RECENT RESEARCH ARTICLES IN WIRELESS SENSOR NETWORKS
-RECOMMENDED READING
International Journal of Wireless & Mobile Networks (IJWMN)
ISSN:0975-3834 [Online]; 0975-4679 [Print]
http://airccse.org/journal/ijwmn.html
CHANNEL MAXIMIZATION IN WIRELESS BACKHAUL BASED HETNETS
Mostafa Hefnawi
Royal Military College of Canada,Canada.
ABSTRACT
In this paper, we consider the optimization of wireless capacity-limited backhaul links in future heterogeneous networks (HetNets). We assume that the HetNet is formed with one macro-cell base station (MBS), which is associated with multiple small-cell base stations (SBSs). It is also assumed both the MBS and the SBSs are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. For the backhaul links, we propose to use a capacity-aware beamforming scheme at the SBSs and MRC at the MBS. Using particle swarm optimization (PSO), each SBS seeks the optimal transmit weight vectors that maximize the backhaul uplink capacity and the access uplinks signal-tointerference plus noise ratio (SINR). The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware backhaul link scheme achieves similar or better performance than traditional wireless backhaul links and requires considerably less computational complexity.
KEYWORDS
HetNets, wireless backhaul, cognitive radio, Massive MIMO, multiuser MIMO, PSO.
For More Details :
http://aircconline.com/ijwmn/V9N3/9317ijwmn05.pdf
Volume Link :
http://airccse.org/journal/jwmn_current17.html
REFERENCES
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[2] Zhen Gao, Linglong Dai, De Mi, Zhaocheng Wang, Muhammad Ali Imran, and Muhammad Zeeshan Shakir, “MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network,” IEEE Wireless Communications, vol. 22, no. 5, pp. 13-21, Oct. 2015.
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AUTHORS
Dr. Hefnawi is currently a professor and the Chair of Graduate Studies Committee in the Department of Electrical and Computer Engineering at the Royal Military College of Canada. Dr. Hefnawi is a licensed professional engineer in the province of Ontario. He is a contributing author of several refereed journal, book chapters, and proceeding papers in the areas of wireless communications. His research interest includes cognitive radio, wireless sensor network, massive MIMO, cooperative MIMO, multiuser MIMO, and smart grid communications.
VIRTUAL ARCHITECTURE AND ENERGY EFFICIENT ROUTING PROTOCOLS FOR 3D WIRELESS SENSOR NETWORKS
Vianney Kengne Tchendji1,Jean Frederic Myoupo2, Pauline Laure Fotso3 and Ulrich Kenfack Zeukeng1,
1University of Dschang, Cameroon, 2University of Picardie Jules Verne, France and 3University of Yaounde 1, Cameroon
ABSTRACT
This paper proposes a virtual architecture for three-dimensional (3D) wireless sensor networks (WSNs), a dynamic coordinate system, and a scalable energy-efficient training protocol for collections of nodes deployed in the space that are initially anonymous, asynchronous, and unaware of their initial location. The 3D WSNs considered comprise massively deployed tiny energy-constrained commodity sensors and one or more sink nodes that provide an interface to the outside world. The proposed architecture is a generalization of a two-dimensional virtual architecture previously proposed in the literature, in which a flexible and intuitive coordinate system is imposed onto the deployment area and the anonymous nodes are partitioned into clusters where data can be gathered from the environment and synthesized under local control. The architecture solves the hidden sensors problem that occurs because of irregularities in rugged deployment areas or environments containing buildings by training the network of nodes arbitrarily dispersed in the 3D space. In addition, we derive two simple and energy-efficient routing protocols, respectively for dense and sparse networks, based on the proposed dynamic coordinate system. They are used to minimize the power expended in collecting and routing data to the sink node, thus increasing the lifetime of the network.
KEYWORDS
Wireless Sensor Network, Self-organization, Training protocol, Energy-efficient Routing Protocol.
For More Details :
http://aircconline.com/ijwmn/V9N5/9517ijwmn07.pdf
Volume Link :
http://airccse.org/journal/jwmn_current17.html
REFERENCES
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AUTHORS
Vianney Kengne Tchendji is a Senior Lecturer of Computer Science at the University of Dschang, Dschang, Cameroon. He received his PhD in Computer Science from the University of Picardie-Jules Verne, Amiens, France, in 2014. His current research interests include network virtualization, parallel algorithms and architectures, scheduling, wireless communication, ad hoc and sensor networking.
A DYNAMIC ADDRESSING PROTOCOL ON CODE MESSAGES FOR AN UNDERWATER WIRELESS HALF DUPLEX NETWORKS OF AUTONOMOUS SENSORS
Alexander Dikarev, Stanislav Dmitriev, Vitaliy Kubkin and Arthur Abelentsev,
Underwater Communication and Navigation Laboratory, Russia
ABSTRACT
This paper presents the new protocol for the organization of dynamic addressing nodes in the underwater wireless networks. In view of the extremely limited frequency band and significant delays inherent in the underwater acoustic data transmission channel, as well as the nonlinearity of the propagation paths of the acoustic signal in water, an approach is proposed for constructing a dynamic addressing protocol based on avoiding collisions at the receiving point. The protocol takes into account the peculiarities of the physical layer of the data transmission and is designed for servicing the network of autonomous non-synchronized nodes.
KEYWORDS
Network Protocols, Underwater Wireless Network,underwater acoustic communication.
For More Details :
http://aircconline.com/ijwmn/V9N6/9617ijwmn03.pdf
Volume Link : http://airccse.org/journal/jwmn_current17.html
REFERENCES
[1] Akyildiz, I.F. and D. Pompili, 2005. Underwater Acoustic sensor Networks: Research Challenges A survey, pp: 257-279
[2] Heidemann J, Li Yuan, Syed Affan, Wills Jack, Ye Wei, 2005. Underwater Sensor Networking: Research Challenges and Potential Applications, USC/ISI Technical Report ISI-TR-2005-603
[3] Manjula R.B., Sunilkumar S. Manvi, 2011. Issues in Underwater Acoustic Sensor Networks, International Journal of Computer and Electrical Engineering, Vol.3, No. 1, February, 2011, pp.101- 102
[4] Jun Liu, Zhong Zhou, Zheng Peng, Jun-Hong Cui, Mobi-Synch: Efficient Time Synchronization for Mobile Underwater Sensor Networks, 2010, UCONN CSE Technical Report: UbiNet-TR10-01, University of Connecticut, Storrs, CT 06269
[5] Ying Guo, Yutao Liu. Time synchronization for Mobile Underwater Sensor Networks. Journal of networks, vol. 8, NO. 1, January 2013
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[8] Dikarev A., Griffiths A., Watson S., Lennox B., Green P. R., Combined multiuser acoustic communication and localization system for µAUVs operating in confined underwater environments, 2015. IFAC Workshop on Navigation, Guidance and Control. Girona, Spain
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[11] Long Cheng, Chengdong Wu, Yunzhou Zhang, Hao Wu,MengxinLi,CarstenMaple.,
[12]A Survey of Localization in Wireless Sensor Network. Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2012, Article ID 962523, 12 pages doi:10.1155/2012/962523
AUTHORS
Alexander Dikarev received his M.Eng in Launching equipment of rockets and cosmic apparatus from Volgograd Technical State University, Russia. He has 10 years experience in underwater acoustic communication and navigation system design and development: in Research Insitute of Hydroacoustic Communications (Volgograd, Russia), The University Of Manchester (UK), now he is R&D Director in Underwater communication & Navigation laboratory (Moscow, Russia)
Stanislav Dmitriev received his M.Sc in Radiophysics in Volgograd State University, Russia. He has 10 years of experience in Underwater Acoustic communication & navigation system design & development: in Research Insitute of Hydroacoustic Communications (Volgograd, Russia), now he is Engineering Director in Underwater Communication & Navigation laboratory (Moscow, Russia).
Vitaly Kubkin received his M.Eng in Volgograd Technical State University, Russia. He has 10 years of experience in Underwater Acoustic communication & navigation system design & development: in Research Insitute of Hydroacoustic Communications (Volgograd, Russia), now he is Senior Researcher in Underwater Communication & Navigation laboratory (Moscow, Russia).
Artur Abelentsev received his M.Ec in Management in Kuban State Technological University, Russia. He has more than 15 years of experience in IT, embedded system architect and research management. He is a CEO in Underwater Communication & Navigation laboratory (Moscow, Russia).
BLACKLIST MANAGEMENT USING A VERIFICATION REPORT TO IMPROVE THE ENERGY EFFICIENCY OF CFFS IN WSNS
JungSub Ahn and TaeHo Cho,
Sungkyunkwan University, Republic of Korea
ABSTRACT
Recently, the applications scope of Wireless Sensor Networks (WSNs) has been broadened. WSN communication security is important because sensor nodes are vulnerable to various security attacks when deployed in an open environment. An adversary could exploit this vulnerability to inject false reports into the network. En-route filtering techniques have been researched to block false reports. The CFFS scheme filters the false report by collaboratively validating the report by clustering the nodes. However, CFFS is not considered effective against repetitive attacks. Repeated attacks have a significant impact on network lifetime. In this paper, we propose a method to detect repetitive attacks with cluster-based false data filtering and to identify the compromised nodes and quickly block them. The proposed scheme uses fuzzy logic to determine the distribution of additional keys according to the network conditions, thereby improving energy efficiency.
KEYWORDS
WSN Security, Fabricated Report Verification, WSN Lifetime Extension, Enhanced CFFS
For More Details :
http://aircconline.com/ijwmn/V10N4/10418ijwmn04.pdf
Volume Link :
http://airccse.org/journal/jwmn_current18.html
REFERENCES
[1] Akyildiz, Ian F., et al. “A survey on sensor networks.” IEEE communications magazine 40.8 (2002): 102-114.
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countermeasures.” Sensor Network Protocols and Applications, 2003. Proceedings of the First IEEE. 2003 IEEE International Workshop on. IEEE, 2003.
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[9] Mohammadi, Shahriar, and Hossein Jadidoleslamy. “A comparison of physical attacks on wireless sensor networks.” International Journal of Peer to Peer Networks 2.2 (2011): 24-42.
[10] Ahn, Jung-Sub, and Tae-Ho Cho. “PREVENTION METHOD OF FALSE REPORT GENERATION IN CLUSTER HEADS FOR DYNAMIC EN-ROUTE FILTERING OF WIRELESS SENSOR NETWORKS.”
[11] Kumar, Alok, and Alwyn Roshan Pais. “En-route filtering techniques in wireless sensor networks: a survey.” Wireless Personal Communications 96.1 (2017): 697-739.
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[16] Liu, Zhixiong, et al. “A Cluster-Based False Data Filtering Scheme in Wireless Sensor Networks.” Adhoc & Sensor Wireless Networks 23 (2014). International Journal of Wireless & Mobile Networks (IJWMN) Vol. 10, No. 4, August 2018
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[22] https://www.eol.ucar.edu/isf/facilities/isa/internal/CrossBow/DataSheets/mica2.pdf
[23] Nam, Su Man, and Tae Ho Cho. “Context-aware architecture for probabilistic voting-based filtering scheme in sensor networks.” IEEE Transactions on Mobile Computing 16.10 (2017): 2751-2763.
AUTHORS
Jung Sub Ahn received the B.S. degree in computer engineering from Kyunil University in 2016 and now doing Ph.D. degree in Department of Electrical and Computer Engineering from Sungkyunkwan University. His research interests include wireless sensor network security, modelling & simulation, IoT security
Tea Ho Cho received a Ph.D. degree in Electrical and Computer Engineering from the University of Arizona, USA, in 1993, and B.S. and M.S. degrees in Electrical and Computer Engineering from Sungkyunkwan University, Repulic of Korea, and the University of Alabama, USA, respectively. He is currently a Professor in the College of Software at Sungkyunkwan University, Korea.
EFFICIENTLY SECURE BROADCASTING IN 5G WIRELESS FOG-BASED-FRONTHAUL NETWORKS
Nabeel I. Sulieman and Richard D. Gitlin,
University of South Florida, USA.
ABSTRACT
Enhanced Diversity and Network Coding (eDC-NC), the synergistic combination of Diversity and modified Triangular Network Coding, was introduced recently to provide efficient and ultra-reliable networking with near-instantaneous fault recovery. In this paper it is shown that eDC-NC technology can efficiently and securely broadcast messages in 5G wireless fog-computing-based Radio Access Networks (F-RAN). In particular, this work is directed towards demonstrating the ability of eDC-NC technology to more efficiently provide secure messages broadcasting than standardized methods such as Secure Multicasting using Secret (Shared) Key Cryptography, such that the adversary has no ability to acquire information even if they wiretap the entire F-RAN network (except of course the source and destination nodes). Our results show that using secure eDC-NC technology in F-RAN fronthaul network will enhance secure broadcasting and provide ultra-reliability networking, near-instantaneous fault recovery, and retain the throughput benefits of Network Coding.
KEYWORDS
5G, Diversity Coding, Triangular Network Coding, F-RAN, Secure Multicasting
For More Details :
http://aircconline.com/ijwmn/V10N3/10318ijwmn01.pdf
Volume Link :
http://airccse.org/journal/jwmn_current18.html
REFERENCES
[1] N. Cai and W. Yeung, “Secure Network Coding”, IEEE International Symposium on Information Theory (ISIT), Lausanne, Switzerland, July 2002, pp. 323.
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[6] N. I. Sulieman, E. Balevi, and R. D. Gitlin, “Near-instant link failure recovery in 5G wireless Fog-basefronthaul networks,” IEEE Wireless Telecommunication Symposium, Phoenix, AZ, April 2018.
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AUTHORS
Nabeel I. Sulieman received his B.S. degree in Electrical Engineering from University of Baghdad, Baghdad – Iraq in 1998, he was one of the ten highest ranked students in the Electrical Engineering Department, and he received his M.S. degree with merit in wireless communications systems from Brunel University, London – UK in 2008. From 2002 until 2014, he worked for Iraqi Telecommunication and Post Company as a technical support engineer. In addition, he worked as an instructor for short technical courses in Higher Institute of Telecommunications-Baghdad-Iraq. Currently, he is a Ph.D. Candidate in Electrical Engineering Department at the University of South Florida in the Innovations in Wireless Information Networking Laboratory (iWINLAB) under the supervision of Dr. Richard Gitlin, and his research interests include Diversity Coding, Network Coding, 5G Wireless Fronthaul Networks, Synchronization of Diversity and Network Coding, Software Defined Networking (SDN), and Network Function Virtualization (NFV).
Richard D. Gitlin is a State of Florida 21st Century World Class Scholar, Distinguished University Professor and the Agere Systems Chaired Distinguished Professor of Electrical Engineering at the University of South Florida. He has more than 45 years of leadership in the communications and networking industry. He was at Bell Labs/Lucent Technologies for 32-years performing and leading pioneering research and development in digital communications, broadband networking, and wireless systems. Dr. Gitlin was Senior VP for Communications and Networking Research at Bell Labs and later CTO of Lucent’s Data Networking Business Unit. After retiring from Lucent, he was visiting professor of Electrical Engineering at Columbia University, where he supervised several doctoral students and research projects and then Chief Technology Officer of Hammerhead Systems, a venture funded networking company in Silicon Valley. Since joining USF in 2008, he has focused on the intersection of communications with medicine and created an interdisciplinary team that is focused on wireless networking of in vivo miniature wirelessly controlled devices to advance minimally invasive surgery and other cyber-physical health care systems. Dr. Gitlin has also directed research on advancing wireless local and 4G and 5G cellular systems by increasing their reliability and capacity. Dr. Gitlin is a member of the National Academy of Engineering (NAE), a Fellow of the IEEE, a Bell Laboratories Fellow, a Charter Fellow of the National Academy of Inventors (NAI), and a member of the Florida Inventors Hall of Fame. He is also a co-recipient of the 2005 Thomas Alva Edison Patent Award and the S.O. Rice prize, has co-authored a text, published ~150 papers and holds 65 patents.
EVALUATING PERFORMANCE OF WIRELESS SENSOR NETWORK IN REALISTIC SMART GRID ENVIRONMENT
Laila Nassef1,2, Remah Elhebshi1 and Linta Jose1,
1King Abdulaziz University, Saudi Arabia and 2Cairo University, Egypt
ABSTRACT
Wireless Sensor Networks (WSNs) is a strong candidate for smart grid applications, such as advanced metering infrastructure, demand response management, dynamic pricing, load control, electricity fraud detection, fault diagnostics, substation monitoring and control as well as automation of various elements of the power grid. The realization of these applications directly depends on efficiency of communication facilities among power grid elements. However, the harsh power grid environmental conditions with obstacles, noise, interference, and fading pose great challenges to reliability of these facilities to monitor and control the power grid. The purpose of this paper is to evaluate performance of WSNs in different power grid environments such as 500 kv substations, main power control room, and underground network transformer vaults. The power grid environments are modeled using a log-normal shadowing path loss model channel with realistic parameters. The network is simulated and performance is evaluated using packet delivery ratio, communication delay, and energy consumption. The simulation results have revealed that different environments have considerable impacts on performance of WSNs which make it suitable for most applications that need low data rate with low reliability requirements.
KEYWORDS
Smart Grid; Wireless Sensor Networks; Propagation Models; NS-2
For More Details :
http://aircconline.com/ijwmn/V10N3/10318ijwmn03.pdf
Volume Link :
http://airccse.org/journal/jwmn_current18.html
REFERENCES
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[[11] P. Sharma & G. Pandove, (May-June 2017) “A Review Article on Wireless Sensor Network in Smart Grid,” International Journal of Advanced Research in Computer Science, Vol. 8, No. 5, pp. 1903- 1907, ISSN No. 0976-5697.
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[[13] S. Jabbar, M. A. Habib, A. A. Minhas, M. Ahmad, R. Ashraf, S. Khalid & K. Han, (18 February 2018) “Analysis of Factors Affecting Energy Aware Routing in Wireless Sensor Network,” Wireless Communications and Mobile Computing- Hindawi, Vol. 2018, Article ID 9087269, pp. 396-405, https://doi.org/10.1155/2018/9087269.
[[14] S. Jabbar, M. Asif Habib, A. Minhas, M. Ahmad, R. Ashraf, S. Khalid & K. Han, (2018) “Analysis of Factors Affecting Energy Aware Routing in Wireless Sensor Network,” Hindawi, Wireless Communications and Mobile Computing, Vol. 2018, Article ID 9087269, https://doi.org/10.1155/2018/9087269.
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A HYBRID FUZZY SYSTEM BASED COOPERATIVE SCALABLE AND SECURED LOCALIZATION SCHEME FOR WIRELESS SENSOR NETWORKS
Abhishek Kumar,
Nurture Education Solutions Private Limited, India.
ABSTRACT
Localization entails position estimation of sensor nodes by employing different techniques and mathematical computations. Localizable sensors also form an inherent part in the functioning of IoT devices and robotics. In this article, the author extends1 a novel scheme for node localization implemented using a hybrid fuzzy logic system to trace the node locations inside the deployment region, presented by the Abhishek Kumar et. al. The results obtained were then optimized using Gauss Newton Optimization to improve the localization accuracy by 50% to 90% vis-à-vis weighted centroid and other fuzzy based localization algorithms. This article attempts to scale the proposed scheme for large number of sensor nodes to emulate somewhat real world scenario by introducing cooperative localization in previous presented work. The study also analyses the effectiveness of such scaling by comparing the localization accuracy. In next section, the article incorporates security in the proposed cooperative localization approach to detect malicious nodes/anchors by mutual authentication using El Gamel digital Signature scheme. A detailed study of the impact of incorporating security and scaling on average processing time and localization coverage has also been performed. The processing time increased by a factor of 2.5s for 500 nodes (can be attributed to more number of iterations and computations and large deployment area with small radio range of nodes) and coverage remained almost equal, albeit slightly low by a factor of 1% to 2%. Apart from these, the article also discusses the impact of adding extra functionalities in the proposed hybrid fuzzy system based localization scheme on processing time and localization accuracy. Lastly, this study also briefs about how the proposed scalable, cooperative and secure localization scheme tackles the type of attacks that pose threat to localization.
KEYWORDS
Sugeno Fuzzy Inference Systems, Mamdani Fuzzy Inference Systems, Localization algorithms, Gauss Newton method, Cooperative localization, Mutual authentication, Elgamel Digital Signature
For More Details :
http://aircconline.com/ijwmn/V10N3/10318ijwmn05.pdf
Volume Link :
http://airccse.org/journal/jwmn_current18.html
REFERENCES
[1] Kumar A., Saini B. (2018) A Sugeno-Mamdani Fuzzy System Based Soft Computing Approach Towards Sensor Node Localization with Optimization. In: Bhattacharyya P., Sastry H., Marriboyina V., Sharma R. (eds) Smart and Innovative Trends in Next Generation Computing Technologies. NGCT 2017. Communications in Computer and Information Science, vol 828. pp 40-55, Springer, Singapore.
[2] A. Kumar, N. Chand, V. Kumar, and V. Kumar, “Range Free Localization Schemes for Wireless Sensor Networks,” Int. J. Comput. Networks Commun., vol. 3, no. 6, pp. 115–129, 2011.
[3] A. Kumar and V. Kumar, “Fuzzy Logic Based Improved Range Free Localization for Wireless Sensor Networks,” vol. 177005, no. 5, pp. 534–542, 2013.
[4] M. A. Monfared, “Range Free Localization of Wireless Sensor Networks Based on Sugeno Fuzzy Inference,” no. c, pp. 36–41, 2012.
[5] S. K. Gharghan, R. Nordin, and M. Ismail, “A wireless sensor network with soft computing localization techniques for track cycling applications,” Sensors (Switzerland), vol. 16, no. 8, 2016.
[6] M. Kadkhoda, M. A. Totounchi, S. Member, M. H. Yaghmaee, and Z. Davarzani, “A Probabilistic Fuzzy Approach for Sensor Location Estimation in Wireless Sensor Networks,” 2010.
[7] L. Mallu and R. Ezhilarasie, “Live migration of virtual machines in cloud environment: A survey,” Indian J. Sci. Technol., vol. 8, no. July, pp. 326–332, 2015.
[8] B. Li, N. Wu, H. Wang, P. H. Tseng, and J. Kuang, “Gaussian message passing-based cooperative localization on factor graph in wireless networks,” Signal Processing, vol. 111, no. April, pp. 1–12, 2015.
[9] H. Naseri and V. Koivunen, “A Bayesian algorithm for distributed network localization using distance and direction data,” pp. 1–11.
[10] Tashnim Jabir Shovon Chowdhury, “A Distributed Cooperative Algorithm for Localization in Wireless Sensor Networks Using Gaussian Mixture Modeling,” University of Toledo, 2016.
[11] Kumar A., Prashar D. (2018) A Novel Approach for Node Localization in Wireless Sensor Networks. In: Singh R., Choudhury S., Gehlot A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. pp 419-428, Springer, Singapore
[12] X. Liu, R. Yang, and Q. Cui, “An Efficient Secure DV-Hop Localization for Wireless Sensor Network,” System, vol. 9, no. 7, pp. 275–284, 2015.
[13] H. Chen, W. Lou, Z. Wang, J. Wu, Z. Wang, and A. Xi, “Securing DV-Hop localization against wormhole attacks in wireless sensor networks,” Pervasive Mob. Comput., vol. 16, no. PA, pp. 22– 35, 2015.
[14] W. Shi, M. Barbeau, J. P. Corriveau, J. Garcia-Alfaro, and M. Yao, “Secure localization in the presence of colluders in WSNs,” Sensors (Switzerland), vol. 17, no. 8, 2017.
[15] P. Li, X. Yu, H. Xu, J. Qian, L. Dong, and H. Nie, “Research on secure localization model based on trust valuation in wireless sensor networks,” Secur. Commun. Networks, vol. 2017, 2017.
[16] G. Kumar, M. K. Rai, H. J. Kim, and R. Saha, “A Secure Localization Approach Using Mutual Authentication and Insider Node Validation in Wireless Sensor Networks,” Mob. Inf. Syst., vol. 2017, 2017.
[17] L. Lazos and R. Poovendran, “SeRLoc: Secure Range-Independent Localization for Wireless Sensor Networks,” Netw. Secur., pp. 21–30, 2004.
ENERGY AND PERFORMANCE EVALUATION OF REACTIVE, PROACTIVE, AND HYBRID ROUTING PROTOCOLS IN WIRELESS MESH NETWORK
Jean Louis Ebongue Kedieng Fendji1 and Sidoine Djuissi Samo2,
1University Institute of Technology, Ngaoundéré and 2Apple College, Dubai, United Arab Emirates
ABSTRACT
In this dynamic world, communication is a sine qua non for development. Communication represents sharing of information which can be local or remote. Though local communications may occur face to face between individuals remote communications take place among people over long distances. Mobile ad hoc networks (MANETs) are becoming an interesting part of research due to the increasing growth of wireless devices (laptops, tablets, mobiles etc.) and as well as wireless internet facilities like 4G/Wi-Fi. A MANET is any infrastructure-less network formed by independent and self-configuring nodes. Each node acts as router. In order to send data, the source node initiates a routing process by using a routing protocol. The nature of the wireless medium is always insecure. So, during routing many attacks can take place. The main objective of an eavesdropper is to grab the confidential information in the network. This secret information is used by a malicious node to perform further attacks. Here, the entire problem lies in identifying the eavesdropper because the eavesdropper acts a normal node in the network. In this paper, we analyzed the impact of eavesdropper while executing an Ad hoc On Demand routing (AODV) protocol in MANETs. All the simulations are done using QualNet 5.1 network simulator. From the results, it is found that the network performance degrades in presence of an eavesdropper.
KEYWORDS
MANETs, AODV, eavesdropper, energy consumption, QualNet
For More Details :
http://aircconline.com/ijwmn/V11N1/11119ijwmn02.pdf
Volume Link :
http://airccse.org/journal/jwmn_current19.html
REFERENCES
[1] D. P. Agrawal and Q-A Zeng. “Introduction to Wireless and Mobile Systems,” Brooks/Cole Publishing, ISBN No. 0534-40851-6, 436 pages, 2003.
[2] S. Giordano and W. W. Lu, “Challenges in mobile ad hoc networking,” IEEE Communications Magazine, vol. 39, no. 6, pp. 129–181, June 2001.
[3] J. Broch, D. Maltz, D. Johnson, Y. Hu, and J. Jetcheva. “Multi-Hop Wireless Ad Hoc Network Routing Protocols.” ACM/IEEE International Conference on Mobile Computing and Networking (MOBICOM’98), pages 85-97, 1998.
[4] Latiff, L. A. and Fisal, N. 2003. ‘Routing Protocols in Wireless Mobile Ad Hoc Network – A Review’. The 9th Asia-Pasific Conference on Communication (APCC 2003), vol. 2, pp. 600- 604.
[5] S. Lee, M. Gerla, and C. Chiang. “On-Demand Multicast Routing Protocol.” IEEE Wireless Communications and Networking Conference (WCNC’99), 1999.
[6] J. Broch, D. Maltz, D. B. Johnson, Yih-Chun Hu, J. Jetcheva. “A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing protocols.”Proceedings of the Fourth Annual ACM/IEEE on Mobile Computing and Networking, MOBICOM 98, October 1998.
[7] C.E. Perkins, E.M. Royer & S. Das, Ad Hoc On Demand Distance Vector (AODV) Routing, IETFInternet draft, draft-ietf-manet-aodv-08.txt, March 2001
[8] C. E. Perkins, and E. M. Royer, “Ad-Hoc On-Demand Distance Vector Routing,” in Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA, pp. 90-100, February 1999
[9] QualNet 5.1 Developer Model Library, Scalable Network Technologies, Inc., http://www.scalable-networks.com
[10] Jiejun Kong, Xiaoyan Hong. AODV: anonymous on demand routing with untraceable routes for mobile adhoc networks. MobiHoc’03, June 1–3, 2003, Annapolis, Maryland, USA
[11] Bing Wu, Jianmin Chen, Jie Wu, Mihaela Cardei, “A Survey on Attacks and Countermeasures in Mobile Ad Hoc Networks”, WIRELESS/MOBILE NETWORK SECURITY Y. Xiao, X. Shen, and D.-Z. Du (Eds.) pp.,2006 Springer
[12] S. Yi and R. Kravets, Composite Key Management for Ad Hoc Networks. Proc. of the 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous’04), pp. 52-61, 2004.
[13] R. Oppliger, Internet and Intranet Security, Artech House, 1998.
[14] Qiu Wang and Hong-Ning Dai and Qinglin Zhao, “Eavesdropping Security in Wireless Ad Hoc Networks with Directional Antennas”
[15] Satoshi Kurosawa, Hidehisa Nakayama, Nei Kato, Abbas Jamalipour2, and Yoshiaki Nemoto, “Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning
Method”, International Journal of Network Security, Vol.5, No.3, PP.338–346, Nov. 2007
[17] Viren Mahajan, Maitreya Natu, and Adarshpal Sethi, “ANALYSIS OF WORMHOLE INTRUSION ATTACKS IN MANETS”, 2008 IEEE
[18] Neeraj Tantubay,Dinesh Ratnam Gautam and Mukesh Kumar Dharjwal , “A Review of Power Conservation in Wireless Mobile Ad hoc Network (MANET)”,IJCSI Vol.8, Issue 4, No.1 , July,2011.
OPTIMAL DATA COLLECTION FOR A 2-LEVEL BALANCED WSN
John R Rankin,
Charles Sturt University Study Group Melbourne, Australia
ABSTRACT
Battery life is a drawback of Wireless Sensor Networks (WSNs) but careful management of the network can provide optimum performance before batteries need replacing. This paper models and analyses the productivity and energy consumption of a 2-level balanced WSN. By optimizing the energy versus time curve first with respect to quiescent periods we obtain a curve of rest length as a function of the number of level two nodes and then by secondly optimizing this curve with respect to the number of remote nodes per level one sensor node, an overall optimum network management strategy is achieved. Programs were written to display the productivity and longevity curves and determine the optimum point if it exists.
KEYWORDS
Wireless Sensor Network, Network Architecture, Optimization, Productivity, Longevity
For More Details :
http://aircconline.com/ijwmn/V9N3/9317ijwmn03.pdf
Volume Link :
http://airccse.org/journal/jwmn_current17.html
REFERENCES
[1] Hoang AN, Forster A, Puccinelli D, Giordano S, “Sensor Node Lifetime: An Experimental Study”,
[2] Yu-Chee Tseng , You-Chiun Wang , Kai-Yang Cheng “iMouse: An Integrated Mobile Surveillance and Wireless Sensor System” IEEE Computer Volume: 40, Issue: 6, June 2007.
[3] Wen-Tsuen Chen , Po-Yu Chen , Wei-Shun Lee , Chi-Fu Huang , “Design and Implementation of a Real Time Video Surveillance System with Wireless Sensor Networks”, Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE.
[4] Ali Benzerbadj, BouabdellahKechar,AhcéneBounceur, Bernard Pottier “Energy Efficient Approach for Surveillance Applications Based on Self Organized Wireless Sensor Networks”, Procedia Computer Science, (Elzevier), Volume 63, 2015, Pages 165-170.
[5] Mahmood Ali, Annette Böhm and Magnus Jonsson, “Wireless Sensor Networks for Surveillance Applications – A Comparative Survey of MAC Protocols”, In: The fourth international conference on wireless and mobile communications (ICWMC 2008). Piscataway: IEEE; 2008. p. 399-403.
[6] Muhammad Farhan Khan, Emad A. Felemban,; SaadQaisar, Salman Ali, “Performance Analysis on Packet Delivery Ratio and End-to-End Delay of Different Network Topologies in Wireless Sensor Networks (WSNs)”, pp 324-329, 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks, 2013.
[7] MeenakshiTripathi, R. B. Battula, M. S. Gaur, V. Laxmi, “Energy Efficient Clustered Routing for Wireless Sensor Network” , pp 324-329, 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks, 2013.
AUTHORS
Dr J Rankin has undertaken research over 45 years starting with General Relativity and Mathematical Physics at the University of Adelaide followed by Computer Graphics, Fuzzy Logic Systems and Games Technology at La Trobe University and most recently Wireless Sensor Networks with Charles Sturt University Study Group Melbourne.
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELESS SENSOR NETWORK
Gholamreza Farahani,
Iranian Research Organization for Science and Technology (IROST), Iran
ABSTRACT
From one side, sensor manufacturing technology and from other side wireless communication technology improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The appropriate performance of WSN has abundant necessity which has dependent on the different parameters such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not only would optimize number of sensors, but also help to reach to the more precise information. Therefore different solutions are proposed to reduce cost and increase life time of sensor networks that most of them are concentrated in the field of routing and information transmission. In this paper, places which they need new sensors placement or sensor movements are determined and then with applying these changes, performance of WSN will calculate. To achieve the optimum placement, the network should evaluate precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest number of added sensors in comparison with other methods.
KEYWORDS
Sensor, Wireless Sensor Network, Geographic Information System, Network performance, Analytical Hierarchy process, Overlap Index
For More Details :
http://aircconline.com/ijwmn/V9N1/9117ijwmn02.pdf
Volume Link :
http://airccse.org/journal/jwmn_current17.html
REFERENCES
[1] Miri S. M. & Afshar A., (2014) “Optimum Layout for Sensors in Water Distribution Networks through Ant Colony Algorithm: A Dual use Vision“, Water and Sewage Quarterly, Vol. 25, No. 3, pp 67-75.
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[4] Osais, Y.E., M. St-Hilaire & R.Y. Fei, (2010), “Directional sensor placement with optimal sensing range, field of view and orientation“, Mobile Networks and Applications, Vol. 15, No. 2, pp 216-225.
[5] Isovitsch, S.L. & J.M. VanBriesen, (2008), “Sensor placement and optimization criteria dependencies in a water distribution system“, Journal of Water Resources Planning and Management, Vol. 134, No. 2, pp 186-196.
[6] Castello, C.C. & Fan J., (2010), “Optimal sensor placement strategy for environmental monitoring using wireless sensor networks“, 42nd Southeastern Symposium on System Theory (SSST), pp 275- 279.
[7] Mini, S., S.K. Udgata & S.L. Sabat, (2014), “Sensor deployment and scheduling for target coverage problem in wireless sensor networks“, IEEE sensors journal, Vol. 14, No. 3, pp 636-644.
[8] Argany, M., (2015), Development of a GIS-Based Method for Sensor Network Deployment and Coverage Optimization, PhD Thesis, Université Laval.
[9] M. Marks, (2010), “A survey of multi-objective deployment in wireless sensor networks“, Journal of Telecommunications and Information Technology, pp 36-41.
[10] C.Zhu, C. Zheng, L. Shu & G. Han, (2012),”A survey on coverage and connectivity issues in wireless sensor networks“, Journal of Network and Computer Applications, Vol. 35, No. 2, pp 619-632.
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[12] S.R.Angajala, (2012), “Coverage Problems in Sensor Networks”, IJECCE, Vol. 3, No. 1, pp 104-110.
[13] A. Ghosh & S.K. Das, (2006), “Coverage and connectivity issues in wireless sensor networks”, Mobile, wireless, and sensor networks: Technology, applications, and future directions, pp 221-256.
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location in distributed sensor networks”, IEEE transactions on computers, Vol. 51, Vol. 12, pp 1448- 1453.
[15] D.S. Deif & Y. Gadallah, (2014), “Classification of wireless sensor networks deployment techniques“, IEEE Communications Surveys & Tutorials, Vol.16, No. 2, pp 834-855.
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AUTHORS
Gholamreza Farahani received his BSc degree in electrical engineering from Sharif University of Technology, Tehran, Iran, in 1998 and MSc and PhD degrees in electrical engineering from Amirkabir University of Technology (Polytechnic), Tehran, Iran in 2000 and 2006 respectively. Currently, he is an assistant professor in the Institute of Electrical and Information Technology, Iranian Research Organization for Science and Technology (IROST), Iran. His research interest is Wireless Network especially Wireless Sensor network.
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