Print Email Facebook Twitter A Spatial Computing Approach to Programming Large Scale Wireless Sensor Networks Title A Spatial Computing Approach to Programming Large Scale Wireless Sensor Networks Author Mihoci Andrei-Bogdan, A.B. Contributor Dulman Stefan, S. (mentor) Pruteanu Andrei, A. (mentor) Van der Wateren Frits, F. (mentor) Faculty Electrical Engineering, Mathematics and Computer Science Department Embedded Systems Programme MSc. Embedded Systems Date 2011-12-15 Abstract The technology required to design and deploy large scale wireless sensor networks is available, affordable and shows an increased interest in various application domains. However, application development for distributed systems is a cumbersome task, typically carried out with low-level embedded programming paradigms. A middleware is usually employed to bridge the gap between the node-level programming and the overall-system application development. Sometimes, the later one is even performed by non-IT specialists. In this thesis we collaborate with the Chess company to integrate the spatial-computing-paradigm-based Proto middleware with the MyriaNed production-ready wireless sensor network. We analyze the integration challenges and provide a mechanism that integrates the Myria specic characteristics (e.g., Gossiping-based communication protocol, Myria Core software design) with Proto. Additionally, we implement new software modules (viral code dissemination, target-oriented adjustment of parameters and a wireless network snifer for debugging) to enhance the application development process. Finally, we create applications using Myria-Proto to check the capabilities of the new software stack. Subject Protowireless sensor networkmiddlewarevirtual machine To reference this document use: http://resolver.tudelft.nl/uuid:fa0f17ad-859a-46e2-9731-8a46d41f6777 Embargo date 2011-12-20 Part of collection Student theses Document type master thesis Rights (c) 2011 Mihoci Andrei-Bogdan , A.B. Files PDF thesis.pdf 4.32 MB Close viewer /islandora/object/uuid:fa0f17ad-859a-46e2-9731-8a46d41f6777/datastream/OBJ/view