Hierarchical sensor network architecture for stationary ...

Hierarchical sensor network architecture for stationary smart node supervision Ming-Hui Jin*a, Wen-Jong Wub, Chun-Kuang Chenc, Yih-Fan Chenc, Chih-Min Wenc, Cheng-Yen Kaoa, Shih-An Yud, Yun-Han Line, Jhen-Gang Huangf, Herman Raog, Ching-Hsian Hsug, Chih-Kung Leec a Dept. of Computer Science and Information Engineering, National Taiwan University, Taiwan; b Dept. of Eng. Science and Ocean Eng., National Taiwan University, Taipei, Taiwan; c Inst. of Applied Mechanics, National Taiwan University, Taipei, Taiwan; d Dept. of Electrical Engineering, National Taiwan University, Taipei, Taiwan; e Dept. of Chemistry, Tamkang University, Tamsui, Taipei, Taiwan; f Inst. of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; g Dept. of Service Networks & Enabling Technologies, FarEastone Telecommunications Co., Ltd. ABSTRACT Most wireless sensor networks base their design on an ad hoc (multi-hop) network technology that focus on organizing and maintaining a network formed by a group of moving objects with a communication device in an area with no fixed base stations or access points. Although ad hoc network technologies are capable of constructing a sensor network, the design and implementation of sensor networks for monitoring stationary nodes such as construction sites and nature-disaster-prone areas can be furthered simplified to reduce power consumption and overhead. Based on the nature of immobile nodes, a hierarchical sensor network architecture and its associated communication protocols are proposed in this paper. In this proposed architecture, most elements in the sensor network are designed to be equipped with no functions for message forwarding or channel scheduling. The local control center uses a centralized communication protocol to communicate with each sensor node. The local control center can also use ad hoc network technology to relay the data between each of the sensors. This approach not only minimizes the complexity of the sensor nodes implemented but also significantly reduces the cost, size and power consumption of each sensor node. In addition, the benefit of using ad-hoc network technology is that the local controller retains its routing capabilities. Therefore, power efficiency and communication reliability can be both achieved and maximized by this type of hierarchical sensor network. Keyword: Sensor Network, Stationary Smart Node, Hierarchical Architecture, Active Interval

1. INTRODUCTION Sensors have been widely used in various applications (e.g., health, military, home). Traditionally, people apply sensors to detect the status of certain objects. Whenever the detection results diverge from normality significantly, alerts occur and corresponding procedures may be carried out. This workflow in current stage no longer satisfies many applications because they further request the function of early warning. To reach the goal of early warning, long-term and periodical monitoring becomes necessary. Since data collection is a costly task, most long-term periodical monitoring applications desire an automatic detection results collecting mechanism. This motivates the sensor network technologies. Most wireless sensor networks such as the WINS1, the PicoRadio2 and the AMPS3 base their design on an ad hoc (multi-hop) network technology4, 5, 6 that focus on organizing and maintaining a network formed by a group of moving objects with a communication device in an area with no fixed base stations or access points. Although ad hoc network technologies are capable of constructing a sensor network, the design and implementation of sensor networks for *

[email protected]; phone +886-2-2362 5336 ext 401

Smart Structures and Materials 2004: Smart Electronics, MEMS, BioMEMS, and Nanotechnology, edited by Vijay K. Varadan, Proceedings of SPIE Vol. 5389 (SPIE, Bellingham, WA, 2004) · 0277-786X/04/$15 · doi: 10.1117/12.539677

53

monitoring stationary nodes such as construction sites, historic buildings and bridge areas can be furthered simplified to reduce power consumption and overhead. Based on the nature of immobile nodes, we proposed a novel hierarchical sensor network architecture call the hierarchical sensor network (HSN) in this paper. The goal of the HSN architecture is to minimize the cost, size and power consumption for all the sensor nodes. To achieve this goal, each sensor node keeps only the necessary wireless communication functions. That is, all the sensor nodes apply the same channel to report its detection results through broadcasting. Each sensor node does not forward any message from other. To correctly forward the detection results for the sensor nodes to the global control center (GCC), a special purpose device called the local control center (LCC) is introduced in the HSN. In the HSN architecture, each sensor node connects to one and only one LCC and then the whole network is partitioned into several clusters. Inside each cluster, the LCC uses a centralized communication protocol to communicate with its sensor nodes and then forwards the detection results reported from its sensor nodes to the GCC. This approach condenses the whole sensor network into a much smaller superior network and hence significantly reduces the communication complexity for both the sensor nodes and the LCCs. Therefore, this approach not only minimizes the complexity of the sensor nodes implementation but also significantly reduces the cost, size and power consumption of each sensor node. Although the proposed centralized communication protocol efficiently solves the multiple access problems8 inside each cluster, however, this simple approach also introduces several problems. First, this architecture should provide protocols to solve the self-organization problems inside each cluster. Although this study focus on the sensor networks with immobile sensors, however, new sensor nodes or new LCC may join or disjoin this network. To automatically maintain the network, self-organization functions are desired. Second, the collisions between the connections of two adjacent clusters still occur. To avoid the interferences between adjacent clusters, adjacent LCCs should communicate with their sensor nodes in different time intervals. That is, two adjacent clusters should not be active simultaneously. This implies that the GCC should provide a scheduling mechanism which can specify each LCC a safe time interval to communicate with its sensor node. This paper is organized as follows. Section 2 presents the HSN architecture, the self-organization protocols for cluster maintenance and the power saving mechanism. In Section 3, we propose an algorithm to schedule the active time of each cluster. Based on the proposed architecture, a sensor network system prototype for stationary smart node supervision is implemented and evaluated in Section 4. The conclusions and future works are drawn in Section 5.

2.

NETWORK ARCHITECTURE FOR SENSOR NETWORKS

2.1 The System Architecture Fig. 1 shows the proposed network architecture. In this architecture, the network is partitioned into several clusters. Each cluster contains several sensor nodes and a local control center (LCC). A sensor node has capability to detect and then reports the detection results to its LCC. The detection results are then routed back to the sink through the superior network constructed by only the LCCs. The superior network may be a wired or a multihop infrastructureless network. The sink may communicate with the global control center via Internet or satellite.

54

Proc. of SPIE Vol. 5389

Fig. 1 The network architecture for sensor networks with immobile sensors

In this architecture, all the sensor nodes maintain no network information. Whenever a sensor node learns its LCC, all its activities are decided by its LCC. Each sensor node does nothing unless it receives a command from its LCC. This architecture minimizes the design and implementation complexity of the communication module of each sensor node and hence significantly reduces the cost of the sensor nodes. Because in most sensor network, the number of sensor nodes is much more than the number of LCC. Therefore, comparing with other architectures, we expect that the proposed architecture can significantly reduce the cost for most sensor networks. The disadvantage of this architecture is mobility management. Although the proposed protocols of this architecture allow each LCC and sensor node to be mobile, however, this significantly increases the number of sensor affiliation and departure events inside each cluster. Because the sensor nodes are not designed to be mobile, therefore, comparing with other proposed solutions, each sensor node in our proposed architecture spends much time in perceiving that it moves to other cluster. Besides, the registration activity is a costly task. Although the sensor nodes possess poor mobility functions, however, the proposed protocols provide group mobility functions. As long as the sensor nodes keep connection to their LCC, they can move with their LCC without any injury. Therefore, this architecture is well appropriate for sensor networks with immobile sensors or group moving sensors 2.2 The Power Saving Mechanism Power resource is precious for sensor nodes in many applications4, 5, 6. To further reduce the power consumption for each sensor node, the concept of cluster node is introduced. That is, we treat a cluster as a node in the superior network. Fig. 2 shows the life cycle of a cluster node.

Fig. 2. The life cycle of a cluster node.


55

Whenever a LCC is turned on, it is in the initiation stage and starts to join a sensor network. The first task is learning the LCCs nearby. It keeps listen until it perceives any LCC. Whenever the newly joint LCC gets connect to an existing LCC, it registers the GCC through the existing one. Whenever a LCC joins this network and finish the initialization procedure, the corresponding cluster node is in the operation stage. In this stage, the cluster node may be in active mode or idle mode. A LCC is allowed to communicate with its sensor nodes if and only if the corresponding cluster node is in the active mode. This implies that each sensor node can turn off the RF transmitter and receiver, and idle its CPU whenever its cluster node is in idle mode. This also implies that each sensor node can significantly reduce its power consumption idle mode. Although this mechanism significantly reduces the power consumption of all the sensor nodes, however, this also brings several new problems. First, whenever a sensor node turns off the RF transmitter and receiver, its LCC cannot communicate with it. In this situation, the sensor node has to set up an alarm clock before its CPU become idle. Therefore, a protocol is necessary for setting the alarm clock of each sensor node. Second, if two adjacent cluster nodes are in active mode, the communications inside a cluster node may interferes with the communications inside the other cluster node. This implies that adjacent cluster node should not be active simultaneously. In Section 2.3, the proposed protocols solve the first problem. The second problem is a scheduling problem and we will solve it in Section 3. Besides, several network topology maintenance problems are also crucial for supporting this power saving mechanism. 2.3 The Protocols inside Each Cluster In this paper, we assume that each cluster node actives periodically and all the cluster nodes apply the same period. This assumption is held in most long-term periodical monitoring applications. According to this assumption, the concept of detection cycle is introduced and the length of detection cycle is denoted as ldc. Fig. 3 shows an example of detection cycle of a sensor network. In Fig. 3, a cluster node becomes active at time ts and become idle at time te in each detection cycle. Therefore, each sensor node of the cluster can set its alarm clock at time te and then wake up at time ts in the next detection cycle. For convenient, the time interval (ts, te) is said to be the active interval of the cluster node.

Fig. 3. The detection cycle of a sensor network

Fig. 4. The compositions of an active interval

In the proposed protocols, each active interval is partitioned into three periods as Fig. 4. The registration period is used for the sensor nodes which belongs to no clusters and desires to join this network. The length of the time interval for registration period is a constant. The detail procedures regarding the registration period are presented in7 and are ignored in this paper. In the ending period the LCC will broadcast the next active interval of this cluster to all its sensor

56


nodes. The ending period is crucial since this allows the GCC to adjust the active interval of certain clusters. The proposed protocols also require the length of the time interval for the ending period is a constant. In the polling period, the LCC first broadcast a command to all its sensor nodes. If the command requests all the sensor nodes to sense, then the LCC will then wait for a period of time and then sequentially request each sensor node to report its detection results. The time interval of each request-report activity is the same and we denoted it as tr in this paper. And the waiting time depends on the functions of sensors. 2.4. The Self-Organization Protocols To support the power-saving mechanism, the HSN architecture assumes that each sensor node has one and only one LCC which forwards its detection results to the GCC and each LCC knows the set of all its sensor nodes. To maintain the connection relationships inside each cluster, the HSN architecture proposed a self-organization protocol to handle the four events below. 1. A sensor node joins this network. 2. A sensor node disjoins this network. 3. A LCC joins this network. 4. A LCC disjoins this network. The first protocol requires each sensor node to register the membership to a cluster if and only if it connects to no LCC. Whenever a sensor node turns on, it connects to no LCC. In this situation, it tries to receive the packets from the LCCs nearby. Because there may be no LCC nearby, therefore, a protocol is proposed in Fig. 5 to reduce the power consumption for this scenario. In Fig. 5, the protocol first requires that the length of each active interval should be greater than or equal to a well-known constant AIMin. Whenever a sensor node turns on, it keeps receiving the messages from the LCCs nearby for 't milliseconds. If it receives no messages from any LCC in the time interval, it becomes idle, sleeps for ku't milliseconds and then wake up to listen again. Each sensor node with no master repeats this procedure until it receives some messages from a LCC or it spends all its power resources. In this protocol, k and 't are two important parameters. The optimal values of the two parameters vary from application to application.

Fig. 5. Power saving protocol for sensor nodes with no master.

Whenever a sensor node with no master receives some messages from any LCC nearby, it keeps listen until it learns the start time of the next active interval of LCC. Once it learns the next active interval, it sets up its alarm and then wakes up at the next active interval of the LCC. If the first packet broadcasted from a LCC in the registration period is the registration announcement, then the sensor node applies the pure aloha protocol to register the membership to the LCC. In the end of the registration period, the LCC reports the ID of the sensor nodes which registered successfully. Whenever a sensor node successfully registers to a cluster, its LCC is determined. This solves the sensor node joins event problems. The second protocol requires each sensor node to remove its LCC if it receives no messages from its LCC n times successively, where n is a parameter determining by the network designer. And this protocol also requires each LCC to remove a sensor node from its members if the sensor node has no response n times successively. This protocol solve the sensor node disjoins events and the LCC disjoins events. Whenever a sensor node removes its LCC, it applies the first protocol to join another cluster.


57

Whenever a LCC joins the network, it keeps listen and hence it knows the RSSI of each sensor nodes nearby. Whenever it registered to the GCC, the GCC requires some clusters adjacent to the LCC to shift some sensor nodes to the newly joint LCC. This protocol not only solves the LCC joins events but also successfully reduces the processing and traffic load for the LCCs with low power resources.

3.

THE ACTIVE INTERVAL SCHEDULING PROBLEM

3.1 Assumptions, Definitions and Notations In this paper, we make the following definitions. Def. 1. CL = {C1, C2, …, Cn} be the set of all clusters, where n is the number of cluster nodes in the superior network. Def. 2. For each 1 d i d n, cluster Ci contains si sensors. Def. 3. The active interval of Ci is denoted as (ts(i), te(i)). Def. 4. Two clusters Ci and Cj are adjacent if any sensor node in Ci can receive any broadcasted messages from the LCC of Cj to the sensor nodes of Cj. Def. 5. For two different clusters Ci and Cj, Rij = 1 if Ci and Cj are adjacent and Rij = 0 otherwise.

Fig. 6. The adjacency relationships of clusters

The relation defined in the 4th definition above is a symmetric relation. Fig. 6 shows three clusters Ci, Cj and Ck. In Fig. 6, the solid double arrayheaded line between a sensor node and a LCC implies that the sensor node and the LCC belong to the same cluster. And the dotted double arrayheaded line between a sensor node and a LCC implies that the LCC and the sensor node belong to different cluster but this sensor node can receive some broadcasted messages from this LCC to the sensor nodes of this LCC. Therefore, according to the 4th definition above, Ci is adjacent to Cj, Cj is adjacent to Ck and Ci is not adjacent to Ck. Although the broadcasting activities inside the cluster Cj interfere no communications inside the cluster Ck, however, the broadcasting activity inside the cluster Ck may interfere the communications inside the cluster Cj. A1. A2. A3. A4.

We also make the following assumptions The clocks of all the LCCs are well synchronized. For each two different clusters Ci and Cj, the GCC knows whether Ci and Cj are adjacent. For each cluster Ci, the GCC knows the set of all sensor nodes of Ci. The sensor network is homogeneous. That is, all the sensors of the sensor network have the same functions.

The first assumption does not require the time of the clocks of all the LCCs are exactly the same. It implies that the errors of time of the clocks are all smaller than a given threshold. The second and the third assumptions can be easily achieved. The 4th assumption implies that the variable tr denoted in Section 2.3 is a constant and the waiting time of the polling period is also a constant. The assumption A4 also implies that te(i) = ts(i) + siutr + tc is true for all i, where tc is a constant.

58


3.2 Problem Formulation Activate all the cluster nodes sequentially may be the simplest approach for solving the second problem proposed in Section 2.2. Although this approach works, however, when the superior network contains numerous cluster nodes, the minimal value of the ldc may be too large to make the report sensitivity unacceptable. Because non-adjacent cluster nodes are allowed to be active simultaneously in the proposed architecture, therefore, the minimal value of the ldc can be further reduced through appropriate scheduling the active intervals of all the cluster nodes. If the minimal value of the ldc is small enough, then the GCC can easily specify appropriate value of ldc to meet the report sensitivity given by the users. Based on this reason, we define the cost of each active interval schedule as the minimal value of ldc it provides. According to this definition, a low-cost active interval schedule can provide higher report sensitivity. Since the minimal value of the ldc is min{ te(i) | Ci CL}, and the power saving mechanism presented in Section 2.2 requires adjacent cluster nodes can not be active simultaneously. Therefore, we state the active interval scheduling problem as below. Minimize ldc Subject to

(1)

1 d i z j d n, (ts(i), te(i)) (ts(j), te(j)) = I if Rij = 1

(2)

Where ldc = min { ts(i) + siutr + tc | Ci CL}

(3)

3.3. The Algorithm Design Principle and Proposed Greedy Algorithm

Fig. 7. The algorithm design principle

Fig. 7 shows the methodology of algorithm design for solving the active interval scheduling problem. In Fig. 7, the set of all clusters are classified into m sets V1, …, Vm. The set Vi is called the ith selection of the solution. The classification only requires that, for each 1 d i d m and for each {X, Y} Vi, X and Y are not adjacent. Because no cluster interfere any other clusters in the same selection, therefore, the clusters in the same selection can be active simultaneously. In Fig. 7, the active interval of all the clusters in the ith selection is (ti-1, ti), where ti – ti-1 = max{ te(k) – ts(k) | Ck is a cluster in the ith selection}, and the minimal value of ldc = tm. Based on the design principle above, a greedy algorithm is proposed below. Algorithm 1 Step 1. Let V = CL and i = 1. Step 2. If V = I, terminates this algorithm. Step 3. Let Vi = I


59

Step 4. Let Vi’ = {C V | C’Vi, C and C’ are not adjacent} Step 5. If Vi’ = I, let i = i+1 and then go to step 2 Step 6. Randomly select C V. Let Vi = Vi {C}, V = VΩ{C} and then go to step 4

4. 4.1

THE STATIONARY SMART NODE SUPERVISION SYSTEM

The System Prototype

Fig. 8. The sensor network prototype

We have designed and implemented a sensor network prototype for smart node supervision as Fig. 8. In Fig. 8, the prototype applies the GSM/GPRS services as the superior network and employs notebooks to be the LCCs. In current stage, we also implemented a sensor node prototype for this sensor network as Fig. 9. The LCC in current stage is a notebook with a GPRS module and a RF module. The RF module in the LCC is the same as the sensor nodes and is used to communicate with the sensor nodes, and the GPRS module is used to communicate with the GCC directly.

Fig. 9. The sensor node prototype

60


In Fig. 9, the sensor node prototype employs a strain gauge as the sensor and a 433MHz ISM band RF transceiver as the communication device. Other sensors such as the piezometer can also be easily employed by this prototype. Similarly, this prototype can easily employ other RF module and power supply. 4.2.

System Evaluations The sensor network prototype has been tested in a construction site as Fig. 9. In Fig. 9, three sensor nodes are placed in different positions which is denoted by red rectangles. In the experiments, a hydraulic jack is applied to press the steel girder near the strain gauge of each sensor node. The pressures are controlled so that the global control system as Fig. 10 can compare the difference between the given pressures and the detection results reported by each sensor. Table 1 shows the correctness of the detection results received by the LCC in the five positions. The results show that the LCC can correctly receives most detection results reported by the sensor nodes.

2

4

5 3

1

Fig. 9. The test construction site

Fig. 10. The interface in the GCC


61

Table 1. The experimental results show the rates of success RF communication .are over 85%. (The LCC is located 50 meters away.) Locations 1

2

3

4

5

Sensor no. #4 #8 #20 #4 #8 #20 #4 #8 #20 #4 #8 #20 #4 #8 #20

Tx

Rx

Lost

1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000

886 873 876 877 880 908 955 957 967 886 814 939 953 854 920

114 127 124 123 120 92 45 43 33 114 186 61 47 146 80

Success Average success rate rate 88.6% 87.8% 87.3% 87.6% 87.7% 88.8% 88.0% 90.8% 95.5% 96.0% 95.7% 96.7% 88.6% 87.9% 81.4% 93.9% 95.3% 90.9% 85.4% 92.0%

5. CONCLUSIONS AND FUTURE WORKS In this paper, we first introduce the proposed hierarchical sensor network (HSN) architecture for stationary smart node supervision. To support the HSN architecture, a set of self-organization protocols are proposed to automatically maintain the network topology inside each cluster. To further reduce the power consumption while avoiding the inter-cluster interferences, a new scheduling problem called the active interval scheduling problem and its cost model are proposed in this study. In order to find a feasible schedule, a greedy algorithm is designed and proposed. Besides, a sensor network prototype and its sensor node prototype are also implemented. The experimental result shows that the proposed system does work. In the proposed system prototype, each LCC connects to the GCC directly through the GSM/GPRS services. This is not a good solution especially for sensor networks which contain numerous clusters. To further reduce the cost of GSM/GPRS services, a multihop infrastructless network architecture for the superior networks is under implementation in the next network prototype. Besides, the LCC prototypes are also under design and implementation.

REFERENCES 1. 2. 3. 4. 5. 6. 7. 8.

62

G. J. Pottie, and W. J. Kaiser, “Wireless Integrated Network Sensors,” Commun. ACM, vol. 43, pp. 51–58, May 2000. J. M. Rabaey, et al., “PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking,” IEEE Computer, vol. 33, pp. 42–48, July 2000. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proc. 33rd Annu. Hawaii Int. Conf. on System Sciences, pp. 3005–3014, 2000. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Commun. Mag., pp. 102 – 114, Aug. 2002. T. J. Kwon, M. Gerla, V. K. Varma, M. Barton, and T. R. Hsing, “Efficient Flooding with Passive Clustering – An Overhead-Free Selective Forward Mechanism for Ad Hoc/Sensor Networks,” IEEE Proceeding, vol. 91, pp. 1210–1220, Aug. 2003. T. Y. Lin, and Y. C. Tseng, “An Adaptive Sniff Scheduling Scheme for Power Saving in BlueTooth,” IEEE Wireless Commun. Mag., pp. 92–103, Dec. 2002. Reference removed for double blind reviewing. Andrew S. Tanenbaum, Computer Networks, Third edition, Prentice-Hall International, INC.


9.

G. R. Harik, F. G.. Lobo, and D. E. Goldberg, “The Compact Genetic Algorithm”, IlliGAL Report, No. 97006, Aug. 1997. 10. M. Stinivas, and L. M. Patnaik, “Genetic algorithms: A survey”, Computer Journal, 27(2), pp. 17-26, 1994.


63