A hybrid routing tree to avoid the energy hole problem in wireless sensor network

1. A hybrid routing tree to avoid the energy hole problem in wireless sensor network Yuhua Liu, Wenwen Dai, Kaihua Xu, Meirong Zheng Department of Computer Science Huazhong Normal University Wuhan, China Email:yhliu@mail.ccnu.edu.cn

2. Outline • Introductions • Related Work • Wireless and network model • Network model • Energy consumption model • Protocol Descriptions • Initialization of the minimum cost routing tree • Data transfer phase • The maintenance of routing tree • Algorithm Description • Network Lifetime • Simulation Analyses • Network Lifetime • Energy efficiency • Summaries and Outlook

3. Introductions • The wireless sensor network is a self-organizing network system, which is formatted by multiple hops radio communications among the tiny sensor nodes. Those sensor nodes are deployed in the monitoring area to perceive, collect and dispose the information from the monitoring objects in the network, and send the information to observer. • The energy, the ability of calculation and communication of those sensor nodes are limited. So, design a rote algorithm with high-efficiency and low-energy consumption to prolong the lifetime of networks is very important.

4. Related Work (1/2) • Related works show that the sensor network has the phenomenon of uneven energy consumption. A study on this problem developed by literature [5] suggests that there is remaining more than 90% of the initial energy when the network died. • Many research studies have been carry out on this topic. Literature [6]’s model focuses on the deployment. Literature [7]’s model draws attention on mobile sensor nodes and so on.

5. Related Work(2/2) • This article bases on the literature [3]’s network model, building the minimum cost hybrid routing tree by Kruskal, and making the communication among nodes switch between single hop and multi-hop under the effect of energy threshold and distance threshold. This algorithm avoids the "energy hole" phenomenon by sharing the energy consumption to each layer from outside to inside gradually.

6. Wireless and network model • Shown in Figure 1, this paper uses the minimum cost routing tree which is based on ring network model and uses hybrid routing idea to solve the "energy hole" problem. • Energy consumption model Fig. 1. Ring network model

7. Protocol Descriptions (1/6) • Initialization of the minimum cost routing tree Sensor nodes send a short message to sink node after the deployment of network. The message includes the residual energy of node and the node’s ID. Sink node generates the topology distribution of the whole network and produces a minimum cost spanning tree with sink node as the root of the tree. Finally, sink node sends "notification route" message to all the nodes, and requires each node to confirm.

8. Protocol Descriptions (2/6) • Data transfer phase • After initialization, it considers the nodes in the ring and the ring. It uses multi-hop manner to send data to sink node when ,while the nodes send data to sink node directly when .

9. Protocol Descriptions (3/6) • The proper number of the middle ring Fig. 2. Number of middle ring and the remaining energy comparison

10. Protocol Descriptions (4/6) • The maintenance of routing tree • Minimum cost routing tree must consider the situation of nodes’ death caused by energy consumption and natural damage in practical applications. Hence, the new agreement in this paper adds the necessary route maintenance strategy.

11. Protocol Descriptions (5/6) • Algorithm Description • Step1: Initialize the network. 200 nodes are deployed in a ring area randomly, the width of each ring is same to each other and the ring which is close to sink has high-density nodes. • Step2: Sink node obtains the distribution of the whole network and generates the minimum cost routing tree. • Step3: Sink node sends route messages to all sensor nodes according to the minimum cost routing tree. • Step4: Sink node calculates the number of middle ring and sends message to all nodes in middle ring and tells those nodes to forward the data from other ring.

12. Protocol Descriptions (6/6) • Algorithm Description • Step5: Sensor nodes need determine its ring number before sending data to sink: If the ring number is lager than middle ring: all nodes in the ring communicate by multi-hop. Otherwise, nodes send the monitored data and its own residual energy information to sink node directly. • Step6: Sink nodes deal with the collected information simply and calculate the average residual energy value • Step7: Compare and : If , the sink node sends a message of replacing the middle ring to the outer ring;Otherwise: sink node does not send any message. • Step8: Nodes determine whether its link is connected. If it is not connected, it will change its parent node, otherwise, turn into step 2.

13. Simulation Analyses Table 1. The parameters in simulation

14. Simulation Analyses • Network Lifetime This article defines when a certain ring of death that all the nodes that the network killed. Fig. 3. Network Lifetime

15. Simulation Analyses • Energy efficiency The HRTBR algorithm can solve the shortage of the two algorithms. It makes each node in the network uses energy equally and extends the network lifetime and improves the utilization of energy in the network. Fig. 4. Energy efficiency

16. Simulation Analyses • The nodes far from the base station must transmit data over long distances and consume a large amount of energy when using Direct mode routing policy • The nodes near the base station will overload for forward data from other nodes and consume their own energy largely when using Multi mode routing policy • This paper uses energy threshold and middle ring to control the balance of these two means of communication, not only take into account the residual energy of nodes, but also consider the long-distance communication and different energy consumption. Therefore, the proposed algorithm, comparing with the above routing algorithm, can improve energy efficiency and prolong network lifetime at a great advantage.

17. Summaries and Outlook • The simulation analyses tell us this algorithm can effectively avoid the energy hole problem and prolong the network lifetime. The algorithm has good scalability and adapt to the physical environment. Therefore, we should consider using this method in the clustering sensor network in our next study. We hope it can be applied on a larger scale network.

18. Reference • [1] Song Chao, Liu Ming, Gong Hai-gang et al. ACO-based algorithm for solving energy hole problem in Wireless Sensor Networks. Journal of Software, 20(10):2729-2743.(2009) • [2] Liliana Gavrilovska, Srdjan Krco, Veljko Milutinovic, Ivan Stojmenovic, Roman Trobec. Application and Multidisciplinary Aspects of Wireless Sensor Networks : Concepts, Integration, and Case Studies. Springer-Verlag New York,Inc.282, (2010) • [3] Olariu S, stojmenovic I.Design. guidelines for maximizing lifotime and avoiding energy holes in sansor networks with uniform distribution and uniform reporting．In：Domingo-Pascual J, ed.Proe.of the IEEE INFOCOM.New York：IEEE Communications Society, 1-12.(2006) • [4] LI Cheng-Fa, CHEN Gui-Hai, YE Mao, WU Jie. An Uneven Cluster-Based Routing Protocol for Wireless Sensor Network. Journal of Computers, 30(1):27-36.(2007) • [5] Lian J, Naik K, Agnew G.Data capacity improvement of wireless sensor networks using non-uniform sensor distribution.Int’I Journal ofDistilbuted, Sensor Networks, 2(2):121-145.(2006) • [6] Li J, Mohapatra P．Analytical modeling and mitigation techniques for the energy hole problems in sensor networks．Pervasive and Mobile Computing, 3(3):233-254.(2007)

19. [7] Shine HY, Yu GJ, Sheu JP.Energy hole healing protocol for surveillance sensor networks.In:Proc.of the Workshop OIl Wireless,Ad Hoc,and Sensor Networks(WASN).(2005). • [8]HE Guo-yuan, CHEN Di. High Energy-Efficient Routing Protocol Based on Optimal Cluster-Heads for Wireless Sensor Network.Journal of Sensor and Actuators. 21(10):1739-1743(2008)

20. Any queation? Thank you! 2011-12-13