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 8 Issue 4 January - June 2020

Research Paper

Investigating the Impact of Network Parameters on Wormhole Attack with ANODR Routing Protocol in MANET

Dr. Uppe Nanaji* , S. Pallam Setty **

*-** Department of Computer Science and Software Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.

Nanaji, U., and Setty, S. P. (2020). Investigating the Impact of Network Parameters on Wormhole Attack with ANODR Routing Protocol in MANET. i-manager’s Journal on Wireless Communication Networks , 8(4), 1-6. https://doi.org/10.26634/jwcn.8.4.17611

Abstract

The MANET is a network which can organize the mobile ad hoc network nodes dynamically with temporary and arbitrary topologies. This MANET offers many applications in current communication technology. The security and privacy in MANET is a major challenging issue as wireless communication is more vulnerable to security attacks. In this network the individual node operates like transmitter, receiver and router. Moreover, due to openness of the network, there are more chances for malicious users to enter into the network which creates an illusion. So that the individual node understands the data, even if it is sensed from original sender, malicious sender and receiver node behavior. Hence the malicious users create more data loss. So, these wormhole attacks creates network related issues and degrade the MANET efficiency. Major research is now concentrated on the behavior which makes the normal node to act as wormhole to degrade the network performance. In this paper, several parameters are studied and some parameters makes a node to become a wormhole. Experiments are conducted using popular network simulator – “Qualnet Simulator”. The results clearly show the impact of wormhole on the performance of MANETs.

References

[1]. Ahuja, R., Ahuja, A. B., & Ahuja, P. (2013, December). Performance evaluation and comparison of AODV and DSR routing protocols in MANETs under wormhole attack. In 2013, IEEE Second International Conference on Image Information Processing (ICIIP-2013) (pp. 699-702). IEEE. https://doi.org/10.1109/ICIIP.2013.6707686

[2]. Alani, M. M. (2014, November). MANET security: A survey. In 2014, IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2014) (pp. 559-564). IEEE. https://doi.org/10.1109/ICCSCE.2014.7072 781

[3]. As'adi, H., Haddad, A., Jamshidi, A. (2018). A new statistical method for wormhole attack detection in th MANETs. In 2018, 15 International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC). https://doi.org/10.1109/ISCISC.2018. 8546943

[4]. Cabrera, A. T., Mozos, A. G., & Casilari, E. (2010, September). On the suitability of using the residual lifetime as a routing metric in manets. In Telecommunications: The st Infrastructure for the 21 Century (pp. 1-6).

[5]. Douceur, J. R. (2002). The Sybil attack. In Proceedings st of the 1 International Workshop on Peer-to-Peer Systems (IPTPS'02) (pp. 251-260).

[6]. Hu, Y. C., Perrig, A., & Johnson, D. B. (2003a, March). Packet leashes: A defense against wormhole attacks in wireless networks. In IEEE INFOCOM 2003 Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (Vol. 3, pp. 1976-1986). IEEE.

[7]. Hu, Y. C., Perrig, A., & Johnson, D. B. (2003b, September). Rushing attacks and defense in wireless ad nd hoc network routing protocols. In Proceedings of the 2 ACM workshop on Wireless security (pp. 30-40).

[8]. Jha, H. N., Gupta, S., & Maity, D. (2020). Effect of wormhole attacks on MANET. In Design Frameworks for Wireless Networks (pp. 177-195). Singapore: Springer. https://doi.org/10.1007/978-981-13-9574-1

[9]. Joshi, P. (2011). Security issues in routing protocols in MANETs at network layer. Procedia Computer Science, 3, 954-960. https://doi.org/10.1016/j.procs.2010.12.156

[10]. Karlsson, J., Dooley, L. S., Pulkkis, G. (2011). A new MANET wormhole detection algorithm based on traversal time and hop count analysis. International Journal of Sensors, 11(12), 11122-11140. https://doi.org/10.3390/s11 1211122

[11]. Kong, J., & Hong, X. (2003, June). ANODR: Anonymous on demand routing with untraceable routes th for mobile ad-hoc networks. In Proceedings of the 4 ACM International Symposium on Mobile Ad-Hoc Networking & Computing (pp. 291-302). https://doi.org/10.1145/7784 15.778449

[12]. Rai, A., RanjanTewari, R., & Upadhyay, S. K. (2010). Different types of attacks on integrated MANET-internet communication. International Journal of Computer Science and Security (IJCSS), 4(3), 265-274.

[13]. Sarkar, D., Choudhury, S., & Majumder, A. (2018). Enhanced-Ant-AODV for optimal route selection in mobile ad-hoc network. Journal of King Saud University-Computer and Information Sciences, 1–25. https://doi.org/10.1016/j. jksuci.2018.08.013

[14]. Xiao, H., Ibrahim, D. M., & Christianson, B. (2014, April). Energy consumption in mobile ad hoc networks. In 2014, IEEE Wireless Communications and Networking Conference (WCNC) (pp. 2599-2604). IEEE. https://doi. org/10.1109/WCNC.2014.6952818

[15]. Yang, H., Luo, H., Ye, F., Lu, S., & Zhang, L. (2004). Security in mobile ad hoc networks: Challenges and solutions. IEEE Wireless Communications, 11(1), 38-47. https://doi.org/10.1109/MWC.2004.1269716

Full Article (HTML)

Pdf

Research Paper

Enhancing Qos in Wimax using Opnet Simulator

Palla Sravani* , S. Pallam Setty **

*-** Department of Computer Science and Systems Engineering, Andhra University College of Engineering, Visakhapatnam, Andhra Pradesh, India.

Sravani, P., and Setty, S. P. (2020). Enhancing Qos in Wimax using Opnet Simulator. i-manager’s Journal on Wireless Communication Networks , 8(3), 7-14. https://doi.org/10.26634/jwcn.8.4.17704

Abstract

In this paper, an attempt has been made to provide QoS in WiMAX IEEE 802.16 with fairness which is a challenging issue due to limited bandwidth and limited energy. To overcome these an attempt has been made in OPNET (Optimized Network Engineering Tool) which is a powerful network simulator. A appropriate classification approach in modern communication is on hand that is the usage of QoS managed via the community network operator. By developing a new System methodology to QoS with fairness by means of incorporating some principle concepts like UGS, ERTPS, RTPS, BE for VoIP, Video, HTTP to provide equal bandwidth allocation to all users in network. To get QoS along with fairness in WiMAX network, we need to overcome the issues like limited bandwidth and limited energy. This methodology proposes some other planning scheme mirroring the prerequisite of RTPS and the distinct NRTPS associations that accomplish the best ideal QoS requirement, excluding the immoderate aid consumption due to the fact that it maximizes delay for low-throughput applications as well as achieves low average, offers fairness regardless of version variation in server potential, and computationally efficient.

References

[1]. Alavi, H. S., Mojdeh, M., & Yazdani, N. (2005, October). A quality of service architecture for IEEE 802.16 standards. In 2005 Asia-Pacific Conference on Communications (pp. 249-253). IEEE. https://doi.org/10.1109/APCC.2005.15540 58

[2]. Chen, J., Jiao, W., & Guo, Q. (2005, September). Providing integrated QoS control for IEEE 802.16 broadband wireless access systems. In IEEE Vehicular Technology Conference (Vol. 62, No. 2, p. 1254). IEEE.

[3]. Cicconetti, C., Lenzini, L., Mingozzi, E., & Eklund, C. (2006). Quality of service support in IEEE 802.16 networks. IEEE Network, 20(2), 50-55. https://doi.org/10.1109/MNET. 2006.1607896

[4]. Guérin, R., & Peris, V. (1999). Quality-of-service in packet networks: basic mechanisms and directions. Computer Networks, 31(3), 169-189. https://doi.org/ 10.1016/S0169-7552(98)00261-X

[5]. Khalil, A., & Ksentini, A. (2007). Classification of the uplink scheduling algorithms in IEEE 802.16. In Proceedings of International Workshop on Dynamic Networking (IWDYN'07).

[6]. Lee, H., Kwon, T., Cho, D. H., Lim, G., & Chang, Y. (2006, May). Performance analysis of scheduling algorithms for rd VoIP services in IEEE 802.16 e systems. In 2006 IEEE 63 Vehicular Technology Conference (Vol. 3, pp. 1231-1235). IEEE. https://doi.org/10.1109/VETECS.2006.1683031

[7]. Mahmood, A. N. (2018). Study of simulation comparing WiMAX network fixed and mobile using OPNET modeler. International Journal of Computer Applications Foundation of Computer Science (FCS), 179(12), 42-47. https://doi.org/ 10.5120/ijca2018916147

[8]. Mai, Y. T., Yang, C. C., & Lin, Y. H. (2007, February). Cross-layer QoS framework in the IEEE 802.16 network. In The 9th International Conference on Advanced Communication Technology (Vol. 3, pp. 2090-2095). IEEE. https://doi.org/ 10.1109/ICACT.2007.358784

[9]. Shamna, A. R., & Shanthi, S. A. (2020). Performance comparison of MIMO-OFDM using Weiner Hammerstein and CNN equalizers. Journal of Critical Reviews, 7(6), 195-201.

Full Article (HTML)

Pdf

Research Paper

Applications of Particle Swarm Optimization in Wireless Communication System

Enem Theophilus Aniemeka * , Oyajide Depo Olukayode **

* Department of Computer Science, Air Force Institute of Technology, Nigerian Air Force Base, Kaduna, Nigeria.

** Department of Electrical and Electronic Engineering, Osun State Polytechnic Iree, Osun, Nigeria.

Aniemeka, E. T., and Olukayode, O. D. (2020). Applications of Particle Swarm Optimization in Wireless Communication System. i-manager’s Journal on Wireless Communication Networks , 8(4), 15-19. https://doi.org/10.26634/jwcn.8.4.17178

Abstract

Particle Swarm Optimization (PSO) is a popular technique used to solve optimization problems in WSNs due to its simplicity, high quality of solution, fast convergence and insignificant computational burden. However, iterative nature of PSO can prohibit its use for high-speed real-time applications, especially if optimization needs to be carried out frequently. This paper outlines issues in WSNs, introduces PSO and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues. The objective of this paper is to give a flavor of PSO to researchers in WSN, and to give a qualitative treatment of optimization problems in WSNs to PSO researchers in order to promote PSO in WSN applications.

References

[1]. Ait-Aoudia, S., Guerrout, E. H., & Mahiou, R. (2014, July). Medical image segmentation using particle swarm th optimization. In 2014, 18 International Conference on Information Visualisation (pp. 287-291). IEEE. https://doi. org/9.277/IV.2014.68

[2]. Arin, A., & Rabadi, G. (2017). Integrating estimation of distribution algorithms versus Q-learning into Meta-RaPS for solving the 0-1 multidimensional knapsack problem. Computers & Industrial Engineering, 112, 706-720. https:// doi.org/10.1016/j.cie.2016.10.022

[3]. Ha, C., & Kuo, W. (2006). Reliability redundancy allocation: An improved realization for nonconvex nonlinear programming problems. European Journal of Operational Research, 171(1), 24-38.

[4]. Ma, M., Zhang, Y., Tian, H., & Lu, Y. (2008, October). A fast SAR image segmentation algorithm based on particle swarm optimization and grey entropy. In 2008 Fourth International Conference on Natural Computation (Vol. 4, pp. 8-12). IEEE. https://doi.org/10.1109/ICNC.2008.577

[5]. Marini, F., & Walczak, B. (2015). Particle swarm optimization (PSO): A tutorial. Chemometrics and Intelligent Laboratory Systems, 149, 153-165. https://doi.org/10.1016/ j.chemolab.2015.08.020

[6]. Mehmood, R. M., & Lee, H. J. (2016, July). Emotion recognition from EEG brain signals based on particle swarm optimization and genetic search. In 2016, IEEE International Conference on Multimedia & Expo Workshops (ICMEW) (pp. 1-5). IEEE. https://doi.org/10.1109/ICMEW.201 6.7574682

[7]. Shin, Y., & Kita, E. (2017). Solving two-dimensional packing problem using particle swarm optimization. Computer Assisted Methods in Engineering and Science, 19(3), 241-255. Retrieved from https://cames.ippt.pan.pl/ index.php/cames/article/view/92

[8]. Suresh, S., & Lal, S. (2017). Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images. Applied Soft Computing, 55, 503-522.

[9]. Tavakkoli, M. R., Safari, J., & Sassani, F. (2018). Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm. Reliability Engineering and System Safety, 93, 550-589. https://doi.org/10.1016/j.asoc.2017.02.005

[10]. You, M., & Jiang, T. (2014). New method for target identification in a foliage environment using selected bispectra and chaos particle swarm optimisation-based support vector machine. IET Signal Processing, 8(1), 76-84.

[11]. Zeng, K., & Dong, M. A novel cuboid technique for actual noise attenuation from heart sound measurements with particle swarm optimization. Applications Expert Systems, 41(15), 6839-6847. https://doi.org/10.1016/y. eswa.2014.05.006

Full Article (HTML)

Pdf

Research Paper

Simulation of Time Evaluation of Blockchain based Healthcare Data from Security Perspective

Rashid Husain* , Rabia Khan , Shashank Saroop *

* Department of Mathematics and Computer Science, Sule Lamido University, Kafin Hausa, Jigawa, Nigeria.

Punjab Technical University, Meerut, Uttar Pradesh, India.

* *** Department of Computer Science and Engineering, Amity University, Gurugram, Haryana, India.

Husain, R., Khan, R., and Saroop, S. (2020). Simulation of Time Evaluation of Blockchain based Healthcare Data from Security Perspective. i-manager’s Journal on Wireless Communication Networks , 8(4), 20-26. https://doi.org/10.26634/jwcn.8.4.17749

Abstract

The term block chain has been referred as the disruptive innovation in computing. The interest in blockchain technology has been growing since the idea developed in 2008. However, healthcare is one of the major applications in blockchain which has lots of concern over the data security. To make critical information secure the use of blockchain technology came up. Accordingly, more researchers along with the solution of blockchain technology in healthcare data defend the data from tampering and leakage. In this paper, we have done the simulation of processing time assessment of blockchain technology with various secure hash algorithms. This analysis provide better outlook to the user for using these new security framework in an constrained hardware environment.

References

[1]. Al Omar, A., Rahman, M. S., Basu, A., & Kiyomoto, S. (2017, December). Medibchain: A blockchain based privacy preserving platform for healthcare data. In International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage (pp. 534-543). Cham: Springer.

[2]. Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016, August). Medrec: Using blockchain for medical data nd access and permission management. In 2016 2 International Conference on Open and Big Data (OBD) (pp. 25-30). IEEE. https://doi.org/10.1109/OBD.2016.11

[3]. Chen, Y., Ding, S., Xu, Z., Zheng, H., & Yang, S. (2019). Blockchain-based medical records secure storage and medical service framework. Journal of Medical Systems, 43(1), 5. https://doi.org/10.1007/s10916-018-1121-4

[4]. Fan, K., Wang, S., Ren, Y., Li, H., & Yang, Y. (2018). Medblock: Efficient and secure medical data sharing via blockchain. Journal of Medical Systems, 42(8). https://doi. org/10.1007/s10916-018-0993-7

[5]. Garcia, F. D., Oswald, D., Kasper, T., & Pavlidès, P. (2016). Lock it and still lose it-on the (in) security of automotive remote keyless entry systems. In 25th {USENIX} Security Symposium ({USENIX} Security 16).

[6]. Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42(7). https://doi.org/10.1007/s10916-018-0982-x

[7]. Lamport, L., Shostak, R., & Pease, M. (1982). The Byzantine generals problem. ACM Transactions on Progamming Languages and Systems, 4(3), 382-401.

[8]. Li, H., Zhu, L., Shen, M., Gao, F., Tao, X., & Liu, S. (2018). Blockchain-based data preservation system for medical data. Journal of Medical Systems, 42(8). https://doi.org/10. 1007/s10916-018-0997-3

[9]. Liang, X., Zhao, J., Shetty, S., Liu, J., & Li, D. (2017, October). Integrating blockchain for data sharing and collaboration in mobile healthcare applications. In 2017 th IEEE 28 Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 1-5). IEEE.

[10]. Mukhopadhyay, U., Skjellum, A., Hambolu, O., Oakley, J., Yu, L., & Brooks, R. (2016, December). A brief th survey of cryptocurrency systems. In 2016 14 Annual Conference on Privacy, Security and Trust (PST) (pp. 745- 752). IEEE.

[11]. Nakamoto, S. (2008). Bitcoin: Apeer-to-peer electronic cash system. Retrieved from http://www.bitcoin. org/bitcoin.pdf,2008

[12]. Seebacher, S., & Schüritz, R. (2017, May). Blockchain technology as an enabler of service systems: A structured literature review. In International Conference on Exploring Services Science (pp. 12-23). Cham: Springer.

[13]. Tanenbaum, A. S., & Van Steen, M. (2007). Distributed systems: Principles and paradigms. Prentice-Hall.

[14]. Tschorsch, F., & Scheuermann, B. (2016). Bitcoin and beyond: A technical survey on decentralized digital currencies. IEEE Communications Surveys & Tutorials, 18(3), 2084-2123.

[15]. Uddin, M. A., Stranieri, A., Gondal, I., & Balasubramanian, V. (2018). A patient agent to manage blockchains for remote patient monitoring. Studies in Health Technology and Informatics, 254, 105-115.

[16]. Xia, Q., Sifah, E. B., Smahi, A., Amofa, S., & Zhang, X. (2017). BBDS: Blockchain-based data sharing for electronic medical records in cloud environments. Information, 8(2), 44-60. https://doi.org/10.3390/info8020044

[17]. Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology? - A systematic review. PloS One, 11(10). https://doi.org/10.1371/journal.pone.0163477

Full Article (HTML)

Pdf

Research Paper

EE-APTSP: Evolution Node Life Time for WSN

Thamizhmaran K.*

Department of Electronics and Communication Engineering, Government College of Engineering, Bodinayakkanur, Theni, Tamil Nadu, India.

Thamizhmaran, K. (2020). EE-APTSP: Evolution Node Life Time for WSN. i-manager’s Journal on Wireless Communication Networks , 8(4), 27-35. https://doi.org/10.26634/jwcn.8.4.17823

Abstract

A Wireless Sensor Network (WSN) is an aggregation of sensor nodes which are remotely deployed in large numbers and operate the environmental condition and have limited energy resource. In most of the hierarchical routing protocols, the cluster head (CH) selection is on the basis of random probability equation. There is a scope to reduce the energy dissipation by improving CH selection procedure. This research paper proposed a multi hop hierarchical routing protocol called Energy Efficient - Adaptive Periodic Threshold Sensitive Protocol (EE-APTSP), and makes use of evolutionary algorithm for improving cluster head selection of routing protocol in the sensor networks. The concept of relay node is introduced, which acts as an intermediary between Cluster Head (CH) and Base Station (BS) to ease the communication between the CH and BS. The simulation results obtained supports that our proposed algorithm is efficient in terms of network lifetime. APTSP based theory that can be used to create faster, smaller, and more energetic and efficient sensitive threshold. Network Simulator (NS2) is used to implement and test the proposed system. The proposed periodic sensitive protocol provides more energy with secured transmission, further it reduces routing overhead, improves packet delivery ratio and throughput.

References

[1]. Aslam, N., Phillips, W., Robertson, W., & Sivakumar, S. (2011). A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networks. Information Fusion, 12(3), 202-212. https://doi.org/10.1016 /j.inffus.2009.12.005

[2]. Bakr, B. A., & Lilien, L. (2011, June). Extending wireless sensor network lifetime in the LEACH-SM protocol by spare th selection. In 2011 5 International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (pp. 277-282). IEEE. https://doi.org/10.1109/ IMIS.2011.142

[3]. Han, Z., Wu, J., Zhang, J., Liu, L., & Tian, K. (2014). A general self-organized tree-based energy-balance routing protocol for wireless sensor network. IEEE Transactions on Nuclear Science, 61(2), 732-740. https:// doi.org/10.1109/TNS.2014.2309351

[4]. 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. https://doi.org/10.1109/TWC.2002.804190

[5]. Karimi, M., Naji, H. R., & Golestani, S. (2012, May). Optimizing cluster-head selection in wireless sensor networks using genetic algorithm and harmony search th algorithm. In 20 Iranian Conference on Electrical Engineering (ICEE2012) (pp. 706-710). IEEE. https://doi.org/ 10.1109/IranianCEE.2012.6292445

[6]. Kumar, D., Aseri, T. C., & Patel, R. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 662- 667. https://doi.org/10.1016/j.comcom.2008.11.025

[7]. Lindsey, S., & Raghavendra, C. S. (2002, March). PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings of IEEE aerospace conference (Vol. 3, pp. 3) IEEE. https://doi.org/10.1109/AERO.2002. 1035242

[8]. Mahajan, L., & Sharma, N. (2014, February). Improving the stable period of WSN using dynamic Stable leach Election Protocol. In 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT) (pp. 393-400). IEEE. https://doi.org/ 10.1109/ICICICT.2014.6781315

[9]. Manjeshwar, A., & Agrawal, D. P. (2001, April). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In International Parallel and Distributed Processing Symposium (vol. 1, pp. 189-195).

[10]. Manjeshwar, A., & Agrawal, D. P. (2002, April). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In Parallel and Distributed Processing Symposium, International (Vol. 3, pp. 0195b). IEEE Computer Society.

[11]. Naregal, K., & Gudnavar, A. (2012, December). Improved cluster routing protocol for wireless sensor th network through simplification. In 2012 18 International Conference on Advanced Computing and Communications (ADCOM) (pp. 1-3). IEEE. https://doi.org/10.1109/ADCOM. 2012.6563576

[12]. Peiravi, A., Mashhadi, H. R., & Hamed Javadi, S. (2013). An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm. International Journal of Communication Systems, 26(1), 114-126. https://doi.org/10.1002/dac.1336

[13]. Salim, A., Osamy, W., & Khedr, A. M. (2014). IBLEACH: intra-balanced LEACH protocol for wireless sensor networks. Wireless Networks, 20(6), 1515-1525. https:// doi.org/10.1007/s11276-014-0691-4

[14]. Saxena, T. K., Kanojia, K., & Pandey, A. (2019). Multigeographical threshold based routing protocol to enhance network lifetime for wireless sensor networks. International Journal of Advance Research and Innovative Ideas in Education, 5(6), 14-28.

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

Current Issue Vol. 12 Issue 1

Most Read

Most Cited

Volume 8 Issue 4 January - June 2020

Investigating the Impact of Network Parameters on Wormhole Attack with ANODR Routing Protocol in MANET

Dr. Uppe Nanaji* , S. Pallam Setty **

*-** Department of Computer Science and Software Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.

Nanaji, U., and Setty, S. P. (2020). Investigating the Impact of Network Parameters on Wormhole Attack with ANODR Routing Protocol in MANET. i-manager’s Journal on Wireless Communication Networks , 8(4), 1-6. https://doi.org/10.26634/jwcn.8.4.17611

Abstract

References

Full Article (HTML)

Pdf

Enhancing Qos in Wimax using Opnet Simulator

Palla Sravani* , S. Pallam Setty **

*-** Department of Computer Science and Systems Engineering, Andhra University College of Engineering, Visakhapatnam, Andhra Pradesh, India.

Sravani, P., and Setty, S. P. (2020). Enhancing Qos in Wimax using Opnet Simulator. i-manager’s Journal on Wireless Communication Networks , 8(3), 7-14. https://doi.org/10.26634/jwcn.8.4.17704

Abstract

References

Full Article (HTML)

Pdf

Applications of Particle Swarm Optimization in Wireless Communication System

Enem Theophilus Aniemeka * , Oyajide Depo Olukayode **

* Department of Computer Science, Air Force Institute of Technology, Nigerian Air Force Base, Kaduna, Nigeria. ** Department of Electrical and Electronic Engineering, Osun State Polytechnic Iree, Osun, Nigeria.

Aniemeka, E. T., and Olukayode, O. D. (2020). Applications of Particle Swarm Optimization in Wireless Communication System. i-manager’s Journal on Wireless Communication Networks , 8(4), 15-19. https://doi.org/10.26634/jwcn.8.4.17178

Abstract

References

Full Article (HTML)

Pdf

Simulation of Time Evaluation of Blockchain based Healthcare Data from Security Perspective

Rashid Husain* , Rabia Khan **, Shashank Saroop ***

* Department of Mathematics and Computer Science, Sule Lamido University, Kafin Hausa, Jigawa, Nigeria. ** Punjab Technical University, Meerut, Uttar Pradesh, India. *** *** Department of Computer Science and Engineering, Amity University, Gurugram, Haryana, India.

Husain, R., Khan, R., and Saroop, S. (2020). Simulation of Time Evaluation of Blockchain based Healthcare Data from Security Perspective. i-manager’s Journal on Wireless Communication Networks , 8(4), 20-26. https://doi.org/10.26634/jwcn.8.4.17749

Abstract

References

Full Article (HTML)

Pdf

EE-APTSP: Evolution Node Life Time for WSN

Thamizhmaran K.*

Department of Electronics and Communication Engineering, Government College of Engineering, Bodinayakkanur, Theni, Tamil Nadu, India.

Thamizhmaran, K. (2020). EE-APTSP: Evolution Node Life Time for WSN. i-manager’s Journal on Wireless Communication Networks , 8(4), 27-35. https://doi.org/10.26634/jwcn.8.4.17823

Abstract

References

Full Article (HTML)

Pdf

* Department of Computer Science, Air Force Institute of Technology, Nigerian Air Force Base, Kaduna, Nigeria.

** Department of Electrical and Electronic Engineering, Osun State Polytechnic Iree, Osun, Nigeria.

Rashid Husain* , Rabia Khan , Shashank Saroop *

* Department of Mathematics and Computer Science, Sule Lamido University, Kafin Hausa, Jigawa, Nigeria.

Punjab Technical University, Meerut, Uttar Pradesh, India.

* *** Department of Computer Science and Engineering, Amity University, Gurugram, Haryana, India.