THAWS: automated wireless sensor network development and deployment

This research focuses on the design and implementation of a tool to speed-up the development and deployment of heterogeneous wireless sensor networks. The THAWS (Tyndall Heterogeneous Automated Wireless Sensors) tool can be used to quickly create and configure application-specific sensor networks. THAWS presents the user with a choice of options, in order to characterise the desired functionality of the network. With this information, THAWS generates the necessary code from pre-written templates and well-tested, optimized software modules. This is then automatically compiled to form binary files for each node in the network. Wireless programming of the network completes the task of targeting the wireless network towards a specific sensing application. THAWS is an adaptable tool that works with both homogeneous and heterogeneous networks built from wireless sensor nodes that have been developed in the Tyndall National Institute

ShakeNet: A portable wireless sensor network for instrumenting large civil structures

We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software

THAWS: automated design and deployment of heterogeneous wireless sensor networks

This research focuses on the design and implementation of a tool to speed-up the development and deployment of heterogeneous wireless sensor networks. The THAWS (Tyndall Heterogeneous Automated Wireless Sensors) tool can be used to quickly create and configure application-specific sensor networks, based on a list of application requirements and constraints. THAWS presents the user with a choice of options, in order to gain this information on the functionality of the network. With this information, THAWS uses code generation techniques to create the necessary code from pre-written templates and well-tested, optimized software modules from a library, which includes an implementation of novel plug-and-play sensor interface. These library modules can also be modified at the code generation stage. The application code and necessary library modules are then automatically compiled to form binary instruction files for each node in the network. The binary instruction files then wirelessly propagate through the network, and reprogram the nodes. This completes the task of targeting the wireless network towards a specific sensing application. THAWS is an adaptable tool that works with both homogeneous and heterogeneous networks built from wireless sensor nodes that have been developed in the Tyndall National Institute. Its advantage over traditional methods of WSN development is simplification of development

Wireless sensor node design for heterogeneous networks

Two complementary wireless sensor nodes for building two-tiered heterogeneous networks are presented. A larger node with a 25 mm by 25 mm size acts as the backbone of the network, and can handle complex data processing. A smaller, cheaper node with a 10 mm by 10 mm size can perform simpler sensor-interfacing tasks. The 25mm node is based on previous work that has been done in the Tyndall National Institute that created a modular wireless sensor node. In this work, a new 25mm module is developed operating in the 433/868 MHz frequency bands, with a range of 3.8 km. The 10mm node is highly miniaturised, while retaining a high level of modularity. It has been designed to support very energy efficient operation for applications with low duty cycles, with a sleep current of 3.3 μA. Both nodes use commercially available components and have low manufacturing costs to allow the construction of large networks. In addition, interface boards for communicating with nodes have been developed for both the 25mm and 10mm nodes. These interface boards provide a USB connection, and support recharging of a Li-ion battery from the USB power supply. This paper discusses the design goals, the design methods, and the resulting implementation

EMMON - EMbedded MONitoring

Despite the steady increase in experimental deployments, most of research work on WSNs has focused only on communication protocols and algorithms, with a clear lack of effective, feasible and usable system architectures, integrated in a modular platform able to address both functional and non–functional requirements. In this paper, we outline EMMON [1], a full WSN-based system architecture for large–scale, dense and real–time embedded monitoring [3] applications. EMMON provides a hierarchical communication architecture together with integrated middleware and command and control software. Then, EM-Set, the EMMON engineering toolset will be presented. EM-Set includes a network deployment planning, worst–case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset was crucial for the development of EMMON which was designed to use standard commercially available technologies, while maintaining as much flexibility as possible to meet specific applications requirements. Finally, the EMMON architecture has been validated through extensive simulation and experimental evaluation, including a 300+ nodes testbed

EMMON: a system architecture for large- scale, dense and real-time WSNs

In spite of the significant amount of scientific work in Wireless Sensor Networks (WSNs), there is a clear lack of effective, feasible and usable WSN system architectures that address both functional and non-functional requirements in an integrated fashion. This poster abstract outlines the EMMON system architecture for large-scale, dense, real-time embedded monitoring. EMMON relies on a hierarchical network architecture together with integrated middleware and command&control mechanisms. It has been designed to use standard commercially– available technologies, while maintaining as much flexibility as possible to meet specific applications’ requirements. The EMMON WSN architecture has been validated through extensive simulation and experimental evaluation, including through a 300+ node test-bed, the largest WSN test-bed in Europe to dat

A hierarchical group model for programming sensor networks

A hierarchical group model that decouples computation from hardware can characterize and aid in the construction of sensor network software with minimal overhead. Future sensor network applications will move beyond static, homogeneous deployments to include dynamic, heterogeneous elements. These sensor networks will also gain new users, including casual users who will expect intuitive interfaces to interact with sensor networks. To address these challenges, a new computational model and a system implementing the model are presented. This model ensures that computations can be readily reassigned as sensor nodes are introduced or removed. The model includes methods for communication to accommodate these dynamic elements. This dissertation presents a detailed description and design of a computational model that resolves these challenges using a hierarchical group mechanism. In this model, computation is tasked to logical groups and split into collective and local components that communicate hierarchically. Local computation is primarily used for data production and publishes data to the collective computation. Similarly, collective computation is primarily used for data aggregation and pushes results back to the local computation. Finally, the model includes data-processing functions interposed between local and collective functions that are responsible for data conversion. This dissertation also presents implementations and applications of the model. Implementations include Kensho, a C-based implementation of the hierarchical group model, that can be used for a variety of user applications. Another implementation, Tables, presents a spreadsheet-inspired view of the sensor network that takes advantage of hierarchical groups for both computation and communication. Users are able to specify both local and collective functions that execute on the sensor network via the spreadsheet interface. Applications of the model are also explored. One application, FUSN, provides a set of methods for constructing filesystem-based interfaces for sensor networks. This demonstrates the general applicability of the model as applied to sensor network programming and management interfaces. Finally, the model is applied to a novel privacy algorithm to demonstrate that the model isn\u27t strictly limited to programming interfaces

Towards Bridging IoT and Cloud Services: Proposing Smartphones as Mobile and Autonomic Service Gateways

Computing is currently getting at the same time incredibly in the small with sensors/actuators embedded in our every- day objects and also greatly in the large with data and ser- vice clouds accessible anytime, anywhere. This Internet of Things is physically closed to the user but suffers from weak run-time execution environments. Cloud Environments provide powerful data storage and computing power but can not be easily accessed and integrate the final-user context- awareness. We consider smartphones are set to become the universal interface between these two worlds. In this position paper, we propose a middleware approach where smartphones provide service gateways to bridge the gap between IoT services and Cloud services. Since smartphones are mobile gateways, they should be able to (re)configure themself according to their place, things discovered around, and their own resources such battery. Several issues are discussed: collaborative event-based context management, adaptive and opportunistic service deployment and invocation, multi-criteria (user- and performance-oriented) optimization decision algorithm.Comment: Position Pape

Programming models for sensor networks: a survey

Sensor networks have a significant potential in diverse applications some of which are already beginning to be deployed in areas such as environmental monitoring. As the application logic becomes more complex, programming difficulties are becoming a barrier to adoption of these networks. The difficulty in programming sensor networks is not only due to their inherently distributed nature but also the need for mechanisms to address their harsh operating conditions such as unreliable communications, faulty nodes, and extremely constrained resources. Researchers have proposed different programming models to overcome these difficulties with the ultimate goal of making programming easy while making full use of available resources. In this article, we first explore the requirements for programming models for sensor networks. Then we present a taxonomy of the programming models, classified according to the level of abstractions they provide. We present an evaluation of various programming models for their responsiveness to the requirements. Our results point to promising efforts in the area and a discussion of the future directions of research in this area.