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 5 Issue 4 January - March 2017

Research Paper

A Novel Next Hop Selection Algorithm for Multi-Hop Wireless Sensor Networks

Hanafy Mahmoud Ali*

Assistant Professor, Department of Computers and Systems Engineering, Faculty of Engineering, Minia University, El Minia, Egypt.

Ali, H.M. (2017). A Novel Next Hop Selection Algorithm for Multi-Hop Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 1-9. https://doi.org/10.26634/jwcn.5.4.13552

Abstract

In this paper, the author has proposed a new route next-hop selection algorithm for Wireless Sensor Networks (WSNs) that is aimed towards reducing packet loss, end-to-end delay, and energy consumption. In this proposed algorithm, the forwarding nodes are selected through hop-by-hop estimation of QoS, and residual energy. The efficiency of the proposed routing algorithm is evaluated by using the NS-2 simulator. The simulation results show that the proposed algorithm provides a significant improvement in terms of energy consumption, the number of packets forwarded, an end to end delay, and packet delivery ratio compared to the existing routing protocol.

References

[1]. Ahn, K. S., Kim, D. G., Sim, B. S., Youn, H. Y., & Song, O. (2011, May). Balanced chain-based routing protocol (BCBRP) for energy efficient wireless sensor networks. In Parallel and Distributed Processing with Applications Workshops (ISPAW), 2011 Ninth IEEE International Symposium on (pp. 227-231). IEEE.

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

[3]. Alazzawi, L. K., Elkateeb, A. M., Ramesh, A., & Aljuhar, W. (2008, March). Scalability analysis for wireless sensor networks routing protocols. In Advanced Information Networking and Applications-Workshops, 2008. AINAW nd 2008. 22 International Conference on (pp. 139-144). IEEE.

[4]. Biswas, S., & Morris, R. (2005). ExOR: opportunistic multi-hop routing for wireless networks. ACM SIGCOMM Computer Communication Review, 35(4), 133-144.

[5]. Chen, J., Díaz, M., Llopis, L., Rubio, B., & Troya, J. M. (2011). A survey on quality of service support in wireless sensor and actor networks: Requirements and challenges in the context of critical infrastructure protection. Journal of Network and Computer Applications, 34(4), 1225- 1239.

[6]. Dâmaso, A., Rosa, N., & Maciel, P. (2014). Reliability of wireless sensor networks. Sensors, 14(9), 15760-15785.

[7]. Doddamani, L. M., Yaragop, S. M., Chikaraddi, A., & Kanakaraddi, S. (2016, March). Energy consumption comparison of AODV and DSDV routing protocols. In Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on (pp. 2128-2132). IEEE.

[8]. Garcia, M., Bri, D., Boronat, F., & Lloret, J. (2008, March). A new neighbour selection strategy for groupbased wireless sensor networks. In Networking and Services, 2008. ICNS 2008. Fourth International Conference on (pp. 109-114). IEEE.

[9]. Gousalya, S., Lavanya, S., & Bhagyaveni, M. A. (2016, April). Opportunistic AODV routing protocol for cognitive radio wireless sensor networks. In Communication and Signal Processing (ICCSP), 2016 International Conference on (pp. 0412-0415). IEEE.

[10]. Guo, L., Ning, Z., Song, Q., Zhang, L., & Jamalipour, A. (2017). A QoS-Oriented High-Efficiency Resource Allocation Scheme in Wireless Multimedia Sensor Networks. IEEE Sensors Journal, 17(5), 1538-1548.

[11]. Gupta, M., & Kumar, S. (2015, February). Performance Evaluation of DSR, AODV and DSDV Routing Protocol for Wireless Adhoc Network. In Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on (pp. 416-421). IEEE.

[12]. Horvat, G., Vlaovic, J., & Zagar, D. (2015, June). Improving QoS in query-driven WSN using a cross-layered handover algorithm. In Embedded Computing (MECO), th 2015 4 Mediterranean Conference on (pp. 236-239). IEEE.

[13]. Keshtkarjahromi, Y., Ansari, R., & Khokhar, A. (2013, November). Energy efficient decentralized detection based on bit-optimal multi-hop transmission in onedimensional wireless sensor networks. In Wireless Days (WD), 2013 IFIP (pp. 1-8). IEEE.

[14]. Khan, T. F., & Sivakumar, D. (2014, July). Performance of AODV, DSDV and DSR protocols in mobile wireless mesh networks. In Current Trends in Engineering and nd Technology (ICCTET), 2014 2 International Conference on (pp. 397-399). IEEE.

[15]. Kumar, V., Baghel, A. S., & Mishra, P. (2016, March). Performance evaluation of DSDV, AODV and LSGR protocol in ad-hoc networks. In Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on (pp. 4261-4266). IEEE.

[16]. Laranjeira, L. A., & Rodrigues, G. N. (2014). Border effect analysis for reliability assurance and continuous connectivity of wireless sensor networks in the presence of sensor failures. IEEE Transactions on Wireless Communications, 13(8), 4232-4246.

[17]. Lei, F., Yao, L., Zhao, D., & Duan, Y. (2017). Energy- Efficient Abnormal Nodes Detection and Handlings in Wireless Sensor Networks. IEEE Access, 5, 3393-3409.

[18]. Leu, J. S., Chiang, T. H., Yu, M. C., & Su, K. W. (2015). Energy efficient clustering scheme for prolonging the lifetime of wireless sensor network with isolated nodes. IEEE Communications Letters, 19(2), 259-262.

[19]. Li, S., Ge, H., Liang, Y. C., Zhao, F., & Li, J. (2016). Estimator Goore Game based quality of service control with incomplete information for wireless sensor networks. Signal Processing, 126, 77-86.

[20]. Loganathan, D., & Ramamoorthy, P. (2013, February). Efficient routing with multicost parameters based DSDV protocol in wireless ad hoc networks. In Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference on (pp. 435- 439). IEEE.

[21]. Lukachan, G., Labrador, M. A., & Moreno, W. (2006, April). Scalable and energy-efficient routing for largescale wireless sensor networks. In Devices, Circuits and th Systems, Proceedings of the 6 International Caribbean Conference on (pp. 267-272). IEEE.

[22]. Mahapatra, C., Sheng, Z., Leung, V. C., & Stouraitis, T. (2015, June). A reliable and energy efficient IoT data transmission scheme for smart cities based on redundant residue based error correction coding. In Sensing, Communication, and Networking-Workshops (SECON th Workshops), 2015 12 Annual IEEE International Conference on (pp. 1-6). IEEE.

[23]. Mohapatra, S., & Kanungo, P. (2012). Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 Simulator. Procedia Engineering, 30, 69-76.

[24]. Nayaka, R. J., & Biradar, R. C. (2015, June). QoS analysis of WSN based cluster tree data fusion for integrated public utility management. In Advance Computing Conference (IACC), 2015 IEEE International (pp. 579-584). IEEE.

[25]. Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 15(2), 551-591.

[26]. Paul, B., Bhuiyan, K. A., Fatema, K., & Das, P. P. (2014, November). Analysis of AOMDV, AODV, DSR, and DSDV routing protocols for wireless sensor network. In Computational Intelligence and Communication Networks (CICN), 2014 International Conference on (pp. 364-369). IEEE.

[27]. Raghavendra, C. S., Sivalingam, K. M., & Znati, T. (Eds.). (2004). Wireless Sensor Networks. Springer.

[28]. Rahman, J., Hasan, M. A. M., & Islam, M. K. B. (2012, December). Comparative analysis the performance of AODV, DSDV and DSR routing protocols in wireless sensor network. In Electrical & Computer Engineering (ICECE), th 2012 7 International Conference on (pp. 283-286). IEEE.

[29]. Rajesh, M., Vanishree, K., & Sudarshan, T. S. B. (2015, December). Stable route AODV routing protocol for mobile wireless sensor networks. In Computing and Network Communications (CoCoNet), 2015 International Conference on (pp. 917-923). IEEE.

[30]. Salve, V. B., Ragha, L., & Marathe, N. (2015, March). AODV based secure routing algorithm against Sinkhole attack in wirelesses Sensor Networks. In Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference on (pp. 1-7). IEEE.

[31]. Sohraby, K., Minoli, D., & Znati, T. (2007). Wireless Sensor Networks: Technology, Protocols, and Applications. John Wiley & Sons.

[32]. Suryawanshi, R., & Nimbhorkar, S. U. (2013, March). Review on QoS aware improved AODV routing protocol in wireless mesh network. In Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), 2013 International Multi-Conference on (pp. 613-616). IEEE.

[33]. Thangaraj, J., & Kumari, S. (2016, March). Evaluating feasibility of using Wireless Sensor Network in agricultural land through simulation of DSR, AOMDV, AODV, DSDV protocol. In Wireless Communications, Signal Processing and Networking (WiSPNET), International Conference on (pp. 301-305). IEEE.

[34]. Yadav, M., Gupta, S. K., & Saket, R. K. (2015, January). Multi-hop wireless ad-hoc network routing protocols-a comparative study of DSDV, TORA, DSR and AODV. In Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on (pp. 1-5). IEEE.

[35]. Yan, J., Zhou, M., & Ding, Z. (2016). Recent advances in energy-efficient routing protocols for wireless sensor networks: A review. IEEE Access, 4, 5673-5686.

[36]. Zhang, D., Li, G., Zheng, K., Ming, X., & Pan, Z. H. (2014). An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Transactions on Industrial Informatics, 10(1), 766-773.

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Research Paper

Energy Aware Clustering Algorithm for Wireless Sensor Networks

P. Santhanakumar* , G. Arun Sampaul Thomas**

* PG Scholar, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India.

** Assistant Professor and Associate Head, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India.

Santhanakumar, P., and Thomas, G.A.S. (2017). Energy Aware Clustering Algorithm for Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 10-14. https://doi.org/10.26634/jwcn.5.4.13553

Abstract

Clustering is a popular routing technique in configuring Wireless Sensor Networks (WSNs). It can determine the communications between all nodes to collect data in an efficient manner. It handles the main challenge of energyefficiency in WSNs, and can be used to re-configure the network according to changes in the nodes' conditions. In this paper, an energy aware clustering algorithm is proposed for utilizing the energy efficiency and prolonging the lifetime of the network. The proposed algorithm elects the Cluster Head based on the parameter of residual energy. The Cluster Head node gathers the information from its members and forwards it to the Base Station. The proposed algorithm constructs the virtual circle for balancing the energy consumption among the sensor nodes. The simulation results show that the proposed algorithm utilizes the energy efficiently and extends the lifetime of the network efficiently.

References

[1]. Abbasi, A. 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]. Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537- 568.

[4]. Chen, G., Li, C., Ye, M., & Wu, J. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15(2), 193-207.

[5]. Dietrich, I., & Dressler, F. (2009). On the lifetime of wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5(1), 5.

[6]. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660-670.

[7]. Lee, S., Choe, H., Park, B., Song, Y., & Kim, C. K. (2011). LUCA: An energy-efficient unequal clustering algorithm using location information for wireless sensor networks. Wireless Personal Communications, 56(4), 715-731.

[8]. Selvakennedy, S., & Sinnappan, S. (2005, November). The time-controlled clustering algorithm for optimized data dissemination in wireless sensor network. th In Local Computer Networks, 2005. 30 Anniversary. The IEEE Conference on (pp. 509-510). IEEE.

[9]. Sohrabi, K., Gao, J., Ailawadhi, V., & Pottie, G. J. (2000). Protocols for self-organization of a wireless sensor network. IEEE Personal Communications, 7(5), 16-27.

[10]. Ye, M., Li, C., Chen, G., & Wu, J. (2005, April). EECS: An energy efficient clustering scheme in wireless sensor n e t w o r k s. I n Pe r f o rma n c e , C omp u t i n g , a n d th Communications Conference, 2005. IPCCC 2005. 24 IEEE International (pp. 535-540). IEEE.

[11]. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366-379.

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Research Paper

Dynamic Resource Allocation with Power Constraint in WCDMA Wireless Networks

Vandana Khare* , Y. Madhavee Latha, D. Srinivasa Rao*

* Research Scholar, JNT University, Hyderabad, India.

Principal, Malla Reddy Engineering College for Women, Hyderabad, India.

* Professor, Department of Electronics and Communication Engineering, JNTUH, Hyderabad, India.

Khare, V., Latha, Y.M., Rao, D.S. (2017). Dynamic Resource Allocation with Power Constraint in WCDMA Wireless Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 15-19. https://doi.org/10.26634/jwcn.5.4.13554

Abstract

WCDMA is a Wideband Code Division Multiple Access technique. Because of high data rate, it is mainly used in the 3 generation mobile networks. In Centralized Call Admission Control (CCAC) technique, when a new call arrives, the system checks whether the call should be admitted or not on the basis of Signal to Interference Ratio (SIR), transmission power, and the network load. If the call is accepted, it will increase some interference to the ongoing calls. This new interference would degrade the performance of ongoing calls, increase the outage rate, and ultimately affects the Quality of Service of the network. Hence, to reduce the interference while improving Quality of Service in the WCDMA network, an efficient Resource Allocation with Power Constraint (PC) in the network is required for achieving a higher throughput with appropriate handoff, improved battery life as well as network performance. This paper proposes an algorithm for Resource Allocation with Power Constraint (PC) for real time traffic in WCDMA Network. The simulation result shows that the proposed scheme can significantly reduce power consumption and increase throughput with less delay.

References

[1]. Abdelouahed, J. (2012). A Theoretical Prediction of Users in WCDMA Interference. Journal of Theoretical and Applied Information Technology, 35(2), 163-168.

[2]. Alani, O. Y., & Aziz, M. (2010, June). Dynamic WCDMA system proposal for QoS in multimedia networks. In Computers and Communications (ISCC), 2010 IEEE Symposium on (pp. 1003-1006). IEEE.

[3]. AlQahtani, S. A., Mahmoud, A. S., & Sheikh, A. U. (2007, June). Performance analysis of adaptive rate scheduling scheme for 3G WCDMA wireless networks with multi-operators. In Communications, 2007. ICC'07. IEEE International Conference on (pp. 4811-4816). IEEE.

[4]. Badia, L., Telesca, A., & Zorzi, M. (2006). On the network utility optimal allocation of radio resources in WCDMA systems. IEEE Communications Letters, 10(5), 341-343.

[5]. Chen, Y. L., Wang, J. W., Chen, J. L., & Wen, J. H. (2007). Performance of Call Admission Control with Power Control in Multimedia Cellular Systems. International Journal of Applied Science and Engineering, 5(1), 65-74.

[6]. Liu, I. S., Takawira, F., & Xu, H. J. (2007). Optimization of hybrid token-CDMA MAC system using cross-layer information.

[7]. Mohan, N., & Ravichandran, T. (2009). An efficient multiclass call admission control and adaptive scheduling for WCDMA wireless network. European Journal of Scientific Research, 33(4), 718-727.

[8]. Oh, S. J., Olsen, T. L., & Wasserman, K. M. (2000). Distributed power control and spreading gain allocation in CDMA data networks. In INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE (Vol. 2, pp. 379-385). IEEE.

[9]. Patil, R., & Damodaram, D. A. (2008). Joint scheduling and power control for multiclass users in CDMA wireless ad hoc networks. Wseas Transactions on Communications.

[10]. Rachidi, T. E., Elbatji, A. Y., Sebbane, M., & Bouzekri, H. (2004, March). QoS-aware power control and handoff prioritization in 3G WCDMA networks. In Wireless Communications and Networking Conference, 2004. WCNC. 2004 IEEE (Vol. 2, pp. 665-670). IEEE.

[11]. Wang, X. (2003, March). An FDD wideband CDMA MAC protocol for wireless multimedia networks. In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies (Vol. 1, pp. 734-744). IEEE.

[12]. Zhang, P., & Jordan, S. (2008). Cross layer dynamic resource allocation with targeted throughput for WCDMA data. IEEE Transactions on Wireless Communications, 7(12), 4896-4906.

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Research Paper

Design and Simulation of Digital Beacon Receiver

Revathi* , P. Parvathi, G. Hemachandra*

* PG Scholar, Department of Electronics and Communication Engineering, Sri Vidyanikethan Engineering College, Tirupati, India.

Scientist/Engineer-SE, National Atmospheric Research Laboratory (NARL), Gadanki, Tirupati, India.

* Assistant Professor, Department of Electronics and Communication Engineering, Sri Vidyanikethan Engineering College, Tirupati, India.

Revathi, V., Parvathi, P., and Hemachandra, G. (2017). Design and Simulation of Digital Beacon Receiver. i-manager’s Journal on Wireless Communication Networks, 5(4), 20-26. https://doi.org/10.26634/jwcn.5.4.13555

Abstract

The detailed simulation of Digital Beacon Receiver consists of Low Noise Block Convertor (LNBC) and L-band Down Convertor (LBDC) by using Keysight Technologies Advanced Design System (ADS) Software. In the propagation path between satellite to ground stations, some natural phenomena, such as atmospheric gases, water vapour, oxygen molecules, clouds, rain, dust, fog, existing in different layers of the atmosphere, including troposphere can cause some impairment on the availability and quality of satellite link service periods. This natural phenomenon cause errors and problems, such as attenuation change in polarization, fading delay, and dispersion. Particularly at higher frequencies such as Ku and Ka bands, effects of those propagation phenomena will not be neglectable and they should be considered. For reliable and secure satellite communication, theoretical and experimental propagation study in different frequencies and region is essential. ISRO has setup two beacon signals at 20.2 and 30.5 GHz on board GSAT-14 for this purpose. There are different methods to study satellite wave propagation, such as radar, radiometer, signal beacon method, and satellite beacon methods. Satellite beacon method is one of the most important reliable and inexpensive methods in comparison with the other methods. This paper presents the design simulation of the receiver setup for the above purposes.

References

[1]. Babu, P. R. (2008). Digital Signal Processing, 4 Edition. Scitech Publications.

[2]. Bauer, R. (1997). Ka-band propagation measurements: An opportunity with the Advanced C ommunications Technology Satellite (ACTS) . Proceedings of the IEEE, 85(6), 853-862.

[3]. Bolea-Alamanac, A., Bousquet, M., Castanet, L., & Van de Kamp, M. M. J. L. (2003, May). Implementation of short-term prediction models in fade mitigation techniques control loops. In Joint COST 272/280 Workshop.

[4]. Dunleavy, L. P., Flikkema, P. G., & Kuppusamy, A. (1997, December). Characterization and simulation of a 915MHz wireless receiver. In ARFTG Conference Digestth Fall, 50 (Vol. 32, pp. 42-53). IEEE.

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[6]. Kikkert, C. J., & Kenny, O. P. (2008, December). A digital signal processing based Ka band Satellite Beacon Receiver/Radiometer. In Signal Processing and nd Communication Systems, 2008. ICSPCS 2008. 2 International Conference on (pp. 1-8). IEEE.

[7]. Nandakumar, P., Reddy, D. G. S., & Durga Rao, M. Simulation of L-Band Analog Receiver using ADS software for Ground Station Receiver Applications. International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE), 4(10).

[8]. Prakash, C., Bhatt, K. A., Valdiya, S. S. & Dasgupta, K. S. (2009). Design and Development of Ka Band Digital Beacon Receiver for Ka Band Propagation studied Experiment. International Journal of Systems and Technologies, 2(2), 167-177.

[9]. Prakash, C., Chakka, V. K., Satashia, S. N., & Parikh, K. S. (2013, April). Digital receiver based Ka Band beacon receiver for improved beacon power estimation. In Communications and Signal Processing (ICCSP), 2013 International Conference on (pp. 1117-1122). IEEE.

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Research Paper

Design of Microwave Filter using Coupled Line Technique

Pooja Gupta* , Ashutosh Kumar**

* Assistant Professor, Department of Electronics and Communication Engineering, Kanpur Institute of Technology, Kanpur, India.

** DRDO Scientist, RCMA, Kanpur, India.

Gupta, P., and Kumar, A. (2017). Design of Microwave Filter using Coupled Line Technique. i-manager’s Journal on Wireless Communication Networks, 5(4), 27-31. https://doi.org/10.26634/jwcn.5.4.13556

Abstract

This paper presents the design of narrow band-pass filter and wide band-pass filter using microstrip coupled line structure. The narrow band-pass filter is designed to operate at dual center frequencies of 1.227 GHz and 1.575 GHz for GPS and the wide band-pass filter to operate at X-band segment (8-12 GHz) of microwave frequency spectrum with center frequency of 10 GHz. The device dimensions are calculated using MATLAB coding and the simulative analysis of the filter is done using ADS and microwave studio software. The filter response by CST and ADS are compared using MATLAB.

References

[1]. Al-Amin, M. R., Sundar, S., & Islam, K. Z. (June, 2015). Design and simulation of an Edge-coupled Band Pass Filter at X Band. In International Conference on Materials, Electronics & Information Engineering (ICMEIE-2015), pp.5-6.

[2]. Bhat, B., & Koul, S. K. (1989). Stripline-like Transmission Lines for Microwave Integrated Circuits. New Age International.

[3]. Collin, R. E. (1992). “Introduction, Ch.1”. Foundations for Microwave Engineering, 1-16. New York: McGraw-Hill.

[4]. Goyal, A., & Kaur, A. (2014). Analysis and Design of Microstrip Bandpass Filter. International Journal of Advanced Technology & Engineering Research, 1113- 1116.

[5]. Hong, J. S. G., & Lancaster, M. J. (2001). Microstrip Filters for RF/Microwave Applications. John Wiley & Sons.

[6]. Kumar, M., & Kumar, S. (2014). Designing of Half Wavelength Parallel - Edge Coupled Line Band Pass Filter Using HFSS. IJARCSSE, 4(8), 876-882.

[7]. Pozar, D. M. (2009). Microwave Engineering. John Wiley & Sons.

[8]. Shakdwipee, P., Vyas, K., & Shakdwipee, N. (2012). Design and Simulation of Microstrip Edge-Coupled Band Pass Filter for GPS Application, IJEEMC, 1(1).

[9]. Sharma, G., Navin, P. S., Bhati, Y., & Walia, Y. (2013). Half-wavelength parallel edge coupled filter simulation using Matlab. International Journal of Innovative Re s e a rc h i n C omp u t e r a n d C ommu n i c a t i o n Engineering, 1(2), 248-253.

[10]. Taoufik, R., Touhami, N. A. & Agoutane, M. (2013). Designing of Microstrip Coupled Line Band-Pass Filter. International Journal of Engineering and Technology, 2(4), 266-269.

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Review Paper

Sensory Life in Sensory World

Mohammad Samadi Gharajeh*

Young Researchers and Elite Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran.

Gharajeh, M.S. (2017). Sensory Life in Sensory World. i-manager’s Journal on Wireless Communication Networks, 5(4), 32-44. https://doi.org/10.26634/jwcn.5.4.13557

Abstract

In the recent decades, sensors have affected on our life in various fields, including research activities, standardization procedures, and industrial investments. Various types of sensors (e.g., pressure, temperature, and humidity) can be used in Wireless Sensor Networks (WSNs) to design and implement some of the important applications, such as environmental monitoring, healthcare systems, and military issues. WSNs consist of the low-power, large-scale, and low-cost sensor nodes. The nodes measure phenomena data (e.g., smoke density) to transmit the measured data to a center (e.g., sink or base station). Routing, security, and fault tolerance are some of the crucial challenges in sensor networks. This paper describes various physical features and key usages of the popular sensors. Furthermore, three WSNs applications in monitoring, healthcare, and military are considered subsequently. Since sensor localization and data mining are two important topics in WSNs, their categories and characteristics are addressed too. Evaluation results show the performance of sensor networks compared to radio-frequency identification (RFID) in terms of utilization, purpose, components, mobility, power supply, programmability, and deployment. Besides, some of the WSNs simulators are compared to each other in terms of computation time and memory usage.

References

[1]. Abrishambaf, R., Akbari, A., & Hashemipour, M. (2014). Comparison of wireless sensor network and radio frequency identification for the process control of distributed industrial systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 228(5), 316-329.

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[4]. Aghdam, F. B., Babaie, S, & Gharajeh, M. S. (2011b). Investigate the Attacks on the Network-Transport Layer and Application Attacks on RFID and Solutions for Dealing with them. Proceedings of the National Conference on Electrical and Computer Engineering, Islamic Azad University of Neyriz, Iran, Neyriz. May 2011, pp. 1-8.

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[9]. Bindu, A. H., & Prasad, V. R. (2016). Secure Energy Efficient LEACH (EE_LEACH) Protocol for Wireless Sensor Networks. i-manager's Journal on Wireless Communication Networks, 5(2), 1.

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

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Volume 5 Issue 4 January - March 2017

A Novel Next Hop Selection Algorithm for Multi-Hop Wireless Sensor Networks

Hanafy Mahmoud Ali*

Assistant Professor, Department of Computers and Systems Engineering, Faculty of Engineering, Minia University, El Minia, Egypt.

Ali, H.M. (2017). A Novel Next Hop Selection Algorithm for Multi-Hop Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 1-9. https://doi.org/10.26634/jwcn.5.4.13552

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Energy Aware Clustering Algorithm for Wireless Sensor Networks

P. Santhanakumar* , G. Arun Sampaul Thomas**

* PG Scholar, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India. ** Assistant Professor and Associate Head, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India.

Santhanakumar, P., and Thomas, G.A.S. (2017). Energy Aware Clustering Algorithm for Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 10-14. https://doi.org/10.26634/jwcn.5.4.13553

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Dynamic Resource Allocation with Power Constraint in WCDMA Wireless Networks

Vandana Khare* , Y. Madhavee Latha**, D. Srinivasa Rao***

* Research Scholar, JNT University, Hyderabad, India. ** Principal, Malla Reddy Engineering College for Women, Hyderabad, India. *** Professor, Department of Electronics and Communication Engineering, JNTUH, Hyderabad, India.

Khare, V., Latha, Y.M., Rao, D.S. (2017). Dynamic Resource Allocation with Power Constraint in WCDMA Wireless Networks. i-manager’s Journal on Wireless Communication Networks, 5(4), 15-19. https://doi.org/10.26634/jwcn.5.4.13554

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Design and Simulation of Digital Beacon Receiver

Revathi* , P. Parvathi**, G. Hemachandra***

Revathi, V., Parvathi, P., and Hemachandra, G. (2017). Design and Simulation of Digital Beacon Receiver. i-manager’s Journal on Wireless Communication Networks, 5(4), 20-26. https://doi.org/10.26634/jwcn.5.4.13555

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Design of Microwave Filter using Coupled Line Technique

Pooja Gupta* , Ashutosh Kumar**

* Assistant Professor, Department of Electronics and Communication Engineering, Kanpur Institute of Technology, Kanpur, India. ** DRDO Scientist, RCMA, Kanpur, India.

Gupta, P., and Kumar, A. (2017). Design of Microwave Filter using Coupled Line Technique. i-manager’s Journal on Wireless Communication Networks, 5(4), 27-31. https://doi.org/10.26634/jwcn.5.4.13556

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Sensory Life in Sensory World

Mohammad Samadi Gharajeh*

Young Researchers and Elite Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran.

Gharajeh, M.S. (2017). Sensory Life in Sensory World. i-manager’s Journal on Wireless Communication Networks, 5(4), 32-44. https://doi.org/10.26634/jwcn.5.4.13557

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* PG Scholar, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India.

** Assistant Professor and Associate Head, Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India.

Vandana Khare* , Y. Madhavee Latha, D. Srinivasa Rao*

* Research Scholar, JNT University, Hyderabad, India.

Principal, Malla Reddy Engineering College for Women, Hyderabad, India.

* Professor, Department of Electronics and Communication Engineering, JNTUH, Hyderabad, India.

Revathi* , P. Parvathi, G. Hemachandra*

* Assistant Professor, Department of Electronics and Communication Engineering, Kanpur Institute of Technology, Kanpur, India.

** DRDO Scientist, RCMA, Kanpur, India.