• Save
A self localization scheme for mobile wireless sensor networks
Upcoming SlideShare
Loading in...5
×
 

A self localization scheme for mobile wireless sensor networks

on

  • 805 views

 

Statistics

Views

Total Views
805
Views on SlideShare
805
Embed Views
0

Actions

Likes
0
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

A self localization scheme for mobile wireless sensor networks A self localization scheme for mobile wireless sensor networks Document Transcript

  • 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology A Self Localization Scheme for Mobile Wireless Sensor Networks Kyungmi Kim Hyunsook Kim∗ Global Leadership School Computer Course Division of General Education and Handong Global University Teachers Certification Pohang, Gyeongsangbuk-do 791-708, Korea Daegu University kmkim@handong.ac.kr Gyeongsan, Gyeongsangbuk-do 712-714, Korea imissu5081@hotmail.com Youngchoi Hong Global Leadership School Handong Global University Pohang, Gyeongsangbuk-do 791-708, Korea ychoi@handong.ac.kr Abstract— So far a considerable number of studies have been is common to require the latest location of each sensor node conducted on the localization methods for stationary wireless in the network as time goes on MWSN [3]. sensor networks (WSNs). However, little attention has been The GPS is widely used for acquiring accurate positions. given to the localization scheme for a mobile wireless sensor If each sensor node has a GPS receiver, it can estimate its network (MWSN) where all sensor nodes are moving. In this absolute position [8]. But it is too expensive to equip all paper, we propose a self localization scheme with relay nodes nodes with GPS receivers or to configure the location for which transmit the information from an anchor node to a each node manually, which motivates the research on node sensor node over a communication range of one-hop from an self-localization. Most studies on the sensor localization use anchor node. The main idea in our scheme is to select a relay the distance or the angle measurements from anchor nodes node as the one which maintains proximity with an anchor node with GPS. When the percentage of anchor nodes among total longest along its moving direction. Our scheme enables the reduction of energy consumption in MWSN and records nodes is high enough that each node has three anchor nodes in accurate positions of each node. its area, then estimation of the position becomes a simple triangulation problem [9]. To use these triangulation Keywords-component; self localization; mobile sensor nodes; estimations, there should be more than three anchor nodes in relay node selection; anchor node; wireless sensor network the communication range of a sensor node. But, it is difficult to obtain anchor nodes through a one-hop communication I. INTRODUCTION range due to frequent topological change of mobile sensor Both academia and industry have showed a tremendous nodes. interest in wireless sensor networks during the last decade. Therefore to perform more efficient and cost-effective Besides, forthcoming WSNs will consist of large number of localization, it is necessary to set a minimum number of sensor nodes communicating over a wireless channel, sensor nodes with GPS and then use them as anchor nodes performing distributed sensing and cooperative data which are the basis for determining the positions of the processing for various applications [1]. It is critical for the remaining nodes [10]. It is possible to make a node locate sensor nodes to be aware of their own position in practical itself if a mobile sensor node is within the one-hop range applications. The location-awareness sensor nodes may also from anchor nodes. In the case of MWSN, it is necessary for increase the efficiency of routing protocols due to reduced a sensor node to communicate through multiple hops to an message flooding [2], [3]. anchor node to get its position. However, the solutions of the Localization is the process of estimating the position of a conventional work may not be directly applicable to WSNs sensor node. It has been studied for a few decades as a with mobile sensor nodes. Moreover, there have not been fundamental problem in many studies, including navigation studies for node self-localization employing relay nodes to systems, the robot localization problem in mobile robotics estimate the position of mobile sensor nodes. A relay node is [4], and wireless local area networks [5]. But, localizing a to transmit the information from an anchor node to a sensor static sensor node often differs from identifying the position node beyond the one-hop communication range. of a mobile sensor node because the mobile sensor node has In this paper, we propose a self localization scheme which different characteristics [6]. Many applications involve selects the relay nodes to maintain estimations with high mobile networks with unpredictable movement patterns [7]. It accuracy and to reduce the energy consumption for MWSN.978-0-7695-3896-9/09 $26.00 © 2009 IEEE 774DOI 10.1109/ICCIT.2009.140 Authorized licensed use limited to: SRM University. Downloaded on July 19,2010 at 08:13:39 UTC from IEEE Xplore. Restrictions apply.
  • Therefore, we try to select the relay nodes that can sustain the nodes. At last, all sensor nodes and anchor nodes exist in two-position of mobile anchor nodes to achieve the above goals. dimensional space.Our paper has the following key features. First, the moving Under these assumptions, a sensor node hears all thedirection of the anchor node is used to choose the relay nodes. information from the anchor nodes within its communicationIt allows the relay nodes to keep the position of the mobile range. In other words, the anchor nodes should exist within aanchor nodes. Second, the selected relay nodes can send their one-hop radius of a sensor node. But a sensor node can’tinformation on the anchor nodes to the sensor nodes within estimate its position if there are no anchor nodes inside itsthe communication range. As a result, it reduces energy communication range. So the relay nodes have theirconsumption because only the selected relay nodes are positional information from the anchor node inside their one-activated. hop communication range. The relay nodes can send their This paper is organized as follows. We discuss some information received from the anchor node to a sensor node.related works in Section 2 and present an overview and That is, we should choose the best relay nodes to track thediscussion of our method in Section 3. In Section 4, the mobile anchor node and to save energy for communication.performance of the proposed scheme is simulated and It is important to select the relay node based on theverified. Finally, we conclude the paper in Section 5. moving direction of the anchor node, to choose relay nodes according to some conditions, and to activate the least number of relay nodes. The reason for this statement comes II. RELATED WORKS from the following perspectives. The first thing is that a The previous works can be divided into two categories sensor node gets the information of the anchor nodes frombased on their computational methodology: the centralized many relay nodes more than one time in order to locate itselfmethods and the distributed methods. Centralized localization because of the loss of noise and wireless communicationtechniques require the condition of inter-node ranging and channel characteristics. Hence, it is desirable to choose theconnectivity. In this technique, the positional information is optimal relay node that is capable of sustaining the latestsent to a central base station for localization [11]. Then, all position of the mobile anchor nodes taking into account itsthe nodes receive their positional information from a base moving direction. Secondly, lots of communication timestation. Doherty proposed a semi-definite programming demand greater overhead and delay during communicationapproach [12]. In his algorithm, the convex optimization is between two sensor nodes. So, we have to choose relay nodesused to estimate the positions based on the connectivity according to some conditions which will be discussed in theconstraints provided some nodes have their positions. Shang following section, and they will decrease the total number ofpresented a method from mathematical psychology called relay communications between the two nodes. Finally, wemultidimensional scaling [13]. should minimize the number of nodes participating in The distributed algorithms don’t require a central base communication and activate the least number of relay nodesstation. Localization could be done through the node-to-node to save energy for WSNs. Yet, we need to make sure there arecommunication. There are two approaches in the distributed enough relay nodes to ensure that all sensor nodes are located.localization algorithms: the anchor node-based approach and A. Relay node selectionthe anchor node-free approach. Anchor node-baseddistributed algorithms take advantage of some nodes called There are many candidates for relay nodes that are withinanchor nodes which know their absolute locations by a GPS the anchor node’s communication range. To select theor preset placement. The other nodes estimate their positions optimal relay node among those candidates, we consider itsusing the positional information provided by the neighboring distance from the anchor node and its proximity from theanchor nodes [14]. Anchor node-free distributed algorithms anchor node’s moving direction. We use an internal angleuse an unrefined method to localize a sensor node in the between the anchor node’s moving direction and the relaynetwork. So, applying the refinement algorithm customizes its node’s position in order to determine the proximity betweenposition to optimize a local error metric [15]. Another the two nodes. The optimal relay node is obtained from theapproach of the anchor node-free distributed method uses a projected distance of a sensor node along the anchor node’scoordinate system to optimize a network wide metric in a moving direction, which is expressed as follows:distributed manner [16]. DISTANCE × cos(θ i ) where (1) III. OUR PROPOSED SCHEME DISTANCE = ( X A − X si ) 2 + (YA − Ysi ) 2 Our scheme assumes the following four things. First, a Let us assume that the anchor node is moving to the rightGPS-free sensor node estimates its own position by using the and three sensor nodes exist near that area. In Fig. 1, the noderelative distance from the anchor nodes with GPS. Also, the An is an anchor node, and S1, S2, and S3 are the sensor nodes,anchor node sends the positional information of the sensor which can be candidate nodes for a relay node. d1, d2, and d3nodes within its one-hop communication range to the sensor express the distance from each sensor node to the anchornodes using a received signal strength indicator (RSSI). node and θ1, θ2, and θ3 indicate each internal angle betweenSecond, the anchor nodes know the position, speed and each sensor node and the anchor node.direction of their movements. Third, all sensor nodes are notstatic and move very slowly, more slowly than the anchor 775 Authorized licensed use limited to: SRM University. Downloaded on July 19,2010 at 08:13:39 UTC from IEEE Xplore. Restrictions apply.
  • t2~t5 (4) S2 t14~t20 (7) t8~t11 (4) S6 An t1 t2 t3 S3 t4 t5 An t15 S1 t6 t14 t16 An t12 t13 t17 An ~t5 (3) t7 t10 t11 t18 t t8 t9 S5 19 t20 rs = rt S4 t14~t17 (4) t8~t13 (6) Figure 2. Selecting a relay node based on proximity. B. Localization scheme Figure 1. Three candidate nodes for a relay node. The anchor node is able to know its position using its GPS. It can send the positional information of sensor nodes within its one-hop communication range using RSSI TABLE I. PROJECTED DISTANCE OF EACH SENSOR NODE technology. The selected relay node with the positional Projected information notifies its location to other sensor nodes withinNode Distance Internal angle Priority distance its one-hop communication range. This process is done S1 3.5 20 1.76 2 repeatedly until a sensor node knows the locations of three S2 7 40 2.03 1 neighbor relay nodes. After that, the sensor node calculates its location by the triangulation method using three positional S3 9 70 1.03 3 coordinates. In Fig. 3, the sensor node S has the coordination (X, Y) To decide the optimal relay node, we first calculate the and d1, d2 and d3 denote the Euclidean distances between theprojected distance of each sensor node shown in Table I. unknown nodes and the sensor nodes S1, S2, and S3According to the values of projected distance, the node S2 is respectively. The locations of the three relay node candidateschosen as the relay node because it has the highest value of are already known. They are (x1, y1), (x2, y2) and (x3, y3)projected distance and maintains proximity with the anchor respectively.node the longest as the anchor node moves. The node S3 hasa larger angle θ3 and a longer distance from the anchor nodethan any other node. However, the node S3 has lesspossibility of being inside the one-hop range of the anchornode when the anchor node is moving. Therefore, it isdesirable to choose the node S2 than the node S3, which is far (x1,y1)from the anchor node because θ2 is smaller than θ3. S1 (x2,y2) Fig. 2 shows three examples for how to select a relay node d1 (X,Y) d2 S2among sensor nodes when an anchor node moves. The first S1 Sexample is that when the anchor node is at time slot t3, thenode S1 stays about 3 slots and the node S2 stays over 4 slots d3within the one-hop radius of an anchor node when it moves to S3the right. In a similar fashion, the second example is the timeslot t8. The node S3 has duration of about 4 slots within one- (x3,y3)hop of the anchor node, and the node S4 has duration of about6 slots. The third example is for the case of S5 and S6 at thetime slot of t14. The duration of the node S5 to stay within theone-hop communication range is longer than that of the node Figure 3. Localization of a sensor node using triangulation.S6. These clarify that choosing a relay node based on thesensor node with the longest time in proximity to the anchornode is better than selecting the nearest sensor node from the The distances from each relay node candidate to theanchor node. unknown node can be calculated as follows [17]: 776 Authorized licensed use limited to: SRM University. Downloaded on July 19,2010 at 08:13:39 UTC from IEEE Xplore. Restrictions apply.
  • positions, speed and direction. All sensor nodes are not static ⎧( X − x1 ) 2 + (Y − y 1 ) 2 = d 1 2 ⎪ and move more slowly than the anchor nodes. ⎪ 2 2 ⎨( X − x 2 ) + (Y − y 2 ) = d 2 2 (2) ⎪ 2 2 2 ⎪( X − x 3 ) + (Y − y 3 ) = d 3 ⎩ Solving for X and Y, we get the coordinates of theposition-unknown node by 2 2 2 2 2 2 2 2 2 2 2 2 ( y 2 − y1 )(x 2 − x3 + y 2 − y 3 − d 2 + d 3 ) − ( y3 − y 2 )(x1 − x2 + y1 − y 2 − d1 + d 2 ) X= 2 ((x 2 − x1 )( y3 − y 2 ) − ( x3 − x2 )( y 2 − y1 )) (3) 2 2 2 2 2 2 2 2 2 2 2 2 ( x − x )(x − x3 + y 2 − y 3 − d 2 + d 3 ) − ( x3 − x 2 )(x1 − x2 + y1 − y 2 − d1 + d 2 ) Y= 2 1 2 2 ((x3 − x2 )( y 2 − y1 ) − ( x2 − x1 )( y 3 − y 2 ))C. Node state transition diagram Fig. 4 shows a sensor node state transition diagram. Figure 5. The number of rounds when the nodes die. Fig. 5 shows the number of rounds when a sensor node dies. The x-axis represents the number of dead sensor nodes, and the y-axis represents the time in rounds which are obtained by descending order. We simulate these in two cases: One is the case of deploying relay nodes in the network and the other is a scheme of not having relay nodes. A sensor node in the case of deploying relay nodes has a longer lifetime than the other. Our scheme of using the relay nodes has more desirable energy expenditure than the method of not Figure 4. State transition diagram for a sensor node. using the relay nodes. Fig. 6 shows how long the relay nodes and the sensor nodes stay in one-hop communication range from an anchor There are three states; the sleep state, the discovery state node. As shown in the figure, the duration of selected relayand the active state. We define sleep state as a state where nodes to stay within one-hop communication range from ancommunication and sensing are turned off to reduce energy anchor node is mostly larger than that of the sensor nodes.consumption. Discovery state is defined as receiving signals This makes the proposed scheme spend less power than thefrom other sensor nodes while sensing. If a sensor node is in scheme without relay nodes.active state, it has four roles; monitoring the anchor node,broadcasting its information to other neighboring sensornodes, determining whether a node should become a relaynode and estimating its own location as well. IV. SIMULATION RESULTS We consider a 200 x 200 network configuration with 200nodes throughout the simulation. Some important simulationparameters are listed in Table II. TABLE II. SIMULATION PARAMETERS. Parameter Value Parameter Value Transmission Number of AN 5 720mW energy Speed of Receiving 2 m/s 369mW AN(mean) energy Transmission 20m Initial energy 500kW range Figure 6.The duration of a node staying within one-hop radius of an anchor In our simulations, each node moves at a constant unit node.speed in random directions, and the anchor nodes know their 777 Authorized licensed use limited to: SRM University. Downloaded on July 19,2010 at 08:13:39 UTC from IEEE Xplore. Restrictions apply.
  • [1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless Sensor Networks: A Survey,” Computer Networks, vol. 38, no. 4, pp. 393-422, 2002. [2] B. Karp and H. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. ACM MobiCom ’00, pp. 243-254, Aug. 2000. [3] Y.B. Ko and N.H. Vaidya, “Location-Aided Routing (LAR) in Mobile Ad Hoc Networks,” Wireless Networks, vol. 6, Issue 4, pp. 307-321, 2000. [4] A. Howard, M. Mataric, and G. Sukhatme, “Localization for Mobile Robot Teams Using Maximum Likelihood Estimation,” Proc. IEEE/RSJ Int’l Conf. Intelligent Robots and Systems, Oct. 2002. [5] N. Sundaram and P. Ramanathan, “Connectivity Based Location Estimation Scheme for Wireless Ad Hoc Networks,” Proc. IEEE Global Telecomm. Conf. (Globecom ’02), vol. 1, pp. 143-147, Nov. 2002. [6] Qingjiang Shi, Chen He, Lingge Jiang and Jun Luo, “Sensor Network Localization via Non differentiable Optimization,” Proc. IEEE Figure 7. The time needed to locate each node using three relay nodes’ Telecomm. Conf. (Globecom ’08), pp.1-5, Dec. 2008. positions. [7] B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, M. Goraczko, A. K. Miu, E. Shih, H. Balakrishnan, and S. Madden. “Car-Tel: A Distributed Fig. 7 shows the time needed to find out the location of Mobile Sensor Computing System,” Proc. 4th ACM SenSys, pp. 125-each node using three relay nodes’ positions. We find that 138, Nov. 2006.75% of all nodes successfully estimate their position within [8] Qiao-ling Du, Zhi-hong Qian, Hong Jiang, Shu-xun Wang,200 rounds, and 13% of the nodes find their positions “Localization of Anchor Nodes for Wireless Sensor Networks,” Proc. New Technologies, Mobility and Security, NTMS 08, pp.1-5, Nov.between 200 and 500 rounds. The remaining 12% of the 2008.nodes need more than 500 rounds to find their positions. In [9] Liqiang Zhang, Qiang Cheng, Yingge Wang, Sherali Zeadally, “Ageneral, most of the nodes can successfully find their Novel Distributed Sensor Positioning System Using the Dual of Targetpositions within 4% of their entire lifetime. Tracking,” IEEE TRANSACTIONS ON COMPUTERS, vol. 57, no. 2, pp. 246-260, Feb. 2008. V. CONCLUSIONS [10] Mark R. Morelande, Bill Moran and Marcus Brazil, “Bayesian node In this paper, we propose a self localization scheme which localisation in wireless sensor networks,” Proc. Acoustics, Speech and Signal Processing, ICASSP 2008, pp.2545-2548, 2008.deploys the relay nodes properly to maintain estimations with [11] Ganggang Yu, Fengqi Yu, “A Localization Algorithm for Mobilehigh accuracy and to reduce the energy consumption for Wireless Sensor Networks,” Proc. IEEE International Conference onMWSN. The main idea in our scheme is to select a relay node Integration Technology, pp.623-627, Mar. 2007.as the one which maintains proximity with an anchor node [12] L. Doherty, K. Pister, and L.-E. Ghaoui, “Convex position estimationlongest along its moving direction. An internal angle between in wireless sensor works,” Proc. IEEE Infocom, vol. 3, pp.1655-1633,the anchor node’s direction and the position of a sensor node Apr. 2001.is used to determine the proximity between the two nodes. [13] Y. Shang, W. Ruml, Y. Zhang, and M. Fromherz, “Localization from Our scheme clearly enhances the accuracy of locating Mere Connectivity,” Proc. 4th ACM international symposium on Mobile ad hoc networking & computing, MobiHoc 2003, pp. 201-212,mobile nodes and reduces the total energy consumption for 2003.MWSN. Finally, we found that adopting the relay node is [14] T. He, C. Huang, B. Blum, J. Stankovic and T. Abdelzaher, “Range-beneficial to accurate locating in MWSN but needs to be free localization schemes in large scale sensor networks,” Proc. 9thimproved for various environment or applications in this Annual International Conference on Mobile Computing andinitial study. As part of our future work we will extend our Networking, pp. 81-95, 2003.algorithm to improve the accuracy by diversifying the [15] N. Priyantha, H. Balakrishnan, E. Demaine, and S. Teller, “Anchor-conditions of the relay node qualification for a self free distributed localization in sensor networks,” Proc. 1stlocalization scheme in MWSN. International Conference on Embedded Network Sensor Systems, pp. 340-341, Nov. 2003. ACKNOWLEDGMENT [16] S. Capkun, M. Hamdi and J.-P. Hubaux, “GPS-free positioning in mobile ad-hoc networks,” Proc. 34th Annual Hawaii International This research was supported by Handong Global Conference on System Sciences, vol. 9, pp. 3481-3490, Jan. 2001.University Research Grants 2008. [17] X. Yu, K. Niyogi, S. Mehrotra, and N. Venkatasubramanian, “Adaptive Target Tracking in Sensor Networks,” Proc. Communication Networks and Distributed Systems Modeling and REFERENCES Simulation Conference, Jan. 2004.∗ Correspondent Author 778 Authorized licensed use limited to: SRM University. Downloaded on July 19,2010 at 08:13:39 UTC from IEEE Xplore. Restrictions apply.