There has been growing interest in the Mobile WSN applications where mobility is the fundamental characteristic of the sensor nodes. Mobility poses many challenges to the routing protocols used in such applications. In this thesis we evaluate the performance of Collection Tree Protocol as applied in mobile WSN scenarios. The simulation study shows CTP performs poorly in mobile scenario because of the frequent tree re-generation resulting from node movements. We compare Collection Tree Protocol with reactive ad hoc network routing protocols. The simulation results show that collection tree protocol performs better than reactive MANET protocols in terms of data delivery ratio and control overhead under low traffic rates. The end-to-end delay obtained in case of reactive protocols is also higher compared to that obtained when using CTP, which is due to their route discovery process. This thesis presents an improved data collection protocol Fixed Node Aided CTP based on the analysis of CTP. The protocol introduces the concept of fixed aided routing into CTP. It is shown that our enhanced CTP outperforms CTP in terms of data delivery ratio and control overhead chosen as performance metrics. / UOIT

Wireless sensor networks (WSN) have generated tremendous interest among researchers these years because of their potential usage in a wide variety of applications.<p> Sensor nodes are inexpensive portable devices with limited processing power and energy resources. Sensor nodes can be used to collect information from the environment, locally process this data and transmit the sensed data back to the user.<p> This thesis proposes a new reliable data delivery protocol for general point-to-point data delivery (unicasting) in wireless sensor networks. The new protocol is designed that aims at providing 100% reliability when possible as well as minimizing overhead and network delay. The design of the new protocol includes three components. The new protocol adopts a NACK-based hop-by-hop loss detection and recovery scheme using end-to-end sequence numbers. In order to solve the single/last packet problem in the NACK-based approach, a hybrid ACK/NACK scheme is proposed where an ACK-based approach is used as a supplement to the NACK-based approach to solve the single/last packet problem. The proposed protocol also has a new queue management scheme that gives priority to new data. By introducing the idea of a Ready_Bit and newer packet first rule in the transmission queue, nodes can detect and recover lost packets in parallel with the normal data transmission process. The performance of the new protocol is tested in a Crossbow MicaZ testbed. Experimental results show that the new protocol performs well under various system and protocol parameter settings.

Wireless sensor networks (WSN) have generated tremendous interest among researchers these years because of their potential usage in a wide variety of applications.<p> Sensor nodes are inexpensive portable devices with limited processing power and energy resources. Sensor nodes can be used to collect information from the environment, locally process this data and transmit the sensed data back to the user.<p> This thesis proposes a new reliable data delivery protocol for general point-to-point data delivery (unicasting) in wireless sensor networks. The new protocol is designed that aims at providing 100% reliability when possible as well as minimizing overhead and network delay. The design of the new protocol includes three components. The new protocol adopts a NACK-based hop-by-hop loss detection and recovery scheme using end-to-end sequence numbers. In order to solve the single/last packet problem in the NACK-based approach, a hybrid ACK/NACK scheme is proposed where an ACK-based approach is used as a supplement to the NACK-based approach to solve the single/last packet problem. The proposed protocol also has a new queue management scheme that gives priority to new data. By introducing the idea of a Ready_Bit and newer packet first rule in the transmission queue, nodes can detect and recover lost packets in parallel with the normal data transmission process. The performance of the new protocol is tested in a Crossbow MicaZ testbed. Experimental results show that the new protocol performs well under various system and protocol parameter settings.

The objective of this thesis is to address the problem of energy conservation in wireless sensor networks by tackling two fundamental problems: topology control and data delivery. We first address energy-aware topology control taking into account throughput per unit energy as the primary metric of interest. Through both experimental observations and analysis, we show that the optimal topology is a function of traffic load in the network. We then propose a new topology control scheme, Adaptive Topology Control (ATC), which increases throughput per unit energy. Based on different coordinations among nodes, we proposed three ATC schemes: ATC-CP, ATC-IP, and ATC-MS. Through simulations, we show that three ATC schemes outperform static topology control schemes, and particularly the ATC-MS has the best performance under all environments. Secondly, we explore an energy-aware data delivery problem consisting of two sub-problems: downstream (from a sink to sensors) and upstream (from sensors to a sink) data delivery. Although we address the problems as two independent ones, we eventually solve those problems with two approaches: GARUDA-DN and GARUDA-UP which share a common structure, the minimum dominating set. For the downstream data delivery, we consider reliability as well as energy conservation since unreliable data delivery can increase energy consumption under high data loss rates. To reduce energy consumption and achieve robustness, we propose GARUDA-DN which is scalable to the network size, message characteristics, loss rate and the reliable delivery semantics. From ns2-based simulations, we show that GARUDA-DN performs significantly better than the basic schemes proposed thus far in terms of latency and energy consumption. For the upstream data delivery, we address an energy efficient aggregation scheme to gather correlated data with theoretical solutions: the shortest path tree (SPT), the minimum spanning tree (MST) and the Steiner minimum tree (SMT). To approximate the optimal solution in case of perfect correlation among data, we propose GARUDA-UP which combines the minimum dominating set (MDS) with SPT in order to aggregate correlated data. From discrete event simulations, we show that GARUDA-UP outperforms the SPT and closely approximates the centralized optimal solution, SMT, with less amount of overhead and in a decentralized fashion.

Pocket Switched Networks (PSNs) offer a means of infrastructureless inter-human communication by utilising Delay and Disruption Tolerant Networking (DTN) technology. However, creating PSNs involves solving challenges which were not encountered in the Deep Space Internet for which DTN technology was originally intended.End-to-end communication over multiple hops in PSNs is a product of short range opportunistic wireless communication between personal mobile wireless devices carried by humans. Opportunistic data delivery in PSNs is far less predictable than in the Deep Space Internet because human movement patterns are harder to predict than the orbital motion of satellites. Furthermore, PSNs require some scheme for efficient neighbour discovery in order to save energy and because mobile devices in PSNs may be unaware of when their next encounter will take place.This thesis offers novel solutions for neighbour discovery and opportunistic data delivery in PSNs that make practical use of dynamic inter-human encounter patterns.The first contribution is a novel neighbour discovery algorithm for PSNs called PISTONS which relies on a new inter-probe time calculation (IPC) and the bursty encounter patterns of humans to set the time between neighbour discovery scans. The IPC equations and PISTONS also give participants the ability to easily specify their required level of connectivity and energy saving with a single variable.This thesis also contains novel distributed spatio-temporal clustering and opportunistic data delivery algorithms for PSNs which can be used to deliver data over multiple hops. The spatio-temporal clustering algorimths are also used to analyse the social networks and transient groups which are formed when humans interact.

Sensor networks use a group of collaborating sensor nodes to collect information about real world phenomena. Sensor nodes use low-power short-range radio links to communicate with each other. Communication between sensor nodes shows significant variation over time and space. This can lead to unreliable and unpredictable network performance. These dynamic and lossy characteristics of wireless links pose major challenges for building reliable sensor networks and raise new issues that data delivery protocols must address. This thesis addresses the problems of designing protocols to overcome time-varying environmental conditions that lead to unpredictable network performance. The goal is to provide reliable data delivery in sensor networks and to minimise energy use. The major contributions of this thesis are: measuring the performance of wireless links in field trials on a time scale of weeks; systematic analysis of strengths and weaknesses of existing data delivery protocols; and the design, implementation and testing of a novel autonomic communication framework. We have measured link quality over time in experiments in unattended outdoor environments. Most previous work focused on spatial properties and experiments were not extensive, only lasting for a few hours. Besides common phenomena found in other work, such as the variation of network performance over time and the existence of asymmetric links, we find that links are independent over long time scales, and performance patterns of links are different. We also analyse the performance of data delivery protocols that use different techniques to improve reliability in sensor networks. Through systematic analysis of strengths and weaknesses of existing data delivery strategies, we find that networks using a single technique can only perform well for a limited range of link conditions. Different strategies are required in different operating conditions. Based on these experimental and theoretical studies, a novel autonomic communication framework (ACF) for wireless sensor networks is proposed. Nodes in this ACF are able to change their behaviour to adapt to time-varying environments so that optimal network performance can be achieved. Our framework provides a holistic solution for reliable data delivery to overcome time-varying wireless links. Our implementation and experimental evaluations demonstrate that this holistic framework is effective for reliable and energy-efficient data delivery in realistic sensor network settings.