Impact of using mobile sink routing protocols for wireless sensor networks by IJRTER

IMPACT OF USING MOBILE SINK ROUTING PROTOCOLS FOR WIRELESS SENSOR NETWORKS 1 Mrs.

Akanksha Tiwari, 2 Mr. Praveen Chouksey

Mtech Scholar, CSE Department, Dr.C.V,RAMAN UNIVERSITY, Bilaspur India Assistant Professor, CSE Department, Dr.C.V,RAMAN UNIVERSITY, Bilaspur India

Abstract— The idea of exploiting the mobility of data collection points (sinks) for the purpose of increasing the lifetime of a wireless sensor network with energy-constrained nodes. We give a novel linear programming formulation for the joint problems of determining the movement of the sink and the sojourn time at different points in the network that induce the maximum network lifetime. Differently from previous solutions, our objective function maximizes the overall network lifetime (here defined as the time till the first node “dies” because of energy depletion) rather than minimizing the energy consumption at the nodes. We develop an algorithm for trajectory of mobile sink. We ultimately perform wide-ranging experiments to assess the performance of the proposed method. The results reveal that the proposed way out is nearly optimal and also better than IEEPB in terms of network lifetime. Keywords—: network mobile sink, sensing capabilities , Routing, network management. I. INTRODUCTION For wireless sensor networks with up to 256 nodes our model produces sink movement patterns and sojourn times leading to a network lifetime up to almost five times that obtained with a static sink. Simulation results are performed to determine the distribution of the residual energy at the nodes over time. These results confirm that energy consumption varies with the current sink location, The energy of nodes near to sink exhausted very quickly in hierarchal protocols where the base station is fixed, as a result networks get disconnected. To overcome this problem and prolong the life time of network mobile sink is used to collect the data. Sink changes its position randomly according to the requirement of mobility [1]. There are many ways in which sink can move in a network of, it can move on the top of network, bottom of network, diagonally in network and in many other directions. Before the sink changes its position, it stops for a fixed amount of time to collect the data from sensors within its range called pause time [2]. According to the definition of discrete mobility pattern described, the sink changes its location from time to time. A routing protocol that transfers data towards such a sink should perform the following operations that are not needed for traditional WSNs: a) b) c)

Notify a node when its link with the sink gets broken due to mobility. Inform the whole network of the topological changes incurred by mobility. Minimize the packet loss during the sink moving period.

During pause time, the sink broadcasts a beacon frame to its neighboring node for transmitting the data packets. When node sends the data, sink broadcasts another beacon frame to stop transmission which reduces the packet drop [3]. The network life time can be extended if mobile sink balances the traffic load of nodes. To minimize the traffic load shortest path routing is used.

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

 ROUTING TOWARDS A MOBILE SINK. A wireless Sensor Network is made up of independently sensors spread over the space to observe the physical and environmental conditions and to considerably pass their data through the group of sensors to a main location. Modern Sensor Network also helps to control the activity of sensors. These systems are now used in many industrial and computer applications [4]. A sensor node is small device consists of a sensing subsystem for gathering the data from the environment, a processing subsystem for local data processing and storage , and a wireless antenna for data transmission [5]. The energy requirement for performing the entire task is fulfilled by an energy source. In general a senor node is combination of computing, communicating and sensing capabilities. II RELATED WORK  Angle-based Dynamic Source Routing: Though Dynamic Source Routing is a popular on-demand algorithm designed to restrict the bandwidth consumed by control packets, the flooding of Route Request packets to find paths to a destination makes it difficult to apply DSR to wireless sensor networks, which have tiny sensor nodes of limited memory and power. In this study, an angle-based multi-hop routing algorithm for mobile WSNs, which is termed ADSR, is proposed[6]. ADSR is a variation of DSR utilizing the location information of a neighboring mobile node and a stationary sink to make the decision of dropping or rebroadcasting the RREQ packet received.  Dynamic Angle-Based K-Path Routing For Wireless Sensor Networks DAKR, a new routing protocol that improves the delay and energy performance, has been proposed in this paper. The protocol has less memory requirements, which is very desirable for Wireless Sensor Networks in general. The protocol also minimizes flooding of packets, and the number of copies of the packets held by the sensor networks is also minimum [7]. This is highly desirable for the energy constrained Wireless Sensor Networks. The simulation results show the lesser delay and memory required by DAKR over a standard geographic protocol like the ADSR.  Power-Efficient Gathering in Sensor Information Systems PEGASIS is an extension of the LEACH protocol, which forms chains from sensor nodes so that each node transmits and receives from a neighbor and only one node is selected from that chain to transmit to the base station[8]. PEGASIS protocol which was introduced by Lindsey Stephanie is a power-efficient gathering in sensor information systems.  Threshold Sensitive Energy Efficient Sensor Network Protocol The CH sends aggregated data to higher level CH until the data reaches the sink. Thus, the sensor network architecture in TEEN is based on a hierarchical grouping where closer nodes form clusters and this process goes on the second level until the BS (sink) is reached. TEEN is useful for applications where the users can control a trade-off between energy efficiency, data accuracy, and response time dynamically. TEEN uses a data-centric method with hierarchical approach. Important features of TEEN include its suitability for time critical sensing applications. Also, since message transmission [9]. It is targeted at reactive networks and is the first protocol developed for reactive networks, to our knowledge.  Adaptive Periodic Threshold Sensitive Energy Efficient Sensor Network Protocol APTEEN is an improvement to TEEN to overcome its shortcomings and aims at both capturing periodic data collections and reacting to time-critical events. Thus, APTEEN is a hybrid clustering-based routing protocol that allows the sensor to send their sensed data periodically and

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

react to any sudden change in the value of the sensed attribute by reporting the corresponding values to their CHs [10]. ď&#x201A;ˇ ď&#x201A;ˇ

III. OBJECTIVES We investigate the problems of long chain for efficient energy consumption and delay in data delivery considering sink mobility. We spotlight on the notion of fixed path mobility and confine the sink to limited potential locations.

IV. IMPLEMENTATION ď&#x201A;ˇ Data collection in Wireless sensor network o Sink node All collected sensor data are forwarded to sink node. It is used for data collection purpose it can be a base station or access point. o Multiple Sink In Multiple Sink Node Data Collection Problem data from sensor nodes needs to be transmitted to one of multiple sinks in wireless sensor networks. To minimize the latency of data collection, Schedule designs an approximation algorithm [11]. o Approximate Data Collection (ADC) ADC is to divide a sensor network into clusters, discover local data correlations on each cluster head, and perform global approximate data collection on the sink node according to model parameters uploaded by cluster heads. o Comparison of sink node Static sink node was used for data collection in wireless sensor network by using multi hop forwarding so there is more energy consumption nearby node around Base station and relaying in data from other one. Mobile sink node was used to collect data from sensors node and stored it to the base station. But due to failure of a node whole process fail as only one mobile sink node is using. Multiple sink nodes were used in data collection process from the sensors and stored collected data on the base station in the database [12]. Here when one of the node mobile sink node fail other is available as the backup one. o Sparse Sensor Networks using Data Mules modelling for data collection A mobile sink node called data MULE travel in sensing area randomly and collect the data. It collects all the data from all sensors so communication traffic increases. In and Shah, analyzes an architecture in sparse network to collect data from sensors data Mules are present in the environment. Data is collected when Mules is in close range of sensors. Mules collected data drop off to the access point [13]. o Clustered Aggregation Technique for data collection In cluster aggregation method (CAG) the sensor transmit their data to cluster head that are largely different from the cluster head. CAG is proposed in using spatial correlation of sensors data it reduces the number of transmission and provides result to aggregate queries [14]. o Dual-Sink Using Mobile and Static Sinks in WSNs for data collection The problem of energy loss during the data collection is removing by proposing the Dual sink node which is distributed and energy efficient protocol for that purpose [15] Wu use both static and mobile sink node.

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

o Data Collection in Sensor Networks with Data Mules Data collection in sensing network with data Mules is proposed the protocol for reliable and energy efficient data collection [16]. This paper focused on main phases such as data discovery and data transfer. o Data Gathering Scheme for WSNs with Static and Mobile Sinks for Energy Efficiency To balance the energy consumption among the sensor mobile sink node is used in data collection process. The Problem of energy consumption and large transmission delay is due to the change of sensor route. Static sink node is used with the mobile sink node as in [17]. V RESULT The energy distribution on both scenarios is almost equal. Simulation result shows that the residual energy of network over rounds decreases gradually in both techniques, but there is much efficient energy consumption in our proposed technique. In IEEPB, cluster head sends the data to sink and the larger amount of energy is utilized due to long distance between chain leader and sink. In MIEEPB, chain leaders consume less energy for this purpose due to sink mobility which causes less distance between the chain leaders and the sink. Figure 6.5 presents the comparison of normalized average energy consumption of the MIEEPB with other protocols. Simulation results show the normalized average energy consumption of sensor nodes over rounds in MIEEPB is 2 % better than the previous methods. The distance among sparse nodes themselves and the base station is fewer than in IEEPB; this practice saves plenty of energy. .

Figure.1 : Interval plot- Analysis of Throughput

o Data collection in Sensor Networks with a Mobile Sink for Data Quality Maximization The gateways which are used to communicate with mobile sink node deployed nearby Trajectories[18]. The data quality can be maximize as mobile sink node moving in sensing area along a fixed trajectory to collect data Liang[19].

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

o A Sensor Data Collection Method with a Mobile Sink for Communication Traffic Reduction In Seino, proposed sink node travel in fixed route in sensing area and collect the data from sensors and stored on the base station. Communication traffic can be reduced by delivering the predicated sensor data. In this method the mobile sink node broadcast the predicated value to the sensor and only that sensor can send the data which exceeds the admissible error margin [20]. VI. CONCLUSION In this paper, to address the problem, the priority is to introduce an unequal clustering mechanism to balance the energy consumption among the cluster heads. The Clusters which are closer to the base station have smaller sizes than those farther away from the base station, so cluster heads closer to the base station can preserve some energy for the purpose of inter-cluster data forwarding. Simulation results show that unequal clustering mechanism clearly improves the network lifetime over proposed protocol. Finding a solution that could determine the best value of these parameters according to network scale. The energy consumed by the nodes at time. This is clear that Adaptive technique is more energy efficient and the energy consumption is less in this technique as compared with other routing. After some time of simulation run, this check is performed to get the behavior of the network. VIII. FUTURE WORK o Our proposed protocol Performance analysis and compared results performs well compared to Low Energy Adaptive Clustering Hierarchy. o To evaluate the performance of throughput, the numbers of packets received by BS are compared with the number of packets sent by the nodes in each round. o To analyze the energy consumption of nodes in each round. Residual energy ensures graceful degradation of network life. REFERENCES 1.

Husam Kareem,S.J. Hashim,A. Sali,Shamala Subramaniam, A Survey Of State Of The Art: Hierarchical Routing Algorithms For Wireless Sensor Networks, Journal Of Theoretical And Applied Information Technology April 2014. Vol. 62 No.3 2. Ahmed Salim1, Asmaa Ahmed Badran2 “ Impact of using Mobile Sink on Hierarchical Routing Protocols for Wireless Sensor Networks International Journal of Advanced Science and Technology” Vol.77 (2015), pp.37-48 . 3. Backhyun Kim and Iksoo KimEnergy Aware Routing Protocol in Wireless Sensor Networks, IJCSNS International Journal of Computer Science and Network Security, VOL.6 No.1, January 2006. 4. Yourong Chen, Zhangquan Wang, Tiaojuan Ren, and Hexin Lv, Lifetime Optimization Algorithm with Mobile Sink Nodes for Wireless Sensor Networks Based on Location Information. 5. Teenu Bharti, Mrs. Kusum Dalal, Swati, Comparative Analysis of Routing Protocols Based on Energy Efficiency in Wireless Sensor Network, International Journal of Engineering Research and General Science Volume 3, Issue 3, May-June, 2015 ISSN 2091-2730 6. A Survey about Routing Protocols with Mobile Sink for Wireless Sensor Network, International Journal of Future Generation Communication and Networking Vol.7, No.5 (2014), pp.221-228 7. Bin WANG, Dongliang Xie, Canfeng Chen, Jian Ma and Shiduan Cheng, Deploying Multiple Mobile Sinks in Event-Driven WSNs, This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the ICC 2008 proceedings. 8. Z. Maria Wang, Stefano Basagni, Emanuel Melachrinoudis and Chiara Petrioli, Z. Maria Wang, Stefano Basagni, Emanuel Melachrinoudis and Chiara Petrioli, Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 9. Jun Luo Jacques Panchard Michał Pi´orkowski, MobiRoute: Routing towards a Mobile Sink for Improving Lifetime in Sensor Networks, the optimum trace (in terms of network lifetime) for a mobile sink is the network periphery. 10. J.Boleng, “Normalizing mobility characteristics and enabling adaptive protocols for ad hoc networks,” in Proceedings of the 11th Local and Metropolitan Area Networks Workshop, March 2001. 11. J.Li, J.Jannotti, D.De Couto, D.Karger, and R.Morris, “A scalable location service for geographic ad hoc routing,” in Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking (Mobicom), 2000, pp.120–130.

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457] 12. T.Camp, J.Boleng, and L.Wilco x, “Location information services in mobile ad hoc networks,” in International Communications Conference (ICC), 2002, To appear. 13. Heinzelman, W., A. Chandrakasan and H. Balakrishnan, 2000. “Energy efficient communication protocol for wireless microsensor networks,” in System Sciences, 2000. Proceedings of the 33 Annual rd Hawaii International Conference On, pp: 10. 14. Yun, Y. and Y. Xia, 2010. “Maximizing the lifetime of wireless sensor networks with mobile sink indelaytolerant applications,” Mobile Computing,IEEE Transactions On, 9(9): 1308-1318. 15. Liang, W., J. Luo and X. Xu, 2010. “Prolonging network lifetime via acontrolled mobile sink in wireless sensor networks,” in Global TelecommunicationsConference (GLOBECOM 2010), 2010 IEEE, pp: 1-6. 16. Anas Abu Taleb, Tareq Alhmiedat, Osama Al-haj Hassan, Nidal M. Turab, A Survey of Sink Mobility Models for Wireless Sensor Networks, Journal of Emerging Trends in Computing and Information Sciences, ISSN 2079-8407, Vol. 4, No. 9 September 2013. 17. Husam Kareem,S.J. Hashim,A. Sali, Shamala Subramaniam, A Survey Of State Of The Art: Hierarchical Routing Algorithms For Wireless Sensor Networks, Journal Of Theoretical And Applied Information Technology, ISSN: 1817-3195,Vol. 62 No.3, 30th April 2014. 18. Mukesh Prajapat, Dr. N.C. Barwar, Performance Analysis of Energy Dissipation in WSNs Using Multi-Chain PEGASIS, ISSN:0975 – 8887, International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014. 19. Deepa V.Jose, Dr.G. Sadashivappa. Mobile Sink Assisted Energy Efficient Routing Algorithm for Wireless Sensor Networks, World of Computer Science and Information Technology Journal (WCSIT) ISSN:22210741Vol.5,No.2,16-22,2015. 20. Ahmed Salim and Asmaa Ahmed Badran, Impact of using Mobile Sink on Hierarchical Routing Protocols for Wireless Sensor Networks, International Journal of Advanced Science and Technology, pp.37-48Vol.77 (2015).

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