Energy-efficient Data Dissemination in Wireless Sensor Networks
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1 Energy-efficient Data Dissemination in Wireless Sensor Networks Ji-Han Jiang 1 Kuo-Hua Kao 2 Singing ee 2 1 Department of Computer Science and Information Engineering National Formosa University, Yun-in, Taiwan, R.O.C. jhjiang@nfu.edu.tw 2 Department of Computer Science and Information Engineering National Chung Cheng University, Chia-Yi, Taiwan, R.O.C. geoge.kao@gmail.com singling@cs.ccu.edu.tw Abstract In this paper, a novel data dissemination scheme in wireless sensor network is proposed. A global location-based structure called the transfer posts are adopted to act as the data forwarding stations among sink nodes and source nodes with mobility. The sink nodes can easily request or collect data through the transfer posts in which store the location information of source nodes. The transfer posts are shared by multiple source nodes. Proposed method achieves energy efficiency during query forwarding stage and data delivering stage. Evaluation results show that our method consumes less energy compared to recently results such as two-tier data dissemination (TTDD) [3] and [6]. We have resolved the problem of query forwarding and data delivering among mobile sinks and multiple sources with the remarkable performance. Keywords: Wireless Sensor Networks, Data Dissemination, Mobility, Transfer Post 1. Introduction Wireless sensor network is a multi-hop ad hoc wireless network consisting of hundreds or thousands of sensor nodes deployed randomly. Each sensor node is stationary and is equipped with a sensing device, a limited built-in battery and a short range wireless transmitter-receiver. The sensor nodes are used to monitoring the phenomena in the network, collect interested data, and forward them toward sink nodes that request this data. Some algorithms have been proposed to implement energy efficient communication protocols in wireless sensor network [2, 4, 7, 8]. [3] proposed the TTDD method to build a grid structure according to each source location to handle the requests of multiple mobile sink nodes. However, this method consumes too much energy on building a grid structure for each source node and on executing local query flooding for sink nodes requests. There is another approach recently, the [6] utilizes a virtual infrastructure called rail, which is placed in the middle area of the networks to communicate among sensor nodes, sink nodes and source nodes. However it is inefficient in some situation where the query request has to transmit around the whole rail until it reaches a node that has relevant data. In this paper, we propose a new infrastructure for data dissemination. A global location-based structure called the transfer posts are adopted to act as the data forwarding stations among sink nodes and source nodes with mobility. The infrastructure of transfer posts can be shared by multiple source nodes and use to store the location information of source nodes. For analysis convenient, in this paper the transfer posts are organized as a grid structure shared by all source nodes to reduce energy consumption on building infrastructure. Our method is more energy-efficient by using the transfer posts to resolve the problem of query forwarding of sinks and data delivering of sources. Furthermore, it also avoids local query flooding as well. Our method can be adopted in a wildlife park, battlefield, etc. For example, tourists or zoologists (sink nodes) with a mobile device (for example a PDA) observe the behavior of lion (source nodes) through wireless sensor network in a wildlife park. Figure 1 shows the example. Mobility support brings new challenge to wireless sensor network [1, 3, 4, 6]. uo et al
2 zoologist tourist tourist Figure 1: A wireless sensor network example. Tourists or zoologists (sink nodes) with a mobile device (e.g. a PDA) observe the behavior of lions in a wildlife park. The rest of this paper is organized as follows. Related works are shown in Section 2. Section 3 describes the main concept of our scheme including grid construction, query forwarding, data delivery and mobility support. The communication cost of our method and other approaches are compared in Section 4. Section 5 concludes our work. 2. Related Works Global flooding and mobile sink location updating frequently in wireless sensor network are energy consuming. Thus, recently, extensive researches have been dedicated to the study of energy efficient data dissemination protocols [1, 3, 4, 6]. A scalable energy-efficient asynchronous dissemination protocol (SEAD) [4], proposes a recursive algorithm that searches for minimum energy dissemination tree and saves energy in managing mobile sinks. The sink does not report its current location to the tree. The entire path to the tree is not needed to be readjusted when sinks move out of the tree range. SEAD minimizes energy consumption in both building the dissemination tree and disseminating data to mobile sinks. Visvanathan et al. proposed a hierarchical data dissemination scheme (HDDS) [1] for large-scale sensor network. HDDS routes data towards sinks using a hierarchy of randomly selected dissemination nodes. Because dissemination nodes have limited resources, whenever a dissemination node is overloaded, it inserts another level of dissemination nodes to reduce its load. HDDS reduces energy consumption in sensor network that dynamically adapt to demands for sensor data. In [3], TTDD grid structures are created according to the location of the source node to prevent global flooding and frequent location updates. The grid structure supports mobility of the sink nodes. Query and data are transmitted along the grids and flooding is confined within the local grids only. However grid construction per each source and local query flooding also consume great energy. One of the disadvantages of TTDD is short of the support of the mobile source. The method of was proposed in [6], it defines data dissemination architecture for large-scale wireless sensor networks. system adopts a virtual infrastructure called rail, which is placed in the middle area of the networks so that every node can easily access it. There is only one rail in the network and it acts as a rendezvous area of the events and the queries. Rail communicates among nodes, sinks and sources, and mobility of source nodes are also supported by the. We have noticed that TTDD consumes a considerable energy on grid construction and local query flooding. In our scheme, we reduce the energy consumption of grid construction by using global grid structure (i.e. the infrastructure of transfer posts) and avoid local query flooding by using transfer posts. Also, we have observed that the query forwarding in the system is inefficient that a query request might have to travel around the whole rail until it reaches a relevant data node. We have solved this problem by using the immediate transfer post, which is the transfer post in the same grid with sink node or source node. 3. Our Method In this section, we present the basic model of our scheme. The main goal in our scheme is to reduce energy consumption and support good mobility for source nodes and sink nodes. Our scheme is based on the following assumptions: (1) Sensor nodes are uniformly distributed in the wireless sensor networks. (2) All the sensor nodes in the field are homogeneous and have a constrained energy. Sensor nodes remain stationary after being deployed. (3) Sensor nodes deliver packets to destination hop by hop by simple greedy forwarding algorithm. (4) Each sensor node is aware of its geographic location (for example through receiving GPS signals) (5) There are multiple sinks and multiple sources moving around in the sensor field
3 (6) For analysis convenient, in the following the transfer posts are organized as a grid structure. Once the sensor nodes are deployed, the grid construction process is executed. Then every sensor node is aware of its own grid region and immediate transfer post. Immediate transfer post plays an important role in our method, it directly reduces the energy consumption by avoiding query flooding when sink nodes query. Immediate transfer post also simplifies the communication between source node and sin node. As soon as a source node generates data, it starts preparing for data dissemination by informing all the grids in the sensor field with its geographic location by geocasting. When a sink needs data, it selects a neighbor as the mobile agent. sends a data-query packet to the immediate transfer post, which then propagates the query through other transfer post toward the source. Requested data will be forwarded in the reverse path from the source to the sink. An example of our scheme is shown in Figure 2. F Grid Construction Grid construction is executed only once after the sensor nodes are deployed. We assume that a sensor field spans a two-dimensional plane. We divide the sensor field into grids. Each grid is an α αsquare. For a sensor node s at location (x, y), it can be aware of that it is in the grid g ij, where {i=x/α, j=y/α}. The immediate transfer post of s can be get by the rectangular region of coordinates of the bottom-left corner (α/2+α*i-ε,α/2+α*j-ε) and top-right corner (α/2+α*i+ε,α/2+α*j+ε), where ε is a positivereal number set by the system. Figure 3 shows the grid construction. The size of transfer post directly affects the network performance. The number of nodes in transfer post decreases, as the transfer post gets smaller. Since there are few nodes in transfer post, they have to deal with more operations, such as query forwarding and data delivering. They will consume much more energy than other nodes outside the transfer post and die first. It leads to the hot spot problem and loss of connectivity of the network. On the contrary, if the size of transfer post is too big, the source notification process consume more energy while geocasting information of source nodes to these fields. These geocast messages consume a considerable energy such that the network lifetime decreases. s (α/2+α i-ε,α/2+α j-ε) (α/2+α i+ε,α/2+α j+ε) g 13 α Source node Immediate transfer post of source node A Immediate transfer post of sink node Data notification message Query forwarding Figure 2: An example of our scheme in the wireless sensor network. The remaining of this section will describe step by step to implement our method. The first step is the grid construction, and the second step is source notification, the third step is query forwarding and the forth step is data delivery mechanisms. The final part is mobility support. g Source node Geocasting Figure 3: An example of grid construction and source notification. 3.2 Source Notification Node s Immediate transfer post of node s When a source generates data, it will inform its immediate transfer post with a data-notification message, which includes data type, its location and other information. A - 3 -
4 Immediate transfer post calculates the transfer post of its four neighboring grid and forwards the data-notification message to these fields by geocasting. The neighbor transfer post continues propagating the data-notification message in a similar way. Nodes in the transfer post store the information included in the data-notification message. In our scheme, multiple source nodes share the same global grid structure. Figure 3 shows the source notification. 3.3 Query Forwarding Once a sink begins to collect data, it will select a neighbor sensor node as its mobile agent at first. Then the sink sends out the data-query message to its mobile agent, thus mobile agent forwards the mesage to sink s immediate transfer post. Since all the transfer posts are aware of that where the source node is, while the sensor node in the immediate transfer post receiving the data-query message, it can forward the data-query message to the source node easily. When a transfer post forwards data-query message to the source node, it utilizes a virtual straight line connecting the source node and transfer post itself. Then it selects the next transfer post from its neighbor transfer posts that its distance with the straight line is the smallest. Every transfer post forwards the message to the source node in the similar way till the message reaches the immediate transfer post of source node. During the query forwarding stage, once the transfer post receives the message from upstream transfer post, it stores the location of upstream transfer post. An example is shown in figure 2, transfer post F 2 stores the location of and transfer post stores the location of. 3.4 Data Delivery node only has to report its location to its mobile agent periodically. The mobile sink node s immediate transfer post sends data message to the mobile agent, which in turn relays data message to the sink. As the sink node moves, no new mobile agent is chosen until the sink node moves out of the range of its original grid. Once the sink node leaves the original grid, it will select a neighbor as its new mobile agent and inform its original mobile agent that which grid it enters now and location of its new mobile agent. Then the original mobile agent sends a location update message includes the information of which grid the sink node is in now and location of sink node s new mobile agent to its immediate transfer post. Immediate transfer post utilizes a virtual right-angled triangle separated by midline which is connecting the upstream transfer post and immediate transfer post itself into two, each one is 45 degree. Then it checks whether the new immediate transfer post is in the range of the virtual right-angled triangle. If the new immediate transfer post is in the range of the virtual right-angled triangle, the original immediate transfer post will inform the upstream transfer post that sink node has moved to another grid. Immediate transfer post ocation update G 2 Figure 4(a): (1) moves out of original grid G 1 to grid G 2 and (2) informs its mobile agent and selects a new mobile agent. Mobile agent sends location update to its immediate transfer post and upstream transfer post F F 2 45 G 1 (2) (1) Since the transfer post has stored the location of its upstream transfer post, source node can easily deliver the data message according to the location of upstream transfer post toward the sink node after it received the data-query message. An example is shown in figure 2, source node forwards data messages through -F 2 - to the sink node. 3.5 Mobility Support Immediate transfer post F Sink Mobility As mentioned earlier, the sink node selects a neighbor as its mobile agent. A mobile sink Figure 4(b): Upstream transfer post forwards data messages to transfer post F 2 so that sink node is able to keep receiving data messages
5 Then the upstream transfer post will forward the data message to the new immediate transfer post such that sink node can keep receiving data message. Figure 4(a) and 4(b) shows the operation of mobility support of the first case. Otherwise, the original immediate transfer post will forward the data message to the new immediate transfer post directly. Figure 5(a) and 5(b) shows the operation of mobility support of the second case. Immediate transfer post ocation update Figure 5(a): (1) moves out of original grid G 1 to grid G 2 and (2) informs its mobile agent and selects a new mobile agent. Mobile agent sends location update to its immediate transfer post. Immediate transfer post ocation update Figure 5(b): The original immediate transfer post forwards data messages to the new immediate transfer post F 2 so that sink node is able to keep receiving data messages Source Mobility In our scheme, all the source nodes share the same global grid structure and inform all the grids when they begin to generate data. It would be inefficient that if we re-inform all the grids with the source node s location while source node moving. As a source node moves, G 2 45 F2 G 2 (2) F 2 (1) 45 it sends a location update message to its immediate transfer post without informing all the grids with its new location. We exploit immediate transfer post to represent the mobile source node. Once the immediate transfer post receives the data-query message, it forwards the data-query message to the mobile source node. As the source node moves, no source notification process is executed until the grid count between the source node and its immediate transfer post exceeds a threshold. The value of the threshold allows trade-off to be made between energy consumption on re-informing all the grids and energy consumption on the location update. 4. Performance Analysis In this section, we analyze the communication cost of our scheme. The communication cost of a network is the total amount of traffic generated in the network. The total communication cost directly affects network lifetime. We compare our scheme with TTDD and. 4.1 Model and Notation We assume that a square field of area A in which N sensor nodes are uniformly distributed. There are about N nodes on each side of the field. According to the analysis model of, we assume that there are four types of message: event notification (p e ), query (p q ), data (p d ), and control message (p c ). There are m sinks and n sources in the sensor field. The total number of events and queries can be written as n e and m q, where e is the average number of events and q is the average number of queries. 4.2 Communication Cost We first analyze the worst-case communication cost of our scheme and compare the performance with those of TTDD and. In our scheme, every source node informs all the grids in the sensor network with event notification messages by geocasting. The message meets about 2 / 2 N nodes until it starts geocasting in the immediate transfer post, where N is the number of sensor nodes in a grid in our scheme. N F is the number of sensor nodes in the transfer post. Thus, the communication cost for all the sources notification can be written as - 5 -
6 2 4n ( N / N )( N N F ) P. e 2 The cost for the query to reach a source is ( c N ) p q, where c N is the average number of sensor nodes along the straight-line path from the source to the sink ( c 2). The communication cost of query forwarding can be written as m q( c N ). p q The cost for the data to reach a sink is ( c N ) p d, where c N is the average number of sensor nodes along the straight-line path from the source to the sink ( c 2). The communication cost of data transmitting can be written as n e( c N ) p. d The total communication cost of our scheme is the sum of communication cost of sources notification, communication cost of query forwarding and communication cost of data transmitting 2 4n ( N / N)( N N F ) Pe mq ( c N ) pq ne ( c N ) pd 2 of TTDD can be computed with a similar approach, that is 1 N c 2N p ne c( 2N N ) p. 4N n pc mq q N 2 of can be computed with a similar approach, that is 1 2 mq 2N pq ne p e p q 4 pd mqpq c N. 4 There are two simulation settings, the first one has 5 sink nodes, 1 source nodes and total number of events 1 and the other one has 1 sink nodes, 5 source nodes and total number of queries 1. There are 1, sensor nodes uniformly distributed in the wireless sensor networks. Figure 6 shows the total communication cost of our scheme compared with TTDD and with the first one simulation setting. We can observe that consumes less energy while the number of queries is small. consumes less energy on source notification such that it consumes less energy than our method before the number of queries increase to 35. As the number of queries increase, consumes more energy than our method because its inefficient query forwarding method. Figure 7 shows that our scheme consumes less energy than other approaches while query forwarding and data delivering. Obviously TTDD consumes more energy than other two approaches because of its grid construction and d local flooding strategy Total number of queries TTDD Figure 6: Total communication cost comparison of our scheme, TTDD and TTDD Total number of queries Figure 7: of query forwarding and data delivery of our scheme compared with TTDD and Figure 8 shows the communication cost of the second one simulation setting. Since the there are fewer source nodes than the first one simulation setting, our method consumes relatively less energy on source notification. Obviously our scheme consumes less energy than while the source nodes are fewer. Figure 9 and figure 1 show the effect of number of sink nodes and number of source nodes. In figure 9, we can observe that communication cost increases slightly while the number of sink nodes increase since our method is energy-efficient while query forwarding and data delivering. Figure 1 show that the communication cost increase hugely while the number of source node increase. It is because we utilize geocasting in the source notification stage
7 exploits a global grid structure to support multiple mobile sink nodes and multiple mobile source nodes. Although our scheme consumes more energy than during source notification stage, our scheme is more energy-efficient while query forwarding and data delivering by utilizing the transfer post. From the above evaluation, we can conclude that our scheme consumes less energy than TTDD and and increases network lifetime TTDD Query forwardingand data delivery of our shceme Query forwardingand data delivery of Total number of events Figure 8: Total communication cost and communication of query forwarding and data delivery comparison of our scheme and Number of source nodes Figure 1: Total communication cost of different number of source nodes. 5. Conclusions In this paper, an energy efficient data dissemination method in wireless sensor network is proposed. exploits a global location-based structure to support mobility of sink nodes and source nodes. It provides energy efficient query forwarding and data delivery method as well. Evaluation results show that our scheme consumes less energy than TTDD and especially in query forwarding and data delivering TTDD In the future work, we will focus on the general case with random network topologies and random sensor nodes deployments. In addition, we will also consider the advantages of adjusting positions of transfer posts to meet the practical situation that the wireless sensor networks often change in an unexpected manner Number of sink nodes Figure 9: Total communication cost of different number of sink nodes
8 Reference [1] A. Visvanathan, J. H. Youn, and J. Deogun, Hierarchical Data Disemination Scheme for arge-scale Sensor Networks. In Proceedings of the IEEE International Conference on Communications, Seoul, Korea, May 16-2, 25, Vol. 5, pp [2] C. Intanagonwiwat, R. Govindan, and D. Estrin, Directed Difusion: A Scalable and Robust Communication Paradigm for Sensor Networks. In Proceedings of the Sixth Annual ACM/IEEE International Conference on Mobile Computing and Networking (Mobicom 2), 2. [3] F. Ye, H. uo, J. Cheng, S. u, and. Zhang. A two-tier Data Dissemination Model for arge-scale Wireless Sensor Networks. In Proceedings of Mobile Computing and Networks (Mobicom 22), Atlanta, Georgia, USA, 22, pp [4] H. S. Kim, T. F. Abdelzaher, and W. H. Kwon, Minimum Energy Asynchronous Dissemination to Mobile Sinks in Wireless Sensor Networks. In Proceedings of the First International Conference on Embedded Networked Sensor Systems (SenSys 23), os Angeles, CA, Nov. 5 7, 23, pp [5] J. Chen, Y. Guan and U. Pooch. An Efficient Data Dissemination Method in Wireless Sensor Networks. In Proceedings of the IEEE Global Telecommunications Conference (GOBECOM'4), Dallas, Texas, Nov. 29-Dec. 3, 24, Vol.5 pp [6] J. H. Shin, J. Kim, K. Park and D. Park. : Virtual Infrastructure for Data Dissemination in Wireless Sensor Networks. In the Proceedings of the 2nd ACM International Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN'5), Montreal, Quebec, Canada, Oct. 25, pp [7] T. Shu, M. Krunz and S. Vrudhula. Power Balanced Coverage-time Optimization for Clustered Wireless Sensor Networks. In the Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'5), Urbana-Champaign, I, USA, May 25, pp [8] W. Heinzelman and A. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In the Proceedings of the Hawaii Conf. on System Sciences, Jan. 4-7,
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