Subbalakshmi, (2006). “Joint distributed compression and encryption of Correlated data in sensor networks,” presented at the IEEE Military Commun. Conf. (MILCOM), Washington, DC,

[4]. Hasan, K.S., Rahman, M., Haque, A.L., Rahman, M.A., Rahman, T. and Rasheed, M.M., (2009). Cost effective GPS-GPRS based object tracking system. In Proceedings of the International Multi Conference of Engineers and Computer Scientists.

[5]. M. Mohandes, (2010). “RFID-based system for pilgrims identification & tracking,” J. Appl. Comput. Electromagn. Soc. (ACES), Vol. 25, No. 3,pp. 273–282.

[6]. Mohandes, Haleem, Abul-Hussain, and Balakrishnan, (2011). “Pilgrim tracking using wireless sensor network,” presented at the Workshops, Int. Conf. Adv. Inform. Netw. Appl. (WAINA 2011), Singapore, Mar. 22–25,

[7]. Mohamed Amer al nizar, (2011). “Emergency Stations in the grand mosque of Mecca using WSN”, Master thesis.

[8]. Rappaport T.S, (2002). Wireless Communications: Principles and Practice, 2nd ed. Upper Saddle River, NJ: Prentice Hall.

[9]. Tanenbaum.S, (2003). Computer Networks. Upper Saddle River, NJ: Prentice Hall.

[10]. Zhang .P, C. M. Sadler, S. A. Lyon, and M. Martonosi, ( 2004).“Hardware design experiences in zebranet,” in Proc. 2nd Int. Conf. Embed. Netw. Sensor Syst., New York, pp. 227–238, ACM Press.

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

Current Issue Vol. 12 Issue 1

Most Read

Most Cited

Volume 2 Issue 3 October - December 2013

Cooperative Spectrum Sharing Protocol with Selective Relay System in Cognitive Radio Network

N. Elayabharathi* , M.Poonguzhali**, B. Pradeep Raja***, K.Yalini****

*-**-****Department of ECE, Narasu's Sarathy Institute of Technology, Salem *** Department of ECE, College of Engineering, Anna University, Chennai.

Elayabharathi, N., Raja, B.P., Yalini, K., and Poonguzhali, M. (2013). Cooperative Spectrum Sharing Protocol with selective Relay System in Cognitive Radio Network, i-manager’s Journal on Wireless Communication Networks. 2(3), 1-7. https://doi.org/10.26634/jwcn.2.3.2553

Abstract

References

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Mobile- Microcontroller Based Wireless Communication For The Control Of Appliances Integrated With Their Automation

K.V.N. Kavitha* , Shashank Chaurasia**

*-** School of Electronics Engineering, VIT University, Vellore, India.

Kavitha, K.V.N., and Chaurasia, S. (2013). Mobile- Microcontroller Based Wireless Communication For The Control Of Appliances Integrated With Their Automation, i-manager’s Journal on Wireless Communication Networks. 2(3), 8-13. https://doi.org/10.26634/jwcn.2.3.2554

Abstract

References

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Analysing the Effect of Cluster Strategies in Multicast Traffic using TAM Protocol for Ad-hoc Networks

Deepakraj S* , Thamilselvan R.**

* M.E., Department of Information Technology, Kongu Engineering College, Erode. ** Associate Professor, Kongu Engineering College, Erode.

Deepakraj, S., and Thamilselvan, R. (2013). Analysing The Effect of Cluster Strategies In Multicast Traffic Using TAM Protocol for Ad-Hoc Networks. i-manager’s Journal on Wireless Communication Networks, 2(3), 14-19. https://doi.org/10.26634/jwcn.2.3.2555

Abstract

References

Full Article (HTML)

Pdf

Survey of Adaptive scheme for QoS in Wireless Sensor Networks

Sivaranjini. R* , K. Sakthisudhan**

* Assistant Professor, Dept of ECE, M.Kumarasamy College of Engineering, Karur. ** Assistant Professor, Dept of ECE, Bannari AmmaN Institute of Technology, Sathyamangalam.

Sivaranjini, R., and Sakthisudhan, K. (2013). Survey of Adaptive Scheme for Qos in Wireless Sensor Networks, i-manager’s Journal on Wireless Communication Networks. 2(3), 20-27. https://doi.org/10.26634/jwcn.2.3.2556

Abstract

References

Full Article (HTML)

Pdf

Devotees Tracking Using GPS and ISP

S.Sudha* , L.Gowthami**

*-** M.E Student, Embedded System Technologies, KSR IET, Tiruchengode, India.

Sudha, S., and Gowthami, L. (2013). Devotees Tracking Using GPS and ISP, i-manager’s Journal on Wireless Communication Networks. 2(3), 28-32. https://doi.org/10.26634/jwcn.2.3.2557

Abstract

References

Full Article (HTML)

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N. Elayabharathi* , M.Poonguzhali, B. Pradeep Raja*, K.Yalini****

--Department of ECE, Narasu's Sarathy Institute of Technology, Salem

Department of ECE, College of Engineering, Anna University, Chennai.

* M.E., Department of Information Technology, Kongu Engineering College, Erode.

** Associate Professor, Kongu Engineering College, Erode.

* Assistant Professor, Dept of ECE, M.Kumarasamy College of Engineering, Karur.

** Assistant Professor, Dept of ECE, Bannari AmmaN Institute of Technology, Sathyamangalam.