A Data Delivery Mechanism to Support Mobile Users in Wireless Sensor Networks Euisin Lee, Younghwan Choi, Soochang Park, Donghun Lee, and Sang-Ha Kim Department of Computer Engineering Chungnam National University 220 Gung-dong, Yuseong-gu, Daejeon, 305 764, Republic of Korea Emails: {eslee, yhchoi, winter, dhlee}@cclab.cnu.ac.kr and
[email protected]
Abstract— Wireless sensor networks traditionally consist of sensors perceiving data and sinks gathering the data. In addition, users receive required information from the sinks via infrastructure networks. The users, however, should receive the information from the sinks through multi hop communications of disseminated sensor nodes if such users move into the sensor networks without infrastructure networks. Unlikely, the previous works only considered mobility of sinks, which function users. Nevertheless, it is difficult for such approaches about mobility to exploit the existing data-centric routing algorithms and also for the mobile sinks to function as gateways to connect with infrastructure. To improve the shortcomings, we suggest a novel viewpoint of mobility for wireless sensor networks and propose a novel architecture and mechanism to support the mobility with multiple static sinks in this paper. The multiple static sinks, which are connected with each other via infrastructure, provide high throughput and low latency. Furthermore, they improve hotspot problems and prolong network lifetime. The proposed mechanism finally is evaluated by simulation results about throughput, latency, and network lifetime.
infrastructure networks except sensor networks are more actually. Because, infrastructure networks in these applications cannot be used because they are damaged as a result of the war or the disaster. Hence an assumption that a user and a sink can directly communicate through internet has a problem that is not actually. Therefore communication between the user and the sink inside sensor fields is supported by only sensor nodes. Second form is same with figure 3. It identifies a user with a sink. So it supports a mobility of the user by reflecting movement of the user with the direct movement of the sink [5~9]. But, researches for this form have also various problems. First of all, they cannot use existing effective data collection algorithms [2][3][4] between a sink and sensor nodes based on data in static sink sensor networks. Because, such algorithms can hardly be exploited due to location change of sink which collects data if sinks in sensor networks have
Index Terms— wireless sensor networks, mobility, users, and multiple static sinks
1. Introduction Wireless sensor networks traditionally consist of sensors perceiving data and sinks gathering the data. In addition, users receive required information from the sinks via infrastructure networks. A mobility model in wireless sensor networks, mentioned above, can classify according to each objects. Namely, it is a mobility of sensor node, a mobility of a sink, and a mobility of a user. Hence, deciding a mobility of what kind of object for sensor networks that suits sensor networks according to various applications is important. Recently, applications transmitting data to moving users inside sensor fields such as rescue in disaster area or maneuver in the war zone are on the rise in large-scale sensor networks [5]. But, until now, such researches support a mobility of user by only two forms for these applications. First form is same with figure 2. It supports a mobility of a user on the assumption that the user communicates directly sinks through infrastructure networks, namely, internet like communication systems in traditional sensor networks [1]. But, in applications such as rescues in disaster area or maneuvers in the war zone, circumstances without
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Figure 1. Typical wireless sensor networks model
Figure 2. A model to support mobility of user through infra structure networks, namely, internet & satellite.
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Figure 3. Mobile sink model
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mobility. They have also a defect which is hard to make full use of gateway between sensor networks and Internet. The other problem is that the cost of the overhead to reorganize network topology and reconstruct dissemination paths from sensor nodes to the mobile sink is expensive. Sink mobility causes topology reconstruction in case of the network topology where the sink participates in network construction. Also, although the sink doesn’t join in network topology construction, there could be control overhead for regenerating data dissemination paths to new sink location. It is enormous overheads to sensor nodes with the constrained energy. Hence, we propose a novel communication model of collecting data through sensor node using static sink and delivering the data to a moving user within sensor fields and a novel mechanism to support mobility of users. But, one static sink is a problem that when the user is a long distance, the data isn’t effectively transmitted because a communication between the user and the sink must communicate through multiple hops of sensor nodes. Also it is a hot spot problem which is carried a disproportionate amount of traffic to sensor nodes near the sink Accordingly, we will solve the problems of a single static sink using multiple static sinks as shown in Figure 4. And we will support the ultimate goal of this paper, namely, a mobility of a user. In our proposed mechanism of this paper, if a user intends to obtain information on moving, the user disseminates interest to the nearest sink via a sensor network. The sink, received interest from the user, collects information from sensor nodes using the existing data collection algorithm in static sink sensor networks [2][3][4]. The sink shares the information with every sinks through infrastructure networks. The user requests the shared information to the nearest sink according to a location of the user and receives the shared information from the sink. A proposed mechanism can obtain various advantages with multiple static sinks. First of all, a user selects a nearest sink to its position regardless of location. Therefore short hops communications between a user and a sink are possible. So, it saves energy and enhances data delivery ratio, and reduces delay. Also, because a user requires a dissemination of interests through multiple static sinks, locations of data collection are diverse. It solves a hot spot problem which is carried a disproportionate amount of traffic to sensor nodes
Figure 4. A Novel Communication Model of Wireless Sensor Networks
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near the sink [15]. As a result, the lifetime of the sensor networks will be able to increase because the balanced energy consumption of sensor nodes is possible. We verified through simulation that the lifetime of sensor networks is prolonged because a use of multiple static sinks decreases an energy consumption of sensor nodes. Also, we verified that a performance about the data delivery ratio and the delay never falls nevertheless a communication between the user and the sink for guaranteeing movement of the user is supported by only sensor nodes without infrastructure networks, namely, internet(not understand). The rest of this paper is organized as follows. In Section 2, we present mobility of sensor networks. Section 3 describes a proposal mechanism. Simulation results are presented in Section 4 to evaluate the effectiveness of our design and analyze the impact of important parameters. Section 5 concludes the paper.
2. Mobility of Sensor Networks Wireless sensor networks typically consist of the three objects as shown in Figure 1: user, sink, and sensor node [1]. Depending on the application, wireless sensor networks can be classified by considering the motion of the objects. We believe that each of the following requires different communication architectures and mechanisms. A.
Mobility of sensor node Sinks collecting data and users using information of collected data are static, whereas sensor nodes can move inside sensor fields. Consider, for example, a scenario involving a hazardous materials leak in an urban environment. Metaphorically speaking, we would like to throw a ‘bucket’ of sensor nodes into a building through a window or doorway. The nodes are equipped with chemical sensors that allow them to detect the relevant hazardous material, and deploy themselves throughout the building in such a way that they maximize the area ‘covered’ by these sensors. Data from the nodes are transmitted to a base station located safely outside the building, where they are assembled to form a live map showing the concentration of hazardous compounds within the building. B.
Mobility of sink Sensor nodes deployed inside sensor fields and users using information is static, whereas sinks collecting data can move inside sensor fields. For example, consider the example of habitat monitoring in which a team of life scientists are riding in a vehicle to track an animal. Here the vehicle has to follow the movement of the animal to track it. The vehicle can be equipped with a powerful sink (making it a mobile sink) to collect the data from the sensor nodes along the track of the animal. C. Mobility of user In this case, sensor nodes deployed inside sensor fields and sinks collecting data from sensor nodes is static, whereas users using information of collected data can move. For example, consider operations in the war zone. The headquarters located
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Figure 5. Dissemination of sink announcement message
Figure 6. Mobility support of the user
in the outskirts of the war zone deploy sensor nodes in the war zone and collect locations and movements of enemies from sensor nodes. Through collected data, the headquarters elaborate a plan of operations and delivery the operations to soldiers in the war zone. Then, soldiers carry out the operations and by extension, will collect directly data from sensor nodes to obtain the latest information.
3. Description of Mechanism A.
Overview of Mechanism In our mechanism, if a user intends to obtain information on moving inside sensor networks, the user disseminates interest to the nearest sink via sensor nodes, and then the user receives results of interest from the sink. Also, if the nearest sink of the user changes the user requests the results to new the nearest sink and receives the results from the new sink. This paper makes the following assumptions: • A user can communicate multiple static sinks through only sensor nodes, because networks within sensor fields are without infrastructure networks. • Multiple static sinks are deployed in an arbitrary position in the outskirts of sensor fields connected with infrastructure networks as internet. • Multiple static sinks can directly communicate other sinks via infrastructure networks. • The data which one sink collects is aggregated by the sink. All sinks share the aggregated data via infrastructure networks. To implement the proposed mechanism, we need to address the following phases: dissemination of sink announcement message, interest dissemination of user, data collection of sink, information sharing of multiple static sinks, mobility support of user, and information propagation of sink. We detail each phase to next section. B.
Dissemination of sink announcement message To the initial stage of sensor network, if a sink is located in an arbitrary position in the outskirts of sensor fields which is connected with infrastructure networks as internet it has flooded a sink announcement message to announce itself inside the whole sensor fields like figure 5. As a result of
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Figure 7. Information propagation of the sink
flooding a sink announcement message, every sensor nodes have known hop counts and next hop neighbor sensor node to each sink. And every sensor nodes have known the nearest sink from location of themselves through hop counts to each sink. C.
Interest dissemination of the user While moving inside the sensor fields, if a user wants to collect a data from sensor fields, the user selects the nearest sensor node from location of itself as first agent. And the user delivers an interest to the first agent. The first agent which is delivered the interest from user forwards the interest to a next hop neighbor node toward the nearest sink. The next hop sensor node which is delivered the interest also forwards a next hop neighbor node toward the nearest sink. This process is continued until the sink. So, the sink receives the interest of the user. Also, a back route from the sink to the user for the interest has established through this process. D.
Data collection of the sink Sensor networks with a static sink are a network that sensing data from sensor nodes should be transmitted to the static sink through multi-hop communication. Routing algorithms to collect data in sensor networks with a static sink are used in scenario of various types, for example, a scenario generating data by periods, a scenario generating a minority event, and a scenario detecting a moving object, etc. Hence, a user will can select and use the most appropriate routing algorithm with static sink according to a scenario. Such research was advanced already plentifully [2][3][4]. So we will not mention anymore in this paper. Therefore, we use one in the existing routing algorithm as the routing algorithm to collect data in this paper. E.
Information sharing of multiple static sinks As shown in Fig. 1, a sink in typical sensor networks takes charge of the function as gateways for connection with infrastructure networks [1]. And various papers in relation to multiple static sinks also indicate the connection between a sink and an infrastructure network and the connection between all sinks as an assumption [10 - 13]. Therefore, in this paper, it is a sufficient propriety that all sinks placed in the edge of a sensor field can communicate with the other sinks via
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Figure 9. Residual energy for the number of sink
Figure 8. Network lifetime for the number of sink and sensor node
infrastructure networks. Hence, in proposed mechanism, a sink which is delivered an interest from a user collects data from sensor fields and aggregates the collected data. Next, the sink will share aggregated information with the other sinks through infrastructure networks.
In this section, we evaluate the performance of a proposed mechanism through simulations. We first describe our simulation model and simulation metrics. We next evaluate how environment factors and control parameters affect the performance of a proposed mechanism.
F.
A.
Mobility support of the user The user may move to other place after sending interest to sink by agent. In this case, the user selects another agent and creates a new connection from the original agent to new selected agent. The user can receive the aggregated information from sink through this connection. Thus, mobility of the user is guaranteed. The user can obtain the information of neighbor nodes in radio range of the first agent by reply message received from the first agent. If the user moves out of RF range of the first agent, then the user will retransmit the agent selection message with same RF range of the agent. All sensor nodes which have received this message send a reply message which contains the information of neighbor node in their radio range to the user. As shown in Figure 6, the user checks whether there is sensor nodes which are a neighbor node both in RF range of first agent and in RF range of the sensor node sent the reply messages. Among the sensor nodes which have the connection node in their radio range, the user selects the nearest sensor node from user as second agent. The user settles this selected sensor node as second agent and informs the connection nodes between the first agent and the second agent to the second agent. Second agent creates the connection to the first agent through the connection node informed by user. By this way, the path from the first agent to the user can be created according to movement of user. G.
Information propagation of the sink A sink delivers the aggregated information of the collected data to first agent through the connected path. The first agent delivers the aggregated information to last agent through the connection of agents. Last agent deliveries the aggregated information to the user. As shown in figure 7, if the nearest sink from the user changes, the user requests the information to the new nearest sink and receives the information from the new nearest sink.
4. Performance Evaluation
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Simulation Model and Metrics We implement the proposed mechanism in the Qualnet ver.3.8 [14]. A sensor node’s transmitting and receiving power consumption rate are 0.66W and 0.39W respectively. The transceiver in the simulation has a 200m radio range. Each interest packet is 36 bytes long and the data packet has 64 bytes. The sensor network consists of 50 sensor nodes, which are uniformly deployed in a 1000m x 1000m field. The multiple static sinks are located in the outskirts of sensor fields. The number of user is one. And the default speed of user is set to 10 m/sec. the user disseminates an interest at an interval of 10 second. Every sensor nodes receive the interest and generate only one sensing data for the interest. This is defined as one interest round. Namely, one interest round is 10 second. The simulation lasts for 500 seconds. We use for metrics to evaluate the performance of the proposed mechanism. The network lifetime is defined as the number of the interest round first sensor node die. The residual energy is defined as the residual energy of sensor nodes at time, namely, the interest round that first sensor node die. The data delivery ratio is the ratio of the number of successfully received reports at a user to the total number of reports generated by every sensor node. The delay is defined as the average time between the time a sensor node transmits a report and the time a user receives the report. We compare a static sink model without a mobile user to a multiple static sinks model with a mobile user in the simulation. We express a direct communication model between the user and the sink as ‘sink 1 and not user’ and a user movement model as ‘sink 1 and user 1’ according to the number of sink in figures of performance evaluation. Here ‘1’ is case that sink is one. If the number of sink changes, this numerical value reflects in figures of performance evaluation. B.
Impact of the number of multiple static sinks We first study the impact of the number of sinks on the proposed mechanism’s performance. The number of sinks varies from 1, 2, 3, to 4. And the number of sensor nodes varies from 50, 100, 150, to 200. Sinks have a maximum speed
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Figure 11. Delay for the number of sink and sensor node
Figure 12. Data delivery ratio for user speed
Figure 12. Data delivery ratio for user speed
Figure 13. Delay for user speed
of 10mm/s. In this part, we compare one static sink without the user to multiple static sinks with the user. Figure 8 shows the number of interest round, namely, network lifetime. One static sink model without a mobile user is of small number due to hotspot problem of sensor nodes near the sink. But, the number of interest round of multiple static sinks model with mobile user is higher than the number of interest round of one static sink sensor network even though the sinks are more than 3. Network lifetime, namely, interest round, prolonged because energy consumption of sensor nodes became evenly. Figure 9 shows the residual energy at time that first sensor node dies in simulation circumstances of 50 sensor nodes As shown in Figure 9, the energy consumption of sensor nodes become more evenly because it solves hotspot problem due to addition of sink. Figure 10 shows the data delivery ratio. A model with mobile user is lower than a model without user because it must delivery information from sink to user. But, the hop count between sink and user decreases due to addition of sink because data fails reduce. Therefore the data delivery ratio of a model with mobile user approaches a model without user. Figure 11 shows the delay. The delay of a model with mobile user is longer than the delay of a model without user because it must delivery information from sink to user. Therefore the data delivery ratio of a model with mobile user also approaches a model without user.
varies from 50, 100, 150, to 200. As shown in Figure 8, 10, and 11, the proposed mechanism never falls a performance nevertheless the number of sensor node increase.
C.
Impact of the number of sensor nodes We next evaluate the impact of the number of sensor nodes on the proposed mechanism. The number of sensor nodes
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D.
Impact of the user’ mobility We last evaluate the impact of the user’s moving speed on the proposed mechanism. In the default simulation setting, we vary maximum speed of a user from 6, 8, 10, 12, to 20m/s. In this part, we compare a network model of one static sink without the user to a network model of four static sinks with the user. Figure 12 shows data delivery ratio when the user’ moving speed changes. Because the static sink model without the user is not user, it indicates the same result independent of the user’s moving speed. While the multiple static sinks model with the user decrease according to increment of the user’s moving speed. But the data delivery ratio remains around 0.9 – 1.0 nevertheless the user move faster. Figure 13 shows the delay about data delivery, which increases only slightly as the user moves faster, because it increases the number of agent from the sink to the user. Figure 13 shows that the network lifetime decreases as the user’ moving speed increases. The faster a user moves, the more a user needs the number of agent for connection between the user and the sink.
5. Conclusion In this paper, we propose a novel sensor network model and a novel mechanism to support mobility of users in wireless sensor networks based on multiple static sinks In proposed network model, because multiple static sinks can
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communicate with the other sinks as short hop via infrastructure networks, the user receives the information with higher data delivery ratio and faster time. And the lifetime of the sensor networks increase because the balance energy consumption of sensor nodes is possible. We verified that the lifetime of sensor networks is prolonged because a use of multiple static sinks decreases a consumption of sensor nodes. Also, we verified that a performance about the data delivery ratio and the delay never falls nevertheless a communication between the user and the sink for guaranteeing movement of the user is supported by only sensor nodes without infrastructure networks, namely, internet. REFERENCES [1] I.F. Akyildiz, S. Weilian, et al., "A survey on sensor networks," Communications Magazine, IEEE Journal Vol. 40, pp. 102-114, Aug. 2002. [2] C. Intanagonwiwat, R. Govindan, and D. Estrin, "Directed diffusion: A scalable and robust communication paradigm for sensor networks," ACM/IEEE Mobicom Conference, 2000. [3] W.R. Heinzelman, J. Kulik, and H. Balakrishnan, "Adaptive Protocols for Information Dissemination in Wireless Sensor Networks," ACM/IEEE Mobicom Conference 99, Aug. 1999. [4] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proc. 33rd Hawaii Int’l. Conf. Sys. Sci., Jan. 2000. [5] F. Ye, Haiyun Luo, et al., “A Two-Tier Data Dissemination Model for Large-scale Wireless Sensor Networks,” ACM/IEEE MobiCOM 2002, Sept. 2002. [6] K. Hwang, J. In, et al., "Dynamic sink oriented tree algorithm for efficient target tracking of multiple mobile sink users in wide sensor field," IEEE VTC2004-Fall 2004, Sep. 2004. [7] S. Kim, S. Son, et al., “SAFE: A Data Dissemination Protocol for Periodic Updates in Sensor Networks,” Distributed Computing Systems Workshops 2003, 23rd International Conference. [8] H. L. Xuan and S. Lee, “A Coordination-based Data Dissemination Protocol for Wireless Sensor Networks,” IEEE ISSNIP 2004, Dec. 2004. [9] S. R. Gandham, M. Dawande, et al., "Energy Efficient Schemes for Wireless Sensor Networks with Multiple Mobile Base Stations," IEEE GLOBECOM 2003, Dec. 2003. [10] Henri Dubois-Ferriere, Deborah Estrin, and Thanos Stathopoulos, “Efficient and Practical Query Scoping in Sensor Networks,” IEEE International Conference on Mobile Ad-hoc and Sensor Systems 2004, Oct. 2004. [11] Abhimanyu Das and Debojyoti Dutta, “Data Acquisition in Multiple-sink Sensor Networks,” ACM SIGMOBILE Mobile Computing and Communications Review 2005 [12] E. Ilker Oyman and Cem Erso, “Multiple Sink Network Design Problem in Large Scale Wireless Sensor Networks,” Communications, 2004 IEEE International Conference on, Jun. 2004. [13] Seung Jun Baek, Gustavo de veciana, and Xun su, “Minimizing Energy Consumption in Large-Scale Sensor Networks Through Distributed Data Compression and Hierarchical Agrregation,” Selected Areas in Communications, IEEE Journal 2004, Aug. 2004. [14] Scalable Network Technologies, Qualnet, [online] available: http://www.scalable-networks.com. [15] Hui Dai and Rechard Han, “A node-centric load balancing algorithm for wireless sensor networks,” Global Telecommunications Conference, 2003. GLOBECOM '03. IEEE, Dec. 2003.
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