Academic education Wireless Sensor Network ... - Semantic Scholar

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50 International Symposium ELMAR-2008, 10-12 September 2008, Zadar, Croatia

Academic education Wireless Sensor Network: AeWSN Karl Benkič1, Marko Malajner1, Aleksandar Peulič2 and Žarko Čučej1 1

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University of Maribor, FERI, Smetanova 17 University of Kragujevac, Technical faculty Čačak, Svetog save 65, 32000 Čačak E-mail: [email protected]

Abstract - Over the years several technologies for WSN, including MAC protocols, routing protocols and topology algorithms have been proposed. ZigBee is one of such technologies. This work presents an educations wireless sensor network called AeWSN. AeWSN is based on ZigBee technology and offers the studying and implementing of different topologies and routing algorithms, evaluation of these algorithms and other pre simulation. An AeWSN wireless sensor network consist of three main modules: physical WSN module, Services and control module and "random users" connected to static WSN. Keywords - wireless sensor networks, education, software

1. INTRODUCTION Recently, the use of Wireless Sensor Networks (WSN) has greatly expaned. Military, health and medicine, surveillance and even industrial applications are just a few of the fields where a WSN is already used extensively [1]. Consequently, there is a strong need to provide at least basic knowledge about WSN to undergraduate students. Standard WSN solutions, such as ZigBee [4], were designed with the idea, that primary user concern is just about applications only and that a deep knowledge of WSN is unnecessary. This is, ofcourse, unsuitable for some education purposes. For example: we would like to provide our students with in-depth knowledge about WSN. The project called AeWSN was put in motion last year with this framework. Project AeWSN defines an Academic education Wireless Sensor Network which offers students and researchers the opportunity to the specifics of wireless communications systems, such as forming ad-hoc network, designing media access controls (MAC) for considering optimization between energy consumption and Quality of Services (QoS), topology control and routing testing etc. The goals of these explorations is “learn-by-doing” about the state-of-the-art technology, its concepts, applications in modern telecommunication and information and automatization systems. We believe this knowledge is already essential for engineers from mentioned fields as well as for electronic engineers. The AeWSN project is envisaged a continuously developing system enabling students to design and make new hardware, as well as software expansion and use of WSN. We started with simple applications such as the measurements of temperature, moisture and illumination on fixed locations and making this information available to users. In future, we plan to expand AeWSN platform positioning system possibilities, message

deployment service (similar to RDS), health service etc. A simple single extension and broadening of AeWSN is planned to be carried out by undergraduate students as part of their seminar work. More pretentiousness studies and research work is intended for graduate students and research projects by Ph.D. students.

2. DESCRIPTION OF AeWSN AeWSN is actually a testbed, consisting of (Fig. 1): • WSN nodes, • personal computer with base station module, • SPaRCSoft program containing five modules, • user interface, • commercial programs for modeling, simulation, visualization and software development. Since the idea for developed AeWSN was inspired by standard IEEE 802.15.4 and ZigBee implementation, we have adopted terms coined by them. For exploration of all WSN properties and features we decided, that all network nodes are so called Full Function Device, which enables to configure any kind of WSN topology. 2.1. WSN nodes WSN nodes are designed according to the IEEE 802.15.4 standard. LPC2138 (ARM7) was selected when selecting MCU for the nodes, despite relatively high energy consumption. The reasons for the selection were experiences with CPU from different industrial projects and all the necessary development tools available for it etc. ZigBee compatible Radio Frequency (RF) chip MRF24J40 and LPC2138 ARM microcontroller are connected

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via a Serial Periphery Interface (SPI) bus. Over Analog-Digital Converter (ADC) light is measured. The temperature and humidity sensor is connected over a Dallas one-wire bus. All sensor nodes have remote firmware upgrade feature - firmware of the LPC2138 core procesor can be replaced over ZigBee network. For this purpose we have added the secondary microcontroller PIC18LF2620 and SPI flash memory, where the firmware is stored. Firmware upgrade of the sensor (2.1 processor) is done remotely from the base station (coordinator node).

Fig. 1. AeWSN system The firmware control nodes determines WSN topology and can establish ad-hoc network, etc, as well as some other features latency, traffic, robustness, survivability, etc. 2.3. Personal computer with base station node Special software called SPaRCSoft was developed for the PC. SPaRCSoft is the “soul” of the AeWSN system and its functions are described in the following subsections. SPaRCSoft runs on a PC and is connected to the base station (BSN) WSN sensor node over USB. This makes it part of the AeWSN. The BS node can fulfill several roles: from a sniffer to the WSN coordinator. 2.3. SPaRCSoft The program bundle SPaRCSoft currently consists of five modules (Fig. 1): 1. Authentication and Authorization module. 2. Graph Solver module. 3. Remote Firmware upgrade module.

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4. WSN properties measurement module. 5. WEB service module. The SPaRCSoft is written in C# language in a 3.5 .NET framework (VS2008). Its core also uses API for linking with comercial software as Matlab¸ and OMNET++. Software development tool called μVision is used for ARM processors. Using SPaRCSoft it is possible to have simple implementation of WSN design, build up different test networks and supervise the status in each sensor node. A built-in data base similar to MIB (known from Simple Network Protocol) is used for this purpose by which it is also possible to detect any attack on AeWSN. AAA - An Accreditation, Authentication, Authorization (AAA) module is used for user authentication when they are connecting to the network (of course, if the network is in normal operating state). Users can connect to the WSN through a simple module (basically gateway between 802.15.4 and 802.15.1), with a PDA or a smart-phone which supports Bluetooth. On the PDA there is a simple application allowing logging-in to the network (authentication is made via ZigBee address and the user password). When connected, users can read measurements from any module on the network. Remote firmware upgrade - On every node there is a program with topology and routing algorithm implemented. If we want or need to change the algorithms, a new program must be written, compiled, and prepared in Intel HEX format. Firmware can be written and compiled with every C compiler which supports ARM7 CPU architecture (we currently use KEIL μVision studio). Students and researchers can then upload new firmware to all nodes at the same time (flushing the network) or joust on targeted nodes (one or more) connected to the network. Upgrading is done by SPaRCSoft through BSN which accepts Intel HEX format. The whole firmware update procedure works as follows: New firmware is loaded into SPaRCSoft as Intel HEX format where it is encoded (UUENCODE) and split into a packets size of 256 bytes. Each of the 256 bytes long packets are then transmitted to target node(s) where they are put together into SPI flash. When completed, the firmware is stored in SPI flash, the PIC microcontroller takes over and flashes the LPC. When completed the PIC is put to sleep and LPC takes over. There are two versions of firmware stored on the external flash: Original "working" firmware and a new one when upgrade is made. When firmware upgrade is complete on selected nodes, the coordinator resets the whole network and new algorithms are used for MAC, topology control, data routing…

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Fig. 2. Remote firmware upgrade procedure The complete hardware description, implementation and flashing procedure can be found in other article presented on the conference (Online programmable wireless sensor node for testing purpose). SPaRCGraph - The SPaRCGraph is intended to be used for topology and routing simulations. Topology and routing results are then compared with measurements on the real WSN. The SPaRCGraph is also used for calculating any loss factor in the channel (Log-distance path model) model and for module localization purposes. It is powerful tool for graph theory designed for wireless sensor networks. It is intended as a framework for simplification when developing new topology and routing algorithms as student projects or as a result of previous research. WebServices - When the WSN is free of any test the firmware for "normal operation" is uploaded. When the network is in "normal operation mode" (NOM), sensor nodes gather data about moisture, temperature and illumination. This data is then available to user’s trough HTTP (IIS6 running ASP.NET pages). Data is collected in the SPaRCSoft data gathering section. Data is then transferred to the WebService module and there it is accessible to the HTTP server. SPaRCSoft or SPaRCSoft WebService is inaccessible from the internet. Only the HTTP server has access to it. In the future we, will implement a second WebService which will be accessible as typical ASP.NET WebService. 3. FROM SIMULATIONS TO REAL TEST BED Two main problems need to be solved for simulating topology control and routing algorithms. First, there is no widely known and approved reference model for topology control and routing algorithms. Secondly, there are just a few measurements done on real sensor networks for supporting the theory. Our main goal is to practically (on real WSN) confirm topology and routing simulation results, done with using professional. In regard to this we

built a communication model in SPaRCSoft. Communication model is defined by the communication graph. Topology and routing algorithm simulations are done in OPNET or OMNET++ using previously defined communication graph model. When the simulations are complete, we apply the same routing and topology algorithms to the real network in order to evaluate algorithms on real hardware. Topology and routing algorithms for real networks are coded in ANSI C and/or C++, with the use of μVision. Consequently, the code is not as optimal as in simulation. Due to this, some performance differences may occur when evaluating. When working with real sensor nodes, the AeWSN system must be initialized first. When nodes are deployed they start to broadcast their presence in the neighborhood. When BSN receives the broadcast it sends an invitation to the network. After the nodes in the BSN neighborhood are connected they can accept the broadcast messages in their neighborhood and so on until all the nodes are joined in the network.

Fig. 2. Remote firmware upgrade procedure Figure (Fig. 3) displays the GUI of the SPaRCSoft module SPaRCSoft with topology creation. The power of the transmitting nodes is first simulated (so that no node stays disconnected from the network) and then remotely adjusted. In the figure we can see the theoretical transmitting power (dark color in circle) and reduced transmitting power with channel model (Log-distance) implementation. 3.1. Topology and routing algorithms Topology is defined as “routes implicitly or explicitly used by routing algorith” [2]. Topology has a huge impact on sensor node power consumption and message delivery reliability. As the topology changes, the power consumption of a node is affected (the nearer the neighbor the less the power node consumes). On the other hand, lowering the transmitting power means lowering the count of reachable neighbors. So topology control is a trade-

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off between power consumption and message delivery reliability. Therefore, many topology algorithms (including mesh, cluster tree and star topology defined by ZigBee [4]) can be simulated and tested using the SPaRCGraph module from the SPaRCGraph program. Beside typical ZigBee topology algorithms, some general algorithms are included: • Relative Neighbourhood Graph (RNG). • Minimum Spanning Tree (MST). • Connect Topology. • Noble Topology Control Algorithm (NTC). • Local Information No Topology (LINT). Today, there are more that 60 known routing algorithms for WSN [9]. All the topology algorithms are shortly explained in [2]. First of all the AODV routing protocol for the ZigBee network was implemented [4] followed by the routing algorithms: • Directed diffusion routing protocol. • Rumor Routing Algorithm. • Minimum Cost Forwarding Algorithm. • Power-Efficient Gathering in Sensor Information System routing. Of course, there are some other routing schemes which are also of interest to us (mainly because of QoS support) but we left them for student seminars and research work. We also considered implementing already researched and simulated hybrid routing algorithms based on “ant colony optimization” and “simulated annealing” [5].

4. AeWSN SERVICES The AeWSN network, besides algorithm testing and evaluating, also offers data gathering and services. Service offers people a connection to the WSN and to use it as communication network. If the user wants to connect to a AeWSN, it is required to have: handheld gateway device and PDA or Smart Phone with our software loaded on it. Currently only three services are available on AeWSN: 1. Logging-in to the network, 2. getting information about climate, 3. remote firmware upgrade. There are more services in development, two of them are already at the beta phase: the first one is accessing WSN data over web (HTTP), and the second onse is called user health. When Accessing WSN data over web the user will be able to determine his last connection to the AeWSN, where he was connected and how long. Equal data will be available over PDA and HTTP. pointed out. Eventual restrictions and limitations are commented. Further research directions may be indicated. User health will be a service for real time health monitoring (heart beat, blood pressure, temperature…). It monitors and logs user condition and stores it on the server and in case of an

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emergency (cardiac arrest or stroke) alerts a predefined institution about an event. Of course the user health service will be only run by volunteers working on AeWSN project. We have some experience in the health monitoring field [6] but in the AeWSN project we plan to integrate more than one health service into the wireless sensor network. If the user is authenticated as doctor he will be able to monitor patient health parameters in realtime over PDA or will be able to check medical logs or the medical history of the patient.

5. CONCLUSION The AeWSN project was designed for testing and evaluating wireless sensor networks from the communication point of view – from topology and routing algorithms to information services and security concerns. We have shown that because of the application dependency of commercial WSN they are inappropriate for education. We focused our effort to develop a “studying appropriate” WSN with a simple remotely reconfigurable option. In first stage test-bed will consist from 12 wirelesses sensor node and in the second stage around 45 sensor nodes are planned. With continuously planned student development of AeWSN, we hope that in the near future AeWSN will have implemented a more powerful measurement module and new services, and in this respect more and better routing and MAC algorithms availabe.

REFERENCES [1] F. L. Lewis: Wireless Sensor Networks. Smart Environments: Technologies, Protocols, and Applications, New York, 2004 [2] Gaurav Srivastava, Paul Boustead, Joe F.Chicharo: A Comparison of Topology Control Algorithms for Ad-hoc Networks. University of Wollongong, NSW, Australia, 2003 [3] Qiangfeng Jiang, D. Manivannan: Routing Protocols for Sensor Networks. Department of Computer Science, University of Kentucky, Kentucky [4] R. R. Garcia: Understanding the ZigBee stack. ZigBee alliance home page [5] Karl Benkic and Zarko Cucej: Using Ant colony optimization for routing algorithm in CDMA wireless sensor networks. EuroSSC, Kendal, October 2007 [6] Z. Cucej, A. Peulic: Zigbee based patient parameters monitoring system. ELMAR, 2005 [7] Paolo Santi: Topology Control in Wireless Ad Hoc and Sensor Networks, ISBN-13: 978-0470094532, September 2005. [8] Internet source: www.s-arm.si/UM10120_1.pdf, Philips LPC213x Users Manual [9] Jamal N. Al-Karaki and Ahmed E. Kamal: Routing Techniques in Wireless Sensor Networks: A Survey IEEE Wireless Communications, December 2004