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Network Management Framework for Wireless Sensor Networks Jaewoo Kim, HahnEarl Jeon, and Jaiyong Lee Department of Electrical and Electronics Engineering, Yonsei University, 134 Shinchon-dong Seodaemun-gu, Seoul, 120-749, Korea {kimjw064,hearlj,jyl}@yonsei.ac.kr

Abstract. Network Management is the process of managing, monitoring, and controlling the network. Conventional network management was based on wired network which is heavy and unsuitable for resource constrained WSNs. WSNs can have large scale network and it is impossible to manage each node individually. Also, polling mechanism of Simple Network Management Protocol (SNMP) impose heavy management traffic overhead. Since management messages consume resources of WSNs, it can affect the performance of the network. Therefore, it is necessary for WSNs to perform energy efficient network management. In this paper, we will propose network management framework. We will introduce cluster-based network management architecture, and classify the Management Information Base (MIB) according to their characteristics. Then, we will define management messages and message exchange operation for each kind of MIB. The analysis result of the management overhead indicates that the proposed framework can reduce management traffic compared to polling mechanism. Keywords: Network Management, WSN, Hierarchical architecture, MIB, Management Framework.

1 Introduction Wireless Sensor Networks (WSNs) are networks of sensor nodes which have capability of sensing, processing and communication. The sensor nodes in these networks are powered by a battery with limited power, which is dissipated during sensing, processing, and data transmission/reception. Therefore, energy efficiency is the most important aspect of WSNs to prolong network lifetime. Network management includes the process of managing, monitoring, and controlling the network. WSN protocols and their applications have been developed without considering a management solution. Since WSNs can be deployed in or at harsh environment and resources are scarce, unexpected problems such as fault node or energy depletion can cause malfunction of network. This is the biggest obstacle of practical use of WSNs. Therefore, through network management, it is necessary to monitor the state and operation of WSNs. Also, in the face of unexpected events, WSN applications and network parameters will need to reconfigure and adapt themselves based on the information of the network [3]. T.-h. Kim et al. (Eds.): FGCN 2010, Part I, CCIS 119, pp. 76–84, 2010. © Springer-Verlag Berlin Heidelberg 2010

Network Management Framework for Wireless Sensor Networks

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Because of the dead nodes, the performance of WSN decreases as time goes on. For theses WSNs, the collected WSN Management Information could be used not only for monitoring the network but also for network maintenance. For example, deploying relay node to maintain connectivity [10], or deciding node replacement policy which deploys additional node to maintain the network performance [11][12]. Above researches are based on the network information such as network connectivity, coverage, location, and residual energy. Such information are delivered not by sensor application, they can be obtained from WSN management protocols. Traditional Network Management methods are designed to manage wired networks which have quite different characteristics that cannot be used in WSNs. There are some researches on the network management of ad-hoc network [4][5] or WSNs[3][6][7]. They are all based on SNMP which uses polling mechanism. Polling management messages in WSNs causes huge amount of management traffic because WSNs consist of hundreds or thousands of node and data are delivered through the network in a multi-hop fashion. Management messages consume resources of WSNs and it can affect the performance of the network. Polling is not appropriate to sensor nodes which have to minimize energy consumption. Along with the problem of polling mechanism, rather than managing each individual node, cluster based regional management can distribute the load of sink. In this paper, we propose management framework for WSNs. We will define the network architecture. Based on this architecture, we will define the MIB according to the roles of nodes and characteristics of information. Then, we will propose the management exchange method for each kind of MIB to reducing the polling operation. Analysis shows that it reduces the management overhead of the network. The rest of this paper is organized as follows. In section 2, proposed management scheme is presented and its operation is described. In section 3, management traffic analysis of proposed framework and conventional scheme is presented. Finally, Section 4 concludes this paper.

2 Proposed Scheme 2.1 Network Architecture In large scale WSNs, it is difficult to manage each sensor node individually. Therefore, cluster-based hierarchical architecture is adequate for WSNs. Fig. 1 represents the architecture of a cluster-based WSN. The flat network can be considered as a network which has one cluster. For compatibility with existing network management protocol, sink node acts as a gateway between WSN and Internet. Sink node is both the WSN manager and the SNMP agent. The sink node communicates with external network using SNMP. Sink node sends management policies to all cluster head (CH) nodes. CHs have responsibility of managing its own region which consists of its member sensor nodes. CH manages its region with aggregated information of the member sensor nodes. CH nodes manage its region based on the policies received from the sink node. CH also sends the aggregated information to sink or manager to reduce overall traffic.

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Sensor nodes send and receive not only sensing data but also management data.

Fig. 1. Network Management Architecture for WSNs

2.2 MIB We defined and classified WSN MIB according to the characteristics of information. This is because efficient message delivery method is different according to the characteristics of information. We classified Management information into two types: static information and dynamic information. Static information does not change after network initialization. Dynamic information changes during the network operation. In dynamic information, there are continuously changing information, event-driven information and configurable information. Unlike the normal information, we define critical information to report urgent node state such as lack of battery or connectivity. If the battery level or connectivity is lower than the predetermined threshold, the critical information is created. This information takes high priority and requires reliable transmission. The examples of reliable transmissions are transmission of the same packet several times or multi-path routing. Table 1 Shows the MIB of sensor nodes in WSNs. We applied the MIB for sensor node, CH node, and sink node. CH maintains not only its own information as a sensor node but also the cluster information containing the aggregated information and statistical information of the cluster derived from more than one kind of sensor node MIB. The examples of these kinds of information are such as coverage area, data reliability, and the energy level of the cluster and so on. Table 2 shows the aggregated/statistical information of CH MIB. Sink manages the entire network from the information based on aggregated or statistical information. Sink node MIB is similar to CH. It contains the network information derived from CH MIB. For example, low performance area, low energy level area or low coverage area of some region (cluster). It can be used for future node deployment strategies and in some cases shut down some region to block the errors. It can help monitoring and maintaining the network. Also, sink node can reduce the management load by managing the network regionally, not managing each nodes individually. This regional management reduces the management load of the sink node by distributing the load to CHs.


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Table 1. Classification of sensor node MIB MIB types Static

Dynamic

Continuous Event-driven Configurable Critical

MIB Node type (common node, sink node, cluster head), Cluster Head ID, Transceiver information, Communication coverage, Sensing coverage, Memory, Location Residual energy, Transmission error rate, The number of transmitted or received packets Topology, Neighbor node Sensing period, Duty cycle, Node state(active/sleep) Battery threshold, Connectivity threshold

Table 2. Aggregated/Statistical MIB of CHs MIB types Cluster (Aggregated/Statistical information)

Continuous

Event-driven Configurable Critical

MIB Residual Lifetime of the cluster, coverage of the cluster, Transmission error rate, The number of transmitted or received packets Topology, The number of nodes Sensing period, Duty cycle, Node state(active/sleep) Battery, Connectivity

2.3 Management Message Exchange 2.3.1 Message Types We propose the usage of management messages. We define 5 message types. GET, SET, RESPONSE, TRAP, INFORM which is similar to SNMP. But the usage is different from SNMP. In WSNs, since the network status such as battery depletions or faults changes dynamically, it is necessary to get the information periodically. In SNMP, manager has to send GET-REQUEST message to get some information from agents. But in WSNs, resources are scarce and such polling mechanism makes huge traffic because of the large number of nodes and multi hop communication. Therefore, it is inefficient to use polling. GET, SET, RESPONSE, INFORM messages have similar purpose to SNMP. GET/SET is used when the manager requests/set some MIB. RESPONSE is used in response of GET and SET. INFORM is used when two CHs exchange information. However, we propose periodical/eventual TRAP message rather than GET and RESPONSE message to get MIB. GET/RESPONSE requires two times of data transmission: sending GET and receiving RESPONSE. By defining the data transmission conditions, nodes can generate TRAP messages to send its dynamic MIB. It requires only one-way data transmission to get MIB. Therefore, in our framework, TRAP message has a dual purpose. One is to send dynamic MIBs according to its condition (e.g. period, event). The other is to inform emergency state of the network with critical information such as low battery or low connectivity. That is, in order to monitor the status of the network, we use periodic or event-driven report of sensor nodes and CHs rather than to use polling to get the status. The use of TRAP is more important and frequent in WSNs. The creation of TRAP message is occurred periodically or from some events.

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J. Kim, H. Jeon, and J. Lee Table 3. Management Message Exchange according to its characteristics

MIB types Static Continuous Event-driven Configurable Critical

Description Send to manager when the network initiate

Message TRAP GET/RESPONSE Manager can change the value TRAP GET / RESPONSE Information changes when the event occurs TRAP GET / RESPONSE Information is continuously changes SET / RESPONSE GET / RESPONSE Send Trap message when the value is lower TRAP than the predetermined threshold SET / RESPONSE GET / RESPONSE

2.3.2 Message Usage Table 3 shows the description of each MIB and the mapping of each MIB to each message. Static information is sent to manager or sink node when initializing the network using TRAP. Afterwards, most of the information needed to manage WSN is dynamic information. For continuously changing information and event-driven information, instead of using periodic GET message, TRAP message is generated from a node periodically or when an event occurs and sent to CH. The CH aggregates these informations and sends TRAP message. Configurable information can be changed by SET and RESPONSE message. For critical information, if the value is lower than the predefined threshold, node generates TRAP message and sends it to manager. For all kinds of MIB, GET message can be used. However, due to its inefficiency, it is used only in special cases such as when the manager wants to know detailed information of a node. Existing GET/SET message operates based on 1-1 communication. However, in WSN, there are some cases when a manager wants to know the states of a group of nodes. By using the broadcast or multicast option, GET, SET message can operate to a cluster. 2.4 Operation Scenario of the Framework In this chapter, we present an example of operation scenario of our framework. Fig. 2 shows the flow. At the network initialization phase, sink node sends management requirement or policies to CHs in the network with management messages: GET or SET. GET is used for necessary information of the application and SET is used for setting report period and condition. Nodes send the response with some selected static and dynamic information. In this way, Manager can get the information about the network for management at initialization phase.. Each requirement or policy for each CH can be different according to its applications and the location of CH. Each CH changes these requirements for sensor nodes and broadcasts to its member sensor nodes. Policy contains some actions or operations for certain conditions. After network initialization, nodes and CHs send its dynamic management information (continuous, event-driven) according to certain period or events using TRAP


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message. Before sending the message, CH aggregates and derives statistical information of its cluster such as reliability, coverage area, node energy levels and lifetime of the cluster. Then, CH sends this information according to predetermined period or conditions. CHs can perform some management tasks based on policies received form sink. Finally, Sink nodes derive the overall information of the network by aggregating the information of clusters and manage through the centralized algorithm such as network performance monitoring and node deployment policy and other management tasks.

Fig. 2. An example flow of management operation

3 Management Traffic Analysis We modeled the network and compared the overhead of proposed scheme with periodic polling method according to the network size and the number of clusters. As illustrated in Fig. 3, we assume that the nodes are deployed in a circular area. The sink node is in the center, and the network is divided into M concentric band. Each node in

Fig. 3. The network model showing that the sink is in the center and each band has width of transmission range r

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the ith band sends the packet to a node in the i-1th band. The density and the transmission range are fixed and other parameters are variables. We assume that the nodes are uniformly and randomly distributed with fixed density ρ. The total number of nodes is n, the transmission range of nodes is r, and the number of clusters in the network is K. We compared the message overhead of the continuously changing information which requires periodic update. For calculating the management overhead, the number of bands of the network is represented as follows.

⎡1 n ⎤ M =⎢ ⎥ ⎢ r ρπ ⎥

(1)

Nodes are scattered around the sink node with fixed density. Therefore, if the number of node n increases, the nodes will be deployed outside of current network and M also increases. We compared the number of management messages generated in a network when the sink node gets the dynamic information of the sensor network. MO(CP) shows the network overhead caused by centralized polling approach which is mainly from SNMP request and reply. If the manager is polling the node one by one, the overhead is M −1

MO( CP ) = 2( ρπr 2 ∑ i( 2i − 1 ) + M ( n −ρπr( M − 1 )2 )

(2)

i =1

The first term is the number of management messages of inside bands of the Mth band and the second term is the number of management messages of Mth band. Since multi hop communication is considered, data generated in ith band have to be delivered through i-hops. The twice of these terms are from request and reply. Management overhead MO(CT) caused by centralized TRAP approach is half of the centralized polling. There is not the request message and only the TRAP message is sent. This case also can be seen that it has only one CH. M −1

MO( CT ) = ρπr 2 ∑ i( 2i − 1 ) + M ( n −ρπr( M − 1 ) 2 )

(3)

i =1

In hierarchical architecture, nodes send the management information to CH and the CH aggregates the information and sends it to central manager. We assume that each cluster is the small version of the whole network that has the node density ρ and the number of nodes in a cluster is approximated as n/K. We also assume the CHs are located M hop away from the central manager which represents the upper bound of hop count. The management overhead of hierarchical architecture MO(HT) is

MO( HT ) = MK + ρπr 2

M ' −1

n

∑ i( 2i − 1 ) + M ' ( K −ρπr( M ' −1 )

2

)

(4)

i =1

M' is the number of bands of the cluster can be calculated from (1) with density ρ and the number of the cluster n/K.


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Fig. 4 shows the number of management messages according to the number of nodes in the network. The parameters for the analysis are represented in Table 4. Management traffic of centralized polling approach increases dramatically according to the network size. In Fig. 4 (a), hierarchical network using TRAP message has the smallest number of management messages because periodic polling is never used. Also, in Fig. 4 (b), as the number of clusters increases, the required number of management messages of the network is reduced. Table 4. Parameters for the management traffic analysis Parameter Value

Density (ρ) 0.1 / m2

Communication rage (r) 30 m

Fig. 4. The number of messages generated according to the number of nodes in the network

4 Conclusion We proposed a network management framework for WSNs. We classified MIB according to their characteristics and we used different management message exchange method for each kind of MIB. The analysis shows that using TRAP message in the hierarchical architecture, with data aggregation, reduce the management overhead of the network compared with existing centralized polling approach in WSNs. As the number of nodes and clusters increases, the management overhead is reduced with the cost of CHs. This can achieve longer network lifetime. In the future work, by using this framework, we will define the management protocol with detailed message formats and its operations. And also, we will study about an algorithm for calculating the aggregated or statistical information of the network from management information such as the network lifetime of WSNs. The estimation of the network lifetime based on MIB can be used for maintenance of the network. Acknowledgments. "This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research

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Center) support program supervised by the NIPA(National IT Industry Promotion Agency)" (NIPA-2010-(C1090-1011-0006)).

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