Large-scale wireless sensor networks consist of thousands of tiny and low cost nodes with very limited energy, computing power and communication capabilities. They have a myriad of possible applications. They can be used in hazardous and hostile environments to sense for deadly gases and high temperatures, in personal area networks to monitor vital signs, in military and civilian environments for intrusion detection and tracking, emergency operations, etc. In large scale wireless sensor networks the protocols need to be scalable and energy-efficient. Further, new strategies are needed to address the well-known energy depletion problem that nodes close to the sink node face. In this thesis the Scalable Energy-efficient Location-Aided Routing (SELAR) protocol for wireless sensor networks is proposed to solve the above mentioned problems. In SELAR, nodes use location and energy information of the neighboring nodes to perform the routing function. Further, the sink node is moved during the network operation to increase the network lifetime. By means of simulations, the SELAR protocol is evaluated and compared with two very well-known protocols - LEACH (Low-Energy Adaptive-Clustering Hierarchy) and MTE (Minimum Transmission Energy). The results indicate that in realistic senarios,SELAR delivers up to 12 times more and up to 1.4 times more data packets to the base station than LEACH and MTE respectively. It was also seen from the results that for realistic scenarios, SELAR with moving base station has up to 5 times and up to 27 times more lifetime duration compared to MTE and LEACH respectively.

<p>Wireless Sensor Network is an emerging technology that has applicationsin Wireless Actuators, remote controlling, distribution of softwareupdates and distribution of parameters to sensor nodes. This projectwork basically covers the concept of macro-diversity. This is a situationin which several transmitters are used for transferring the same signal (inmulti-hop sensor networks) to check the increase in connected nodes orin network coverage. Transmitter macro-diversity increases the receivedsignal strength and thus increases the signal-to-noise ratio which resultsin a lower outage probability. To accomplish this task three differentstrategies have been simulated using thirteen different cases. Broadcastingis used when forming SFN of size one (strategy one) and uni-castingis used for forming SFNs of size two (strategy two) and size three (strategythree).In this project reference material has been gathered frombooks, journals and web sources; and MATLAB has been used as thesimulation tool in which codes are written in the M programming language.The algorithm works firstly by discovering all the nodes that areconnected directly with the Base Station through multi-hoping, afterwhich the second algorithm is applied to check how many more nodescan be reached by forming SFNs. A gain of up to 79% was observedusing strategy one and strategy two and up to 83% in strategy three.The results shows that strategy one (Forming SFNs using BroadcastingTechnique) is the best as more nodes can be reached (for different cases)than for the other two strategies (forming SFNs using uni-casting technique).</p>

Wireless Sensor Network is an emerging technology that has applicationsin Wireless Actuators, remote controlling, distribution of softwareupdates and distribution of parameters to sensor nodes. This projectwork basically covers the concept of macro-diversity. This is a situationin which several transmitters are used for transferring the same signal (inmulti-hop sensor networks) to check the increase in connected nodes orin network coverage. Transmitter macro-diversity increases the receivedsignal strength and thus increases the signal-to-noise ratio which resultsin a lower outage probability. To accomplish this task three differentstrategies have been simulated using thirteen different cases. Broadcastingis used when forming SFN of size one (strategy one) and uni-castingis used for forming SFNs of size two (strategy two) and size three (strategythree).In this project reference material has been gathered frombooks, journals and web sources; and MATLAB has been used as thesimulation tool in which codes are written in the M programming language.The algorithm works firstly by discovering all the nodes that areconnected directly with the Base Station through multi-hoping, afterwhich the second algorithm is applied to check how many more nodescan be reached by forming SFNs. A gain of up to 79% was observedusing strategy one and strategy two and up to 83% in strategy three.The results shows that strategy one (Forming SFNs using BroadcastingTechnique) is the best as more nodes can be reached (for different cases)than for the other two strategies (forming SFNs using uni-casting technique).

Environmental monitoring represents a major application domain for wireless sensor networks (WSN). However, despite significant advances in recent years, there are still many challenging issues to be addressed to exploit the full potential of the emerging WSN technology. In this dissertation, we introduce the design and implementation of low-power wireless sensor networks for long-term, autonomous, and near-real-time environmental monitoring applications. We have developed an out-of-box solution consisting of a suite of software, protocols and algorithms to provide reliable data collection with extremely low power consumption. Two wireless sensor networks based on the proposed solution have been deployed in remote field stations to monitor soil moisture along with other environmental parameters. As parts of the ever-growing environmental monitoring cyberinfrastructure, these networks have been integrated into the Texas Environmental Observatory system for long-term operation. Environmental measurement and network performance results are presented to demonstrate the capability, reliability and energy-efficiency of the network.