CSE Department,SCAD CET,Tirunelveli,TamilNadu.

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1 Volume 4, Issue 3, March 2014 ISSN: X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: Special Issue: Computing Terminologies and Research Development Conference Held at SCAD College of Engineering and Technology, India Managing Replicas of Multipath Routing For Detecting Interruption in HWSN Krishnaveni.A #1, Subbulakshmi.G #2 #1 Assistant Professor, CSE Department,SCAD CET,Tirunelveli,TamilNadu. #2 PG Scholar, CSE Department,SCAD CET,Tirunelveli,TamilNadu. Abstract--The managing replicas of multipath routing for interruption tolerance in HWSN is to maximize the network lifetime. For improving system lifetime, the energy consumption, security, reliability and timeliness are considered. Dynamic redundancy management algorithm is presented for improving the system lifetime but energy efficiency and the energy balancing is not considered. In the proposed system DEAR algorithm is designed to ensure energy efficiency and energy balancing based on their different energy and traffic model. During the routing process it considers individual distance as the primary parameter in order to adjust and equalize the energy consumption among involved sensors. In this way all intermediate nodes consume their energy at similar rate which maximize network lifetime. Novel probability model is used to detect the best redundancy level in the terms of source redundancy and the path redundancy. Voting based distributed intrusion detection algorithm is applied to detect the malicious nodes in the HWSN. The analysis result shows the energy consumption, route evaluation time and the packet transmission time. Index Terms- Heterogeneous Wireless Sensor Networks, multipath routing, energy consumption, intrusion detection. I. INTRODUCTION Due to the limited capacity of a multi-hop path and the high dynamics of wireless links, single-path routing approach is unable to provide efficient high data rate transmission in wireless sensor networks.the multipath routing approach is generally utilized as one of the possible solutions to manage with this control. This sector presents the main motivations behind using multipath routing approach in wireless sensor networks.this paper discuss the main design issue in the improvement of the existing multipath routing protocols. As stated before, multipath routing technique has demonstrated its efficiency to improve wireless sensor and ad hoc networks performance. In the following, we review the performance gains that can be achieved through using multipath routing approaches Reliability and Fault-tolerance. For this purpose, multipath routing approaches can provide the best solution to support the bandwidth requirements of different applications and reduce the probability of network congestion through splitting network traffic over several paths. Furthermore, distributing network traffic over more sensor nodes can result in even energy consumption among the sensor nodes and prolong the network lifetime. Energy efficiency and balancing is one of the primary challenges for wireless sensor networks (WSNs) since the tiny sensor nodes cannot be easily recharged once they are deployed. In this paper, a Distance-based Energy Aware Routing (DEAR) algorithm is proposed to ensure energy efficiency and energy balancing based on theoretical analysis of different energy and traffic models. Heterogeneous Wireless Sensor Network(HWSN) utilizing the multipath routing to answer the user queries in the presence of unreliable and malicious nodes. Using the Distance Energy Aware Routing Protocol for route optimization. It detect the optimal path among the multiple paths. This way it consumes the energy. Among the multiple path it choose the optimal path and also detect the intruder among the path. Using the voting based intrusion detection mechanism for detect the interruption among the path. Among this way energy is consume and also gain reliability, security. II. RELATED WORK Many routing protocol are proposed to consuming the energy, but they does not consider about the energy efficiency and the energy balancing. Dynamic redundancy management algorithm is used to identify and apply the best design 2014, ICCTRD All Rights Reserved Page 176

2 parameter. It take multiple copies of each packet so traffic will occur. Random selection of the CH higher communication overhead will occur. Load imbalance will be occur in the different cluster[1]. Improves the network performance using HSN.CHR for long range transmission. It provide the Higher packet delivery. But the number of transmission is small[2].in the mixed communication it provide optimal transmission range but total energy consumption is not minimized by all sensor nodes. It consumes energy for only nearest sensor node[3].it minimize the total energy but the load imbalance was occur.[4]it create the well distributed cluster [5] need the extra energy to rebuilt the cluster. Most of the prior research using the multipath routing to provide the reliability and the timeliness[6] power consumption is not considered. During the multipath routing send the data by using among the multiple path it select the secure path [7-11] Intrusion detection was considered for the security purpose. III. PROPOSED SYSTEM HWSN utilizing multipath routing is used to answer the user queries in the presence of unreliable and malicious nodes. Using the Multipath routing to improve the data delivery. Novel Probability model to detect best redundancy level. Energy efficiency Energy balancing and the Route optimization is done by DEAR algorithm.in HWSN to avoid intrusion an algorithm named voting based distributed intrusion detection is used. A.Energy Consumption In the energy consumption calculate the amount of energy spent during the IDS interval,query interval and the clustering interval.first estimate the maximum number of queries the system can possible handle before running into energy exhaustion. Then calculate the total energy consumed during the intrusion detection, clustering and the query processing. The packet transmission time can be calculate by using the formula as follows: Pt= N 0.5 Let, Pt -> Packet Transmission Time N -> number of nodes B.Query Success Probability To increase query success probability by transmit the data within the time. Data can be transmit from CH to the PC. Query can be failure due to the following reasons: transmission speed violation, intrusion, sensor node failures.ch collect the information from the sensor node. The CH send the data to the PC through the intermediate nodes. C.Architecture For Detecting Interruption In Hwsn The number node given as the input sequence and then it generate keys as the output.it generate the two types of keys.one is probabilistickey and the another one is deterministric key.based on the hop distance di,j connect the neighbourhood nodes.if the nodes within the coverage area then Perform Tclustering based on hop distance di,j otherwise clustering is not performed.choosing the CH based on the highest data rate.for each node in the cluster group the CH will create unique key k prob Then CH generate the session key ksession by itself based upon the probabilistic key. Using the multipath routing it send the data or packet. Among the multiple path it choose the secure path to send the data.based on the Distance Energy Aware Routing algorithm it choose the optimal path.energy can be consumed by using this way. D.Algorithm For Distance Energy Aware Routing Route optimization is done by DEAR algorithm.data can be send to the base station through the multiple path.calculate the distance between the nodes.using this information it find the optimal path. Input:Number of nodes send to the BS via mltipath routing. Output:Find the optimal path. 2014, ICCTRD All Rights Reserved Page 177

3 Fig.1. Architecture for Detecting Interruption In Hwsn Algorithm: Begin 1. Source node i has data to send to Base Station(BS) 2. if ( i < (n=2)) then 3. direct transmission 4. else 5. Choose next hop candidate set A with d(i,j) 6. Choose next hop candidate sub-set B A with dj,bs<di,bs 7. Choose next hop candidate sub-set C B with dc,bs<db-c,bs 8. Choose final next hop candidate j with maximal residual energy 9. end if 10. Node i sends RREQ to node j to request route setup. 11. Node j sends ACK to node i to confirm reception of RREQ 12. Node j determines its next hop in an iterative way above and sends RREQ 13. RREQ message reaches BS 14. BS sends RREP to node i and traffic begins 15. End E.Algorithm For Generating The Keys Using this algorithm it generate the keys.ch generate the key for the nodes.based upon the highest data rate it choose the Cluster Head. Input:Number of nodes and the key. Output:Session key,unique key Algorithm Begin 1.Generate the dynamic nodes n1,n2...n 2.Based on the hop distance di,j connect the neighbourhood nodes 3.If the nodes within the coverage area then 4.Perform Tclustering based on hop distance di,j 5.Else clustering is not performed 2014, ICCTRD All Rights Reserved Page 178

4 6.Choosing the CH based on the highest data rate 7.For each node in the cluster group the CH will create unique key k prob 8.Then CH generate the session key ksession by itself 9. End IV. RESULT. Fig.2.CH Generating keys for the nodes Fig.3. Generate the optimal path Analysis 2014, ICCTRD All Rights Reserved Page 179

5 Fig.4.Required Energy(Bar Chart) Fig.5.Required Energy(Line Chart) Using the voronoi theory it form the clustering.dear algorithm is proposed for route optimization energy efficiency and the energy balancing.it generate the keys to nodes for security purpose.suppose the node can be disjoint from the clstering using the unique key it again join into the cluster.the node is intuder mean it cannot join into the cluster.it compare the three routing algorithm DSDV, DSR and the DEAR. IV. CONCLUSION In our system in order to select the best path in multipath routing, and for energy consumption DEAR algorithm is used, in case of detecting critical path novel probability model is introduced. This approach achieves route evaluation time, packet transmission time and energy factor. For intruder detection in multipath routing vote based intrusion detection algorithm is introduced. The simulated result shows the better energy consumption among the WSN. REFERENCES [1] O. Younis and S. Fahmy, HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks, IEEE Trans. Mobile Comput., vol. 3, no. 4, pp , [2] E. Felemban, L. Chang-Gun, and E. Ekici, MMSPEED: multipath multi-speed protocol for QoS guarantee of reliability and timeliness in wireless sensor networks, IEEE Trans. Mobile Comput., vol. 5, no.6, pp , [3] I. R. Chen, A. P. Speer, and M. Eltoweissy, Adaptive fault-tolerant QoS control algorithms for maximizing system lifetime of query-based wireless sensor networks, IEEE Trans. Dependable Secure Computing, vol. 8, no. 2, pp , [4] M. Yarvis, N. Kushalnagar, H. Singh, A. Rangarajan, Y. Liu, and S.Singh, Exploiting heterogeneity in sensor networks, in Proc IEEE Conf. Computer Commun., vol. 2, pp [5] H. M. Ammari and S. K. Das, Promoting heterogeneity, mobility, and energy-aware Voronoi diagram in wireless sensor networks, IEEE Trans. Parallel Distrib. Syst., vol. 19, no. 7, pp , X. Du and F. Lin, Improving routing in sensor networks with heterogeneous sensor nodes, in Proc IEEE Veh. Technol. Conf., pp [7] S. Bo, L. Osborne, X. Yang, and S. Guizani, Intrusion detection techniques in mobile ad hoc and wireless sensor networks, IEEE Wireless Commun. Mag., vol. 14, no. 5, pp , [8] I. Krontiris, T. Dimitriou, and F. C. Freiling, Towards intrusion detection in wireless sensor networks, in Proc European Wireless Conf. [9] J. H. Cho, I. R. Chen, and P. G. Feng, Effect of intrusion detection on reliability of mission-oriented mobile group systems in mobile ad hoc networks, IEEE Trans. Reliab., vol. 59, no. 1, pp , [10] A. P. R. da Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L.B. Ruiz, and H. C. Wong, Decentralized intrusion detection in wireless sensor networks, in Proc ACM Workshop Quality Service Security Wireless Mobile Netw. [11] Y. Zhou, Y. Fang, and Y. Zhang, Securing wireless sensor networks: a survey, IEEE Commun. Surveys & Tutorials, vol. 10, no. 3, pp. 6 28, [12] L. Lamport, R. Shostak, and M. Pease, The byzantine generals problem, ACM Trans. Programming Languages Syst., vol. 4, no. 3, pp , [13] Y. Yang, C. Zhong, Y. Sun, and J. Yang, Network coding based reliable disjoint and braided multipath routing for sensor networks, J. Netw. Comput. Appl., vol. 33, no. 4, pp , , ICCTRD All Rights Reserved Page 180

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