Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated. 1.

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In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation) , that eciently disseminates information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specic knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to eciently distribute data given a limited energy supply. We simulate and analyze the performance of two specic SPIN protocols, comparing them to other possible approaches and a theoretically optimal protocol. We nd that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches. We also nd that, in terms...

Abstract. In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminate information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specific knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to efficiently distribute data given a limited energy supply. We simulate and analyze the performance of four specific SPIN protocols: SPIN-PP and SPIN-EC, which are optimized for a point-to-point network, and SPIN-BC and SPIN-RL, which are optimized for a broadcast network. Comparing the SPIN protocols to other possible approaches, we find that the SPIN protocols can deliver 60 % more data for a given amount of energy than conventional approaches in a point-to-point network and 80 % more data for a given amount of energy in a broadcast network. We also find that, in terms of dissemination rate and energy usage, the SPIN protocols perform close to the theoretical optimum in both point-to-point and broadcast networks.

Wireless distributed microsensor systems will enable the reliable monitoring and control of a variety of applications that range from medical and home security to machine diagnosis, chemical/biological detection and other military applications. The sensors have to be designed in a highly integrated fashion, optimizing across all levels of system abstraction, with the goal of minimizing energy dissipation. This paper addresses some of the key design considerations for future microsensor systems including the network protocols required for collaborative sensing and information distribution, system partitioning considering computation and communication costs, low energy electronics, power system design and energy harvesting techniques. 1. Introduction Over the last few years, the design of micropower wireless sensor systems has gained increasing importance for a variety of civil and military applications. The Low Power Wireless Integrated Microsensors (LWIM) project has made major advan...

Recent advances in hardware technology facilitate applications requiring large numbers of sensor devices, where each sensor device has computational, storage, and communication capabilities. Since sensor devices are powered by ordinary batteries, power is a limiting resource in sensor networks. Power usage can be reduced by pushing part of the computation into the network to reduce communication cost, which is the main energy consumer in sensor networks. In order to further reduce power usage, we propose power-aware query processing techniques for aggregation queries. Instead of requiring exact answers to queries, we introduce precision into queries to give users full control of the tradeoffs between precision and energy usage. Our query processing approach incorporates in-network prediction to further reduce the need for constant communication. Moreover, we optimize the execution of multiple queries to take advantage of sharing common aggregated values among different queries. Since communication is three orders of magnitude more expensive than computation, incorporating precision and efficiently executing multiple queries results in significant power savings, thus extending the lifetime of sensor networks. 1

This paper introduces a measure of information as a new criteria for the performance analysis of routing algorithms in wireless sensor networks. We argue that since the objective of a sensor network is to estimate a two dimensional random field, a routing algorithm must maximize information flow about the underlying field over the life time of the sensor network. We develop two novel algorithms, MIR (Maximum Information Routing) and CMIR (Conditional Maximum Information Routing) designed to maximize information flow, and present a comparison of the algorithms to a previously proposed algorithm - MREP (Maximum Residual Energy Path) through simulations. We show that the proposed algorithms give significant improvement in terms of information flow, when compared to MREP.

Abstract. Power conservation is a critical issue for ad hoc wireless networks. The main objective of the paper is to find the minimum uniform transmission range of an ad hoc wireless network, where each node uses the same transmission power, while maintaining network connectivity. Three different algorithms, Prim’s Minimum Spanning Tree (MST), its extension with Fibonacci heap implementation, and an area-based binary search are developed to solve the problem. Their performance is compared by simulation study together with Kruskal’s MST, a known solution proposed by Ramanathan and Rosales-Hain for topology control by transmission power adjustment, and an edgebased binary search used by the same study in order to find the per-node-minimality after Kruskal’s algorithm is applied. Our results show that Prim’s MST outperforms both Kruskal’s MST and the two binary searches. The performance between Prim’s MST implemented with binary heap and Fibonacci heap is fairly close, with the Fibonacci implementation slightly outperforming the other. 1

Recent advances in hardware technology make applications requiring large numbers of sensor devices possible, where each sensor device has computation, memory, and communication capabilities. Since sensor devices are powered by ordinary batteries, power is a limiting resource in sensor networks. Some work has been proposed to reduce the power usage by pushing part of the computation into the network to reduce communication cost, which is an expensive operation in sensor networks. In order to further reduce power usage based on the inherent property of sensor networks, we propose power-aware query processing techniques for aggregation queries. Instead of giving exact answers to users' queries, we introduce precision into queries to give users full control of the tradeoff between precision and energy usage. By employing the notion of value prediction at the base station, the need for constant communication of sensed values from the sensor devices to the base station is avoided. Since communication is three orders of magnitude more expensive than computation, significant power savings can be realized extending the lifetime of sensor networks 1

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated. 1.