Functional and Information Models for the MANNA Architecture 1

Transcription

1 Functional and Information Models for the MANNA Architecture 1 Linnyer Beatrys Ruiz*,#, José Marcos Nogueira*, Antonio Alfredo Loureiro* *Universidade Federal de Minas Gerais Department of Computer Science Av. Antonio Carlos, CEP Belo Horizonte- Minas Gerais, Brazil. # Pontifícia Universidade Católica do Paraná Department of Informatics Rua Imaculada Conceição,1155 -CEP Curitiba-Paraná, Brazil ^OLQQ\HUMPDUFRVORXUHLUR`#GFFXIPJEU ABSTRACT. Wireless Sensor Networks (WSNs) are becoming an increasingly important technology that will be used in a variety of applications such as environmental monitoring, infrastructure management, public safety, medical, home and office security, transportation, and military. WSNs will also play a key role in pervasive computing where computing devices and people are connected to the Internet. Until now, WSNs and their applications have been developed without considering a management solution. This is a critical problem since networks comprised of tens of thousands nodes are expected to be used in some of the applications above. This paper presents an information model for wireless sensor network proposed by MANNA management architecture that take into account specific characteristics of this type of network. Some of them are restrict physical resources such as energy and computing power, frequent reconfiguration and adaptation, and faults caused by nodes unavailable. The MANNA architecture considers three management dimensions: management functional areas, management level, and WSN functionalities. These dimensions are proposed to the management of a WSN and are the basis for the information model. KEYWORDS: wireless sensor network management architecture, information model, sensor networks. 1 This work is partially supported by National Research Council (CNPq), Brazil.

2 2 GRES Février 2003, Fortaleza-CE-Brésil. 1. Introduction A Wireless Sensor Network can be used (WSN) to monitor and, eventually, to control a remote environment. The goal of the WSN management is to define a set of functions that intend to promote productivity, as well as to integrate, in an organized way, functions of configuration, operation, administration, and maintenance of all elements and services of a WSN. Until now, WSNs and their applications have been developed without considering a management solution. This may not be a problem for small networks but will definitely be when applications, in order to work properly, will need to reconfigure and adapt themselves based on information scattered over the network. This paper presents an information model proposed by the MANNA management architecture that take into account specific characteristics of this type of network. Management of WSNs is a new research area that only recently started to receive attention from the research community. In this sense, this work presents a contribution to the field, since it proposes a WSN information model to ensure common syntax and semantic of management information. This will make possible the integration of organizational, administrative, and maintenance activities for this kind of network. In the MANNA architecture, the development of the information model led to formulation of the concept that management information may be specified based on three viewpoints: management functional areas, management level and WSN functionalities. The rest of this paper is organized as follows. Section 2 introduces the WSN management. Section 3 presents the MANNA architecture. Section 4 describes the principles for defining an information model for WSN. Section 5 presents the main WSN functionalities organized in a functional model. Section 6 presents the information model. Section 7 discusses the implementation aspects. Finally, in Section 8 the conclusions are drawn. 2. Management of Wireless Sensor Networks Traditional computer networks are designed to accommodate a diversity of applications. Network elements are installed, configured, and connected in a network in a way to provide different kinds of services. In general, management aspects are clearly separated from network common activities, i.e., from the services they provide to their users. Therefore, it is said that there exists an overlapping of management and network functionalities, yet the implementation can be thought independently. In the following we discuss important characteristics of WSNs that make their management different from other networks. In computer networks, the maintenance of components or resources by technicians is a normal fact. The network tends to follow a well-established

3 Functional and Information Models for the MANNA Architecture 3 planning of resources available and it is well-known the location of each network element. In a WSN this is not often the case, since the network is planned to have unattended operation and nodes can be discarded, lost, and be out of operation temporarily or permanently. In this scenario faults are a common fact, what it is not expected in a traditional network. In fact, the initial configuration of a WSN can be quite different from what was supposed to be in case of throwing the nodes in an ocean, forest and other remote regions. In unpredictable situations, a configuration error (e.g., planning error) may cause the loss of the entire network even before it starts to operate. Nodes in a WSN usually execute a common application in a cooperative way, i.e., there is clearly a common goal in the overall network, which it is not common in a traditional network. WSNs are quite different of a Mobile Ad hoc Networks (MANET). A MANET is comprised of mobile nodes that can communicate with each other using wireless links. This is probably the most distinct characteristic of a MANET which is typically not application-dependent, and needs a mechanism similar to the IP address to identify individual nodes. WSNs are typically application-dependent, self-aware, and self-organizing. Thus, depending on the WSN application it may be interesting or not to identify uniquely each node in the network. Furthermore, we may be interesting in a value associated to a given region and not to a particular node. For instance, we may be interested in the temperature at the top of a mountain. A WSN is typically data-centric, what is not common in traditional computer networks. In general, WSNs are designed to cooperate and adapt when performing coordination tasks and functions, and execute unattended operations. Sensor nodes are often static and are deployed in such a way that it is possible to have both sensor and data redundancy. Sensor nodes have strong hardware and software restrictions interms of processing power, memory capacity, battery lifetime, and communication throughput. These are typical characteristics of mobile and wireless devices and not of wired network elements. Thus, software designed for a sensor node must consider those limitations whereas for a wired network element may have other restrictions such as performance and response time. The main physical restriction of a WSN is energy available since batteries are often not recharged during the operation of a sensor node and all activities performed by the node must take into account the energy consumption. 3. MANNA Management Architecture The traditional network management is organized over two planes, i.e., management functional areas and management levels. The MANNA architecture defines a new dimension to the management. It is another abstraction level where the network functionalities are also considered. In this way, WSN management will have an organization that comes from abstractions offered by management

4 4 GRES Février 2003, Fortaleza-CE-Brésil. functional areas, management levels, and WSN functionalities (configuration, maintenance, sensing, processing, and communication). Section 5 presents WSN functionalities as a functional model important to the identification and definition of generic management information that can be used in the management of WSNs. The MANNA architecture considers the three abstraction planes in the definition of a management function and in the development of the functional, physical, and information architectures proposed. In particular, in this paper we present the information model established by the MANNA information architecture. The generic information model will permit management integration in the future. Fig.1 presents the existing relationships in the definition of the management service and information model. The new dimension introduced by the MANNA architecture can be observed in the upper part of Fig. 1. WSN Functionalities Configuration Maintenance Sensing Processing Communication Management function Functional Areas Configuration Management Fault Management Performance Management Security Management Accounting Management Business Management Service Management Network Management Network Element Management Network Element Management Levels Figura 1. Management Functionalities Abstrations The definition of management services is a task that consists in finding which activities or functions must be executed, when and with which data. Management services are executed by a set of functions, and they need to succeed to conclude a given service. The management fuctions use and generate the management information Management functions represent the lowest granularity of functional portions of a management service, as perceived by users. This means that the management architecture must exhibit a function list to deal with the integrated functioning of a WSN, applications and users. Therefore, management functionalities will be

5 Functional and Information Models for the MANNA Architecture 5 independent of network target activities, even when this is not apparent in the implementation. The MANNA architecture establishes that the WSN management does not end in its functions, though. It is necessary to go further. Policy management will be dependent on network states. A network state, or part of it, can be viewed from different perspectives and varies with the moment. The MANNA architecture defines entities, called WSN models, that represent dynamic information of the network and serve as a reference to the management functions. These models provide an abstract vision of the system, through which it is possible to omit all nonrelevant aspects for a certain objective. Thus, the MANNA architecture defines two types of management information: static and dynamic. The static information is represented through managed objects. Section 6 presents the information model proposed. The relationship among services, functions, and WSN models is illustrated in Fig. 2. It represents a scheme to construct the management, starting at the definition of both services and functions which use models to achieve their goals. A service can use one or more management function. Different services can specify common functions that use models to retrieve a network state concerning a given aspect. Service X Service Y uses uses uses uses Function 1 Function 2 Function n uses uses uses uses uses uses WSN Model WSN Model WSN Model WSN Model WSN Model Figura 2: Relationship Among Services, Functions and WSN Models in MANNA Management. The management services, the management functions and the WSN models provided by the MANNA architecture are described in (Ruiz, 2002). Although WSNs are application-dependent, the MANNA architecture provides flexibility, since it was not designed for a particular WSN. The concepts involved with the management functional areas of WSNs differ from established definitions for traditional networks or even other wireless networks. The MANNA architecture considers that the fault, security, performance

6 6 GRES Février 2003, Fortaleza-CE-Brésil. and accounting functional areas are extremely dependent on the configuration functional area. In a WSN, all operational, administrative and maintenance characteristics of the network elements, the network, the services, and business, as well as the adequate execution in the activities of maintenance, sensing, processing and communication are dependent on the configuration of the WSN. An error in the configuration or a forgotten requisite during the planning may compromise all the functionalities of the other areas. In the Logical Layer Architecture (LLA), management functionalities depend on the management level. Many traditional management systems use this model in a bottom-up approach. In the MANNA architecture, the LLA model is used in a topdown approach. Firtly, the business level issues must be analyzed to identify the necessities of the lower levels. Similarly, it is only after the application definition, including the corresponding requirements on the service layer, that we can plan the network and network element management layers, and network element. This is a key observation when reasoning about the WSN management. 4. Principles for Defining an Information Model for WSN A methodology to design an information model must follow some principles. In our case, we propose that the information model for a WSN must be simple, open, adherent to network idiosyncrasies, including its dynamic behavior. We consider the following principles in the definition of the information model: ƒ ƒ ƒ ƒ Build a generic functional model for characterization of the WSN describing the configuration, maintenance, sensing, processing, and communication functionalities. Identify static and dynamic information. Establish the management information from abstractions in different functional areas, management levels, and network functionalities. Orthogonality among the three dimensions should be maintained in the descriptions of information model to avoid redundancy in it. Establish an open and documented information model that allows the reuse of objects, as well as syntax and semantic uniformity of management information. We work with each management functional area, each management level, and the new abstraction level of the WSN functionalities described above. As result, we propose a list of management functions in (Ruiz, 2002), independent of technology and the functional architecture adopted. That management function list is helpful in the development of an information model.

7 Functional and Information Models for the MANNA Architecture 7 5. Functional Model for WSN We believe that to have a better development of the WSN information model, we need to characterize the WSN and establish a functional model. We look at the characteristics of various WSN applications and define five main WSN functionalities: configuration, maintenance, sensing, processing and communication. These functionalities are considered a new dimension for the management as described in Section 3. In the following, we describe these functionalities as a functional model to be used in the information model development. 5.1 Configuration This functionality involves procedures related to planning and self-organizing of a WSN. For example, the definition of WSN application requirements, the determination of the monitored area (shape and dimension), the environment characteristics, the choice of nodes, the definition of WSN type, and service provided. The WSNs are application-dependent. Thus, this functionality changes from a WSN application to another. In the following, we discuss the configuration considering the possible types of WSN and the other management dimensions. Considering the network management level and the management functional areas based on the configuration functionality, the WSNs can be classified as described in the following. A WSN is said to be homogeneous when all nodes have the same hardware. Otherwise, it is said heterogeneous. A WSN is hierarchical when nodes are grouped for the purpose of communication, and flat otherwise. A WSN is static when nodes are stationary, and dynamic otherwise. Note that the topology may be dynamic even when nodes are stationary since new ones can be added to the network or existing nodes become unavailable. A WSN is symmetric when each transceiver has the same transmission range, and asymmetric otherwise. A WSN is said to be regular when its nodes are placed in a grid, irregular when its nodes are randomly distributed presenting different densities on the monitored area, balanced when its nodes are randomly distributed presenting uniform distribution. A WSN also can be sparse or dense depending on the number of nodes per area unit. Considering the network element management level and the management functional areas based on the configuration functionality, the sensor nodes in a WSN are spread over a region and communicate among themselves using point-topoint wireless communication forming an ad hoc network. The nodes are autonomous when they are able to execute self-configuration tasks without human intervention, for example the location discovery. To relay information off of the network, sensor nodes are equipped with wireless communication devices (transceiver). A wireless sensor node is also comprised of one or more sensor element, battery, memory, and processor. The size of a node is an important consideration. Nodes need to have small form factors so that they may be located unobtrusively in the environment targeted for monitoring. The restriction in size is closed related to the amount of energy available to a node. A rugged and robust

8 8 GRES Février 2003, Fortaleza-CE-Brésil. construction is required if nodes are being dispersed in inhospitable terrain such as a forest. Software developed to execute in a wireless sensor node must take into account its hardware restrictions. Because the limited energy capacity, nodes are expected to be thrown away once their energy supply is exhausted. The system can have levels of redundancy built into it to allow failures or to increase the accuracy. This can be achieved by using more sensor nodes than it is strictly necessary to cover an area. Also due to environment nature, logistics, and deploying costs, the deployment of sensors can be a one-time operation; therefore, after nodes have been distributed in the field, human intervention is not an option. Basically there are three different types of sensor nodes: common nodes responsible for collecting sensing data, sink nodes responsible for receiving, storing, and processing data from common nodes, and gateway nodes that connect sink nodes to external entities called observers. WSNs can also include actuators that enable control or actuation on a monitored area. In a hierarchical network, it is common to have a Base Station (BS) that works as a bridge to external entities. Considering the service management level and the management functional areas, the WSN comprises the three entities: observer(s), phenomenon(s), and environment. The observer is a network entity or a final user that wants to have information about data collected by sensor nodes. Depending on the type of application, the observer may send a query to the WSN, and receive a response from it. These queries can be done with or without fidelity. The translation query could be performed by the application software or sensor nodes. The WSN may participate in synthesing the query (e.g., filtering some sensor data or summarizing several measurements into one value), but these procedures are related to the processing functionality. The phenomenon is the entity of interest to the observer that is being sensed and optionally analyzed or filtered by the WSN. The observer is interested in monitoring a phenomenon under some latency and accuracy restrictions. A sensor element generates data about a given phenomenon such as temperature, pressure, electromagnetic field, and chemical agents since it can be comprised of different sensor elements. 5.2 Sensing The lowest level of the sensing application is provided by the autonomous sensor nodes. An important operation in a sensor network is gathering of data. Sensing functionality depends on the type of phenomenon (continuous, mobile, discrete, stationary). An example of a continuous phenomenon is temperature. An example of an application where the phenomenon itself is moving is a sensor deployed for animal detection. Other examples of phenomenon are video, audio, pressure, mechanical stress, humidity, soil composition, luminosity, seismic, and chemical. Despite the fact that gathering is continuous or not, WSNs are defined based on how the data will be transmitted by the determined observer. The sensing encloses the exposure (time, distance and angle of phenomenon exhibition at the sensor), and sensing coverage. Depending on the density of the phenomenon, it will be inefficient if all sensor nodes are active all the time. A model that is well-suited

9 Functional and Information Models for the MANNA Architecture 9 to this case is the Frisbee model (Cerpa et al, 2001). Nevertheless, the sensors can be mobile. In this case, the sensors are moving with respect to each other and the observer as well, they have direction, orientation and aceleration. 5.3 Processing Memory and processor of a sensor node form the computational module. The computational module is a programmable unit that provides computation and storage for other nodes in the system. It performs basic signal processing (e.g., simple translations based on calibrating data or threshold filters), and dispatches the data according to the application. The processing can also involve correlation procedures such as data fusion. The data fusion combines one or more data packets received from different sensors to produce a single packet (data fusion). The data fusion helps to reduce the amount of data transmitted between the sensor nodes and the observer allowing to produce a network that delivers the required data while meeting the energy requirements. Other possible tasks are security processing and data compression. 5.4 Communication Individual nodes communicate and coordinate among themselves. infrastructure communication refers to the communication needed to configure, maintain, and optimize operation. The configuration and topology of the sensor network may be rapidly changing in the presence of a hostile environment, a large volume of assigned work, and nodes that fail routinely. Conventional protocols may be inadequate to manage such situations; new protocols are required to promote the WSN productivity. In static sensor networks, an initial phase of infrastructure communication is needed to set up the network and additional communication is needed to reconfiguration. If the sensors are mobile, additional communication is needed for path discovery/reconfiguration. application communication relates to the transfer of sensed data (or information obtained from it). The amount of energy spent in transmitting a packet has a fixed cost related to the hardware and a variable cost that depends on the distance of transmission. Receiving a data packet also has a fixed energy cost. Therefore, to conserve energy short distance transmissions are preferred. Since the access point (sink node or the BS) may be located far away, the cost to transmit data from a given node to the access point may be high. In a homogeneous and flat WSN, the sensor nodes form a multi-hop network by forwarding each other's messages, what vastly extends connectivity options. In a heterogeneous and hierarchical WSN, the cluster-heads form a single-hop network for reporting aggregated data to the BS. Within a cluster, measured data is sent to the cluster-head by the sensor nodes, which are under its control. All nodes in a cluster are identical except in the heterogeneous WSN where the cluster-head has a larger transmission capacity. WSNs can be classified in terms of the data delivery required by the application interest as continuous when sensor nodes collect data and send them to observer continuously along the time, and on-demand when it answers to an observer's query.

10 10 GRES Février 2003, Fortaleza-CE-Brésil. A WSN is reactive when sensor nodes send data referring to events occurring in the environment and programmed when nodes collect data according to conditions defined by the application. Some approaches can coexist in the same network; we refer to this model as the hybrid model. For any of the above mentioned models, we can classify the communication approach as: flooding (sensors broadcast their information to their neighbors, which in turn broadcast this data until it reaches the observer), unicast (sensor can communicate to the sink node, cluster-head or BS directly), or multicast (sensors form application-directed groups and use multicast to communicate among group members). A major advantage of flooding or broadcast is the lack of a complex network layer protocol for routing, address and location management. 5.5 Maintenance WSN state changes are frequent in a WSN. For example the topology. In the case of static networks, changes occur because nodes may become unavailable during operation. The WSN dynamic behavior must be observed. Thus, maintenance functionality is needed to keep the network operational and functional to ensure robust operation in dynamic environments, as well as optimize overall performance. There are some types of maintenance: corrective, adptative, preventive. The maintenance services depend on the knowledge of the network state. Other example of maintenance is about density of nodes in the WSN. In case of a high density, the maintenance can turn off temporarity some nodes. Therefore, WSNs have important characteristics depending on the application. Some of then are planning, deployment, coverage, accuracy, fidelity, density, selforganization, adaptation and location. The points described in this section will play an important role in the definition of the information model presented in the following. 6. WSN Information Model To ensure common solutions for the WSN management, the MANNA architecture has generated an initial information model. The management entities (manager and agent) can be developed independently of each other, since it is now known which messages they can expect from the other, and which messages they can use themselves to influence the other. From the managing systems point of view, the MANNA functional architecture (Ruiz, 2003) establishes under what circumstances they will receive the event notifications and how they can get its information (monitoring). It is also clear what kind of influence the managing systems have over the WSN resources and how to control them. Management policies are used to define how the management entities should analyze the received information and react to it. In fact, MANNA functional architecture discusses issues

11 Functional and Information Models for the MANNA Architecture 11 such as location of management entities, structuring of management (centralized, distributed, and hierarchical), and services that management entities must execute (Ruiz, 2002). The development of an information management model led to the formulation of the concept that management information may be specified from three viewpoints: management functional areas, management level and WSN functionalities. These viewpoints facilitate specifications at varying abstraction levels and provide a structured method for documenting generic information, starting with business level needs (see Section 3) without being concerned about how it is implemented. The information modeling is too extensive to be covered adequately in this article. Therefore only the major concepts are discussed here. In WSN management, there are two kinds of management information: static and dynamic. The static information describes the configuration of services, network and network elements. It is mapped into object classes. Dynamic management information describes the information the changes frequently. In MANNA architecture, dynamic management information is described by WSN models. In the following, it is described how the MANNA architecture deals with the two types of information. 6.1 Static Information The design of an information model for a WSN is a complex task. The way that MANNA architecture tackles with this complexity is using the abstraction represented in Fig. 1: management functional areas, management levels and WSN functionalities. The MANNA information architecture is based on object oriented information modeling. There are two types of object classes which represent resources under the three different levels of abstraction: managed object and support object classes. The managed object class directly relates with the network components and with the network itself. On the other hand, the support object classes are special ones in the sense that they play the role of supporting the management functions, i.e., making available to them the necessary information. The specification of an object class is done through pre-defined syntactic structures and utilize the ASN.1 language (Abstract Syntax Notation.1), so as to describe the objects and its characteristics. The object classes may be inherited or reused from standard objects. The reuse allows future management integration. Some object classes and their new attributes, based on WSN characteristics, are listed below.

12 12 GRES Février 2003, Fortaleza-CE-Brésil Support Object Classes These object classes can be programmed inside the agent or can be present in the management application. The classes of support objects used in this work are mostly based on OSI patterns. Information Log. It is used to define the criteria for controlling the logging of the information delivery by a WSN to observer. Management Log. It is used to define the criteria for controlling the logging of the management information. Event Forwarding Discriminator. It is used to define the conditions that shall be satisfied by potential event reports before the event report is forwarded to a particular destination. Management Operations Scheduler. It is used to represent the management policies based on type of WSN application and observer goal. Energy Level Severity Assigment Profile. It is a class of management support object that specifies the energy level severity assignment for managed element. Current Remaining Energy Level Summary Control. It is a class of management support object that provide the requirements to generate a report about the remaining energy level. Event Record. It is used to define the information stored in the log as a result of receiving notifications or alarm reports. Besides the events caused by energy problems, other events can happen in a WSN such as, communication events, processing events, sensing events, equipment events, environment events, Quality of Service, integrity violation, operationg violation, and security violation. Monitored Object. It is the object for which performance measurements are being collected. It represents the resource being measured. Current Data Object. It contains the measurements for the resource being monitored for a specified time interval (e.g. from 10:00 a.m. to 04:00p.m.). History Data Object. It contain a copy obtained at the end of the current interval of the performance management and other selected attributes present in the currentdata Object. A new instance of this object class is created at the end of each interval. Threshold Data Object. It contains a set of threshold values which correspond to a set of measurements defined for one or more classes of currentdata. Scanners. Describes how to scan a collection of object in order to get aggregated and transformed information. It may be used to scan the contents of both the currentdata or historydata objects. Scanners may be used to aggregate sets of measurements from a number of currentdata objects representing a number of different Monitored Objects and a number of historydata objects for one or more monitored entities. These scanner objects may simply aggregate the measurements into a scanreport notification for bulk transfer to a managing system or they may be used to perform statistics on the measurement for inclusion in a scanreport which

13 Functional and Information Models for the MANNA Architecture 13 can be sent to the managing system or stored in the log. Scanners used to aggregate measurements include: simplescanner and dynamicsimplescanner. Those used to perform statistics include: meanscanner, meanvariancescanner and minmaxscanner Managed Object Classes The The managed object classes are directly related with features of the WSN sensor and acting nodes. Observing the functionalities of WSN (see Section5), the following object classes based on the standardized generic model were identified. Network. It is composed by interconnected managed objects (physical or logical ones), capable of exchanging information. In these cases, it is the WSN. Examples of new attributes for this class are the network identifier, the composition type (homogeneous, heterogeneous), organization type (flat, hierarchical), organization period, mobility (stationary, stationary nodes and mobile phenomenon, mobile node, and mobile phenomenon), data delivery (continuous, event driven, on demand, programmed, hybrid), type of access point (sink node or base station) localization type (relative and absolute), node distribution (regular, irregular, balanced, sparse, dense), node deployment (it is affected by many factors, some them being the sensor capabilities of individual nodes, radio propagation characteristics and the topology of the region. Other constraints may include introducing a degree of overlap in the sensor coverage of two nodes so that they may collaborate their data processing efforts). Managed Element. It represents the sensor and actuators nodes or other WSN entities, which execute functions on managed elements, providing sensing, processing, and communication services. Examples of new attributes of this class are: localization (relative or absolute), element type (common node, sink node, gateway, cluster head), minimum energy limit, and mobility (direction, orientation and acceleration). The problem is where to place the base station or sink node. Some approaches use a combination of computational geometry, Computer Aided Design, and numerical optimization methods. Equipment. It represents the physical components of a managed element. In this case, this class represents the physical aspects of the sensor node constitution, which is composed by memory, processor, sensor device, battery, and transceiver. The equipment class can be specialized in object classes: 1) battery with the attributes of battery type (linear: the battery is considered to be a bucket of energy. Energy is linearly drawn from this bucket by the energy consumers, discharge rate dependent model: considers the rate at which energy is drawn from the battery to compute the remaining battery life. At high discharge rates, the capacity of the battery is reduced, and relaxation model: takes into account a phenomenon seen in real-life batteries where the battery's voltage recovers if the discharge rate is decreased.), battery capacity, remaining energy level, energy density, max current), 2) computational module composed by processor and memory (clock, state of use, available memory,

14 14 GRES Février 2003, Fortaleza-CE-Brésil. endurance, AD channel, operating voltage, IO pins), 3) sensor element with the attributes sensor type, current consumption, voltage range, minmax range, accuracy, temperature dependence, version, state current, exponsure, and 4) transceiver (type, modulation type, carrier frequency, operating voltage, current consumption, throughput, receiver sensitivity, transmitter power). System. It is used to represent a set of hardware and software, which constitutes an autonomous system capable of executing the information processing and/or transference. Examples of new attributes: operating system type, version, code length, complexity, total MIPS per available MIPS, and synchronization type (mutual exclusion, synchronization of processes). A notification of change in an attribute value must be reported upon the event occurrence, such as software upgrade. Environment. It represents the environment where the WSN is operating. Example of new attributes: environment type (internal, external and unknown), noise ratio, atmospheric pressure, temperature, radiation, electromagnetic field, humidity, and luminosity. The environment can present static and dynamic features. Connection. It represents the actual connections and it is expressed as an association between particular points. The direction of connectivity can be unidirectional (asymmetric) or bi-directional (symmetric). If an instance of this class is unidirectional, the point "a'' will be the origin and the terminal point "z'' will be the destination. The operational state will indicate the capacity to load a signal. Example of attribute for this class is the communication way type (simplex, half duplex, full duplex). The network topology describes the connections which may exist and it is expressed as in relationships between a set of points. WSN Observer. It represent the entity which requires the WSN services. It may be a human user applying for the use of services via some human-machine communication or it may be some computer-based organizational system. WSN Goals. WSN goals are the users' benefits obtained by carrying out WSN activities, using WSN services. They can be defined as accuracy, latency, fidelity, etc. WSN Management Context. WSN context defines the environment where WSN management services are carried out. The definition includes the description of who manages the network, what in it is managed and how it can be managed. WSN management context shall be described by using three dimensions: management functional areas, management levels, and WSN functionalities Issues Concerning Management Information Base (MIB) Implementaion and Usage The description of objects present in the information model and the relationship among them are specified in the management information base. In the WSN, in order to update a MIB with the current network state, it may be required to measure various parameters. In general, the collection of these parameters presents spatial

15 Functional and Information Models for the MANNA Architecture 15 and temporal errors. This is called the "uncertainty problem". To have a higher precision in the network state, probabilistic measures should be done with a higher granularity. As in any probing, this would take a finite amount of the system energy and could modify the network state. This is called the "probe effect''. In this way, a better precision in the management information requires the modification of the WSN state. The MANNA architecture proposes the limitation in the scope as a method for reducing the uncertainty and the energy consumption while updating the MIB. Spatial limitation consists in defining a physical space inside which the data will be considered for management. Temporal limitation defines a time window (fixed or sliding) inside which the collected data are considered. Functional limitation selects the data of a certain functional network segment for management, for example, the data of a group of nodes or a group leader. In MANNA physical architecture defined in (Ruiz,2002) we discussed the physical implementation of the management. In relation to MIB, many tools in the application layer prefer to deal the data collection as a traditional database, using well-known query languages to access the data. However, in applications which require tens of thousands of data sources, with fast data exchange, these systems are inefficient. WSN have limited bandwidth (whose quality is variable) and energy capacity. The management does not consume significant amounts of this resource. Data management is needed for the high scalability, not offering critical failure points and taking the data from the source to the requester as fast as possible. 6.2 WSN Dynamic Information Model. In a WSN, the network conditions can vary dramatically along the time. In this case, the utilization of models established by MANNA is of fundamental importance for the management, although its updating cycle can be extremely dynamic and complex. Based on the information obtained with these models, services and functions are executed according to management policies. Dynamic management information is described by WSN models and needs to be obtained frequently. The acquisition of this information has a cost in terms of energy consumption. Therefore, an important aspect is to determine the adequate moment, frequency, and fidelity for updating that information. Furthermore, the information collected may be not valid at the moment is processed by the management entity due to delays, omissions, and uncertainty present in WSNs. In the obtaining of WSN models some static information are necessary. In the following, some network models are presented. They always represent dynamical aspects of the network. The dynamic information represented in the network models could or could not be stored in MIBs.

16 16 GRES Février 2003, Fortaleza-CE-Brésil. Sensing Coverage Area Map. This model describes the actual sensing coverage map of the sensor elements. Communication Coverage Area Map. This model describes the present communication coverage map from the range of transceivers. Production. Coverage Area Map. This model describes the actual production coverage map of the sensor nodes. Behavioral Model. Represents the behavior of a WSN. Statistical and probabilistic models may be much more efficient in estimating the network behavior than deterministic models. Dependence Model. Represents the functional dependency that exists between the nodes. The network is modeled as a graph, where the nodes in the graph correspond to nodes in the WSN and the edges between them represent the existing dependency relations, as, for example, the connectivity between the nodes. In order to represent the dependencies, Bayesian or Markovian models, for instance, may be used. Network Topology. Represents the actual topology map and the reachability of the network. It may be used to obtain information about the necessity of adding new nodes. Residual Energy. Represents the remaining energy in a node or in a network. According to the location and its activities, the remaining energy of each sensor is different. This information may also be available considering a region or a time interval. Using this information, together with the data generated by the network topology model, it is possible to identify the areas that will have a shorter lifetime. Usage Standard. Represents the activity of the network. It can be delimited for a period of time, quantity of data transmitted for each sensor unit, or still by the number of movements made by the target. Cost. Represents the cost of equipment, energy and personnel necessary for maintaining the desired performance levels. Other models may be used for the representation of network functionalities, from other perspectives. In telecommunication networks and distributed systems, there are two categories of relations - structural and cooperational -, that may be represented through these models: Structural Models. They represent the relations of aggregation and of connectivity between network elements, as well as the description of the same network elements; Cooperational Models. They represent relations of interaction between network entities. For example, there is a "service user'' relation. The relations of cooperation are created, activated and terminated (normally, abnormally, aborted, etc) between the network components and distributed systems. The components involved may, by their own initiative or activated by foreign actors, adjust their behavior or share resources, contributing to a common objective. In sensor networks, the cooperation between the sensors, in general, is a peer-to-peer type. Only two sensor nodes cooperate within each other at a given moment.

17 Functional and Information Models for the MANNA Architecture Overview of the Management Information Model This section provides a possible situation for understanding how the various managed object classes are used to provide management services proposed by the MANNA architecture. We describe a possible management situation and how the MANNA architecture works and identify the corresponding managed object. We consider the management service of density maintenance. Consider that a managing entity has just received a sensing range area map and detects the existence of a high node density, because there are lots of intersections from the sensing range of the nodes. In this case, the used attributes of managed object classes are: transmission power of transceivers, location of nodes, energy capacity and remaining energy level of nodes, sensor type, range of sensor, data delivery of network, mobility of network, type of phenomenon, node distribution, etc. The managing entity faces a redundancy problem of the sensing data received. On one hand redundancy provides a mechanism of fault-tolerance and multiresolution. On the other hand, it represents waste of resources. This redundancy problem was detected by the MANNA architecture using the WSN models, in particular, the "Sensing Coverage Area Map''. Based on this map, maintenance functions may be executed. These functions can be manual, automatic or semi-automatic, depending on the physical architecture established for the management, and the management policy. In this case, a function possibly invoked is the "Node Operating State Control Function'' which can change the node attribute operational state. This function and the used management information represents the intersection of the three abstraction plans for the Configuration Functional Area, Network Element Management Level and Sensing Functionality. The function allows placing the redundant nodes in the inactive state. For this, the agent attributes the value disable for the operational state of the objects present in the MIB which represents such nodes, acting over the nodes and removing them from the sensing service. In the MANNA architecture, the execution of management services (composed by functions and using management information static) are dependent on the information obtained from the WSN models (topology map, energy map, covering area map). The possible locations of the management entities (manager and agent), their functionalities and the type of the management (centralized, distributed, and hierarchical) are defined by the MANNA functional architecture. All physical aspects of the management are establish by the MANNA physical architecture. All this is based on three management dimensions: management functional area, management levels, and WSN functionalities.

18 18 GRES Février 2003, Fortaleza-CE-Brésil. 8.. Conclusion The WSN management is related to activities which control or monitor the use of resources to promote productivity. Within WSNs, the resources can be those which provide gathering, data storage or processing capabilities, or they can be those which provide interconnection capabilities. Human beings are ultimately responsible for managing the WSN management environment, although responsibilities may be delegated to automated processes. In this work we focus on an information model for a WSN that is designed and used for management. The information model is designed to ensure common syntax and semantic of management information. The purpose of the information model is to give structure to the management information conveyed externally by systems management protocols and to model management aspects of the related resources. The resources exist independently of their need to be managed. The relationship that exists between the resource and the managed object, as an abstraction of that resource is not modeled in a general way; that is, the precise properties abstracted and the specific effects of management operations on a resource must be specified as part of the managed object class specification. This will make possible the integration of organizational, administrative, and maintenance activities for this kind of network. In the MANNA architecture, we define two kinds of management information: static and dynamic. The development of the information model led to the formulation of the concept that management information and both functional and physical architectures are specified from three viewpoints: management functional areas, management level and WSN functionalities. 9. Bibliography Budhaditya Deb, Sudeept Bhatnagar and Badri Nath, " A Topology Discovery Algorithm for Sensor Networks with Applications to Network Management", Technical Report of Department of Computer Science, Rutgers University DCS-TR-441, May, Cerpa, A. and J. Elson, D. Estrin, L. Girod, M. Hamilton and J. Zhao " Habitat Monitoring: Application Driver for Wireless Communications Technology", In Proceedings of the 2001 ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, April Ruiz, Linnyer Beatrys. "MANNA: A Management Architecture for Wireless Sensor Networks", Technical Report of Department of Computer Science, Federal University of Minas Gerais, August, Ruiz, Linnyer Beatrys; Nogueira José Marcos; Loureiro, Antonio A.. "MANNA: A Management Architecture for Wireless Sensor Networks", IEEE Communication Maganzine, vol. 41 n.2, 2003.