Performance Evaluation of DV-Hop and NDV-Hop Localization Methods in Wireless Sensor Networks

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1 Performance Evaluation of DV-Hop and NDV-Hop Localization Methods in Wireless Sensor Networks Manijeh Keshtgary Dept. of Computer Eng. & IT ShirazUniversity of technology Shiraz,Iran, And Mohammad Hadi Tabeshfaraz Dept. of Computer Eng. & IT Tehran University Kish, Iran, And Masoud Fasihy Dept. of Computer Eng. & IT Amirkabir University Tehran, Iran, ABSTRACT Knowledge of nodes locations is an important requirement for many applications in Wireless Sensor Networks. In the hop-based range-free localization methods, anchors broadcast the localization messages including a hop count value to the entire network. Each node receives this message and calculates its own distance with anchor in hops and then approximates its own location. In this paper, we review range-free localization methods and evaluate the performance of two methods: DV hop and NDV-Hop by simulation. Recent papers are mostly concentrated on the number of anchors for NDV-Hop and no other parameters like network area and distribution model. Here, we consider the effect of area and distribution model on localization accuracy. Keywords: Hop-based, Accuracy, Localization, Wireless Sensor Networks. 1. INTRODUCTION WSN is usually constructed with large number of sensor nodes, which are heavily organized within the monitored area [1]. Algorithm in localization technology is an important issue in WSN. In WSN technology, knowledge of where the information has been obtained is very vital and important. When an event takes place, it can only be recognized and processed if the position of the place that generates the information is known. At present, the widely used poisoning system is GPS [] (Global Position System). The nodes with GPS receiver is localized by receiving the real time information from GPS satellite. The GPS has advantages of high accuracy, good real time, and high anti-jamming performance, etc. However, this method is not a suitable solution for localization because of the below reasons [11]. 1. GPS can t be used as an in indoor solution since it can t be placed in a satellite line of sight.. GPS consumes lots of energy and reduces the network lifetime. 3. GPS is expensive and can t be used in largescale sensor nodes. In the most of localization methods, limited numbers of nodes are location-aware which are called Anchors. Anchors can be fixed or mobile. Some methods like mobile beacon, mobile anchor

2 [3], and single mobile beacon [4] use mobile anchors. The advantage of these methods is that a mobile anchor can be used instead of many fixed anchors, and in each location, it can be considered as a fixed anchor. However, the mobility could cause some problems. Other localization methods use Fixed Anchors. In this method, localization can be commenced by anchors. They broadcast their own location to the network and three other anchors in order to calculate their own location. In this method, the accuracy of localization depends on the approximate value of own location. The localization algorithm is generally divided into two categories: range-based and range-free algorithm. Range-based methods use some measurement equipment for calculation of distance. Some of these methods are DV-Distance [5], Euclidean [5], N-hop Multitration [6], and Robust Sensor Localization [7]. Extra hardware and additional energy consumption are important bottleneck for these methods. Another category of localization methods named range-free, don t use measurement equipment, so they have lower cost. In hop-based range-free methods, nodes estimate the distance by counting the hops to the anchors. Hop-based range-free methods have no extra hardware and flexible. Localization precision is more practical for implementation in any environment, so we concentrate on this category of localization method. We consider DV-hop [5] and NDV-HOP [8] as typical algorithms of this category and evaluate their localization error using simulation. Recent researches [9, 1], improve the DV-Hop to increase the accuracy of localization method. Here we consider classic DV algorithm. Therefore, classic DV-HOP can be seen and used as a benchmark for evaluating the errors and accuracy range in NDV-HOP Localization method. The rest of this paper is organized as follow. We discuss DV-Hop and NDV-HOP methods in sections and 3. We evaluate the efficiency of these two methods focusing on their localization errors in section 4. We conclude the paper in section 5.. DV-HOP LOCALIZATION METHOD Niculescu and Nath [5] introduce a classic DV-Hop method which is similar to the distance vector routing schemes. This method includes three stages: First, Anchors distribute their localization message to the entire network. This message may include fields such as Anchor ID, Location, and Hop-count. Hop-Limit is defined as the maximum number of hops that a localization message can be alive. Each node receives this message and stores it in its memory, increment the hop-count by one and forwards this message for neighbors if the hopcount is less than or equal to the hop-limit, otherwise the message will be killed by sensor node. If a node receives more than one message from an anchor, the shortest path will be considered; the new message will be ignored and the sensor node only forwards the message. According to this fact that the first message from an anchor include the shortest hop-length, each node considerers only the first message from each anchor and ignore the next messages. When a node receives localization messages from 3 anchors in hops, this step will be terminated. [11] If any anchor receives a localization message from an anchor, store it to calculate the AHL (Average hop Length). For example in figure 1, we have 3 anchors (a1, a and a3). Figure 1: DV-Hop example The distance from a1 to a is 4m, a to a3 is 75m and a1 to a3 is 1m. The hop-count from a1 to a is, a to a3 is 5 and a1 to a3 is 6. Each anchor calculates own AHL as follows: AHL (a1) = (1+4) / (6+) =17.5

3 AHL (a) = (4 + 75) / ( + 5) = 16.4 AHL (a3) = (75 + 1) / (5 + 6) = 16.4 In the second step, each anchor distributes the AHL to the entire network. Each anchor receives this packet and considers the first AHL receives from nearest anchor. For example in figure 1, for node n, the first AHL received from a is 16.4, so the distance from anchors for node n is calculated by multiplying the minimum hop number and average distance of each hop: n-a1=3*16.4=49.6 n-a=*16.4=3.84 n-a3=3*16.4=49.6 Now, each node is able to estimate the location by Multilateration method. Let's see how the location could be estimated. Assume that (x i,y i ) is the location of ith anchor and r i is the distance of a node to this anchor. If (x u,y u ) is the location of the node, then we have from Euclidean distance equation: We subtract this equation with i=3 from equation with i=1 and i= and simplify equation based on x u and y u then: ( ) ( ) By converting these equations into a matrix we have: [ ] [ ] = [ ] (5) Now x u and y u can be calculated easily [11] 3. NDV -HOP LOCALIZATION METHOD X. Zhang, H. Xie and X. Zhao [1] proposed some improvements over DV-Hop from following three aspects: Average hop distance is calculated by selecting all anchors. Classic DV-Hop uses only two anchors to calculate average Hop length (AHL), But, experiments shows that the more anchors are considered, the lower localization error is. For the applications which need high accuracy, all the anchors can be considered when calculating AHL. This method is adopted in order to obtain higher accuracy of localization. AHL is corrected by anchors. In this method, the distance between nodes Beacon can be calculated by multiplying the distance between each hop and the recorded hops. For example; the approximate distance can be estimated and shown from the node Beacon i till node Beacon j by : (6) where HopSize i denote the average hop distance calculated by beacon node i, and hop i,j is the number of hops between beacon nodes i and j.at the same time,the actual distance between beacon node i and j can be calculated according to the selfposition information and that of beacon node j obtained in the first phase. The actual distance between i and j can be estimate by formula (7): = ( ) ( ) (7) At the same time the approximate error of hop between i,j node can be calculated. Difference i,j between estimated distance d est and the real i,j distance d rel can be divided to the number of hops between them. hopmod i,j i =(d i,j est -d i,j rel )/hop i,j, wher eh hopmod i,j i is the average hop error. Finally, the location of boundary nodes is corrected by considering the network bounds. This is a fact that the estimated location for any nodes should be satisfies some conditions, such as xmin x xmax (9) ymin y ymax (1) Where xmin and xmax are the minimum and maximum value of along the x axis in the monitored area respectively. So for the x-axis, if x<xmin, replace x with xmin, and if x>xmax, replace x with xmax. For the y-axis, the same replacement is done.

4 So, the out-of-scope problem has been avoided and relative error decreases. Therefore, we can say that NDV-HOP method has advantages over the classic DV-HOP because it uses all the distance between node Beacons in the network space, in order to find an accurate location compared to classic DV-Hop. 4. SIMULATION RESULTS We have used OMNET++ 3. to simulate these methods. OMNET is an object oriented and eventdriven software based on C++. Implemented model is formed by hierarchical modules communicating by messages. Simulation parameters are: - Network size (the number of sensor nodes) - The number of anchors. - Range of sensor nodes. - Range of anchors. - Distribution model of sensor nodes The network model is set as follows: All the nodes in the network are homogenous, and there is no influential factor in the communicating procedure with one another. All the nodes have the same communication radius, success probability of the communication and flooding routing protocol. 1 nodes are randomly distributed in different area (5*5,1*1,15*15,* ) At first, we will evaluate the performance of DVhop and NDV-hop algorithm performance with respect to different area in a uniform model. Then we do the same evaluation for normal model. Figures, 3 and 4 show the localization errors in uniform model for anchor nodes of 5, 1 and when there has been an increase in area. shows the area of network in figures. In the figure, the localization error for 5 anchors nodes in the area of (5*5, 1*1,15*15 ) is shown. As it can be seen, the localization error in the NDV-HOP is much less than DV-HOP although. With an increase in the number of anchor nodes, the error is reduced in the NDV-HOP and difference between accuracy of these two algorithms is more. For instance; in the area of 5*5, the localization errors of NDV- HOP localization for 1 anchor nodes is approximately.3637 where as in DV-HOP is around localization error ndv-hop dvhop Figure : Localization error in uniform distribution (for 5 anchors) The evaluation parameter is: Localization error: The difference between estimated coordinates and real coordinates divided by communication radius, which can be described as RE= R i -E i /R.where R i denotes real coordinates, E i is estimated coordinates and R is the communication radius Localization Error Evaluation localization error ndv-hop dvhop Figure 3: Localization error in uniform distribution (for 1 anchors)

5 localization error ndvhop dv-hop that are more practical in WSN: classic DV-Hop and NDV-Hop. Localization error of NDV-hop is less than DV-Hop because it uses different error correction scheme. In both methods, localization error increases with increasing the area, but NDV- Hop has better accuracy in large-area networks. Also we found that accuracy in uniform distribution is better than normal distribution. As the result, NDV-Hop method has low localization error in uniform distribution. For future work, we will consider other parameters for performance evaluation of these two methods such as energy consumption and fault tolerance. Figure 4: Localization error in uniform distribution (for anchors) Until now, we assume that nodes are distributed in a uniform model. Now we study the localization error in non-uniform networks. We consider normal distribution model because this model is more feasible than the others. Figure 5 compares the localization error for the case of anchors and NDV-Hop algorithm with two different distribution models, Uniform and normal. As we can see, Localization error in normal distribution is more than uniform networks. It means that the performance of NDV-Hop method in uniform networks is better than other distribution models such as normal Figure 5: Localization error of NDV-Hop in normal and uniform distribution (for anchors) 5. CONCLUSIONS Normal Uniform Localization is an important challenge in the wireless sensor networks. In this paper, we evaluate performance of two hop-based range-free methods 6. REFERENCES [1] Z. Li, R. Li, Y. Wei and T. Pei, "Survey of localization Techniques in Wireless Sensor Networks", Information Technology Journal 9 (8), 1, pp []A. M. Youssef, M. Youssef, A Taxonomy of Localization Schemes for Wireless Sensor Networks", Proc. Of International Conference on Wireless Networks (ICWN 7), Las Vegas, USA, 7, pp [3] K. F. Ssu, C. H. Ou and H. C. Jiau, "Localization with Mobile Anchor Points in Wireless Sensor Networks", IEEE Transactions on Vehicular Technology, vol. 54, No.3, 5, pp [4] A. Galstyan, B. Krishnmachari, K. Lerman and S. Pattem, "Distributed Online Localization in Sensor Networks Using a Moving Target", Proceedings of third international symposium on information processing in sensor networks (ISPN). Berkeley, 4, pp [5] D. Niculescu and B. Nath. "Ad Hoc Positioning System (APS),'' Proc. of the IEEE GLOBECOM 1, San Antonio, 1, pp [6] A. Savvides, H. Park and M. Srivastava, "The bits and flops of the N-hop multilateration Primitive For Node Localization Problems", First ACM International Workshop on Wireless Sensor Networks and Application (WSNA), Atlanta Georgia. USA,, pp

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