IP based Wireless Sensor Networks : performance Analysis using Simulations and Experiments

Wireless sensor networks are at the crux of the Internet of Things applications. At the current state, there exist several technologies competing against each other in the IoT space. These proprietary technologies and hardware pose a serious problem of interoperability, which is vital to unleash the vision of the Internet of Things. Moreover, the traditional approach towards wireless sensor networks was to be unlike the internet, primarily because of the power and memory constraints posed by the tiny sensor nodes. The IETF 6LoWPAN technology facilitates the usage of IPv6 communications in sensor networks, which helps solve the problem of interoperability, enabling low power, low cost micro-controllers to be globally connected to the internet. Another IETF technology, CoAP allows interactive communication over the internet for these resource constrained devices. Along with 802.15.4, 6LoWPAN and CoAP, an open, standardized WSN stack for resource constrained devices and environments becomes available. The Contiki OS, touted as the open source OS for IoT, provides low power IPv6 communications and supports the 6LoWPAN and CoAP protocols, along with mesh routing using RPL. Along with these, a CoAP framework, Californium (Cf) provides a scalable and RESTful API to handle IoT devices. These open tools and technologies are employed in this work to form an open, inter-operable, scalable, reliable and low power WSN stack. This stack is then simulated using Contiki's default network simulator Cooja, to conduct performance analysis in varying conditions such as noise, topology, traffic etc. Finally, as a proof of concept and a validation of the simulated stack, physical deployment is carried out, using a Raspberry Pi as a border router, which connects the wireless sensor network to the global internet along with the T-mote sky sensor motes. Therefore, this work develops and demonstrates an open, interoperable, reliable, scalable, low power, low cost WSN stack, both in terms of simulations and physical deployments, and carries out performance evaluation of the stack in terms of throughput, latency and packet loss.<p>Validerad; 2016; Nivå 1; 2016-11-22 (inah)</p>A belief-rule-based DSS to assess flood risks by using wireless sensor networks, PERvasive Computing and COMmunications for sustainable developmen