Tunable Reliability of Information Transport in Wireless Sensor Networks

A key functionality of Wireless Sensor Networks (WSNs) consists in obtaining and transporting the information of interest (e.g., event/status) required by the applications. The applications running on WSN also specify desired reliability levels on the desired information. Consequently, reliability requirements, possibly changing over time and of tunable levels over an application, are stipulated on the transport of information. As the WSN environments are often exposed to perturbations (e.g., energy depletion, sensor and connectivity loss etc), these specifically need to be considered in order to achieve the desired reliability on information transport. The existing approaches to reliable transport typically focus on maximizing the attained reliability levels than the more complex facets of reliability adaptation or tunability. These approaches thus tend to over utilize the network resources (e.g., energy) even when the application does not require enhanced reliability. On this background, this thesis develops a novel generalized framework for reliable information transport in WSNs. The proposed framework supports various applications, provides tunable reliability of information transport and copes with dynamic network conditions. To ascertain the fundamental issues dictating the reliability of information transport in WSNs, this thesis models and compares existing information transport techniques. We highlight the key problems with the existing techniques and provide solutions to achieve desired application requirements. The generic information transport framework developed in this thesis comprises of flexible and modular architectural blocks where different existing approaches can be easily incorporated. To maintain the generality of the framework we classify WSN applications and devise their information model. We achieve tunable reliability using probabilistic forwarding and opportunistic suppression of the information. For the detection of information loss, a hybrid acknowledgment technique is proposed which efficiently combines implicit and explicit acknowledgments. To ensure end-to-end reliability we develop heuristics to allocate reliability across the hops and tunable retransmission mechanism at each sensor node. In addition, if the sensor nodes know the spatial correlation of the information, they adapt the number of retransmissions according to the number of source nodes. Furthermore, congestion control is necessary in order to ensure the tunable reliability. We propose proactively detecting the congestion by observing the input and output information flow across a node. When congestion is detected, we propose mechanisms to split the information flow on multiple paths to alleviate congestion. If the congestion persists the information rate is adapted by the sensor nodes. Our simulation results in the standard sensor network simulator TOSSIM show that the proposed framework supports various applications with evolving reliability requirements, copes with dynamic network properties and outperforms the state-of-the-art solutions. Our framework also significantly reduces the number of transmissions to result in an efficient solution