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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OF THE DISSERTATION University of California, Los Angeles, 2003 Professor Deborah L. Estrin, Chair active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is a critical piece of infrastructure in any dis- tributed system, but wireless sensor networks make particularly extensive use physical world. However, while the clock accuracy and precision requirements are often stricter in sensor networks than in traditional distributed systems, energy and channel constraints limit the resources available to meet these goals.

Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. Sensor nodes cooperate in order to merge individual sensor readings into a high-level sensing result, such as integrating a time series of position measurements into a velocity estimate. The physical time of sensor readings is a key element in this process called data fusion. Hence, time synchronization is a crucial component of WSNs. We argue that time synchronization schemes developed for traditional networks such as NTP [21] are ill-suited for WSNs and suggest more appropriate approaches.

As the cost of embedded sensors and actuators drops, new applications will arise that exploit high density networks of small devices capable of a variety of sensing tasks. Although individual devices may have limited functionality, the true value of the system comes from the emergent behavior that arises when data from many places in the system is combined. This type of data fusion has a number of requirements, but two of the most important are: 1) synchronized time, precise enough to resolve movement in the sensed phenomenon (e.g., sound); and 2) known geographic locations, on a similar scale to the sensors' size and deployment density. However, the installation cost of a localization system with sufficient granularity is considerable, because of the large amount of effort required to deploy such a system and make all the measurements required to tune it. In this paper, we describe a system based on COTS components that incorporates our novel time synchronization and acoustic ranging techniques. The result is a low-cost, readily available platform for distributed, coherent signal processing.

Sensornets are large-scale distributed sensing networks comprised of many small sensing devices equipped with memory, processors, and short-range wireless communication. Making effective use of sensornet data will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Recent work has identified data-centric routing as one such method. In this paper we suggest that a companion method, data-centric storage, may also be a useful approach.

We present the design, implementation, and evaluation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems, particularly distributed source localization. Each ENSBox integrates an ARM processor running Linux and supports key facilities required for source localization: a sensor array, wireless network services, time synchronization, and precise self-calibration of array position and orientation. The ENSBox’s integrated, high precision self-calibration facility sets it apart from other platforms. This self-calibration is precise enough to support acoustic source localization applications in complex, realistic environments: e.g., 5 cm average 2D position error and 1.5 degree average orientation error over a partially obstructed 80x50 m outdoor area. Further, our integration of array orientation into the position estimation algorithm is a novel extension of traditional multilateration techniques. We present the result of several different test deployments, measuring the performance of the system in urban settings, as well as forested, hilly environments with obstructing foliage and 20–30 m distances between neighboring nodes. Categories and Subject Descriptors C.3 [Computer Systems Organization]: Special-Purpose and Application-Based Systems—Signal processing

In this paper, we describe an implementation of a ad-hoc, distributed sensor platform that provides synchronized time to its users. By abstracting the time synchronization layer away, we allow developers to focus on the core challenges of their applications (e.g., signal processing, aggregation, routing) rather than dealing with the algorithmic and systems issues that inevitably arise when integrating sensing with distributed synchronization. Through a variety of techniques, notably the use of Reference-Broadcast Synchronization (RBS) [5], our platform offers better than 5sec precision when comparing streams of audio data sampled at nodes separated by one network hop.

in Kakadu National Park using a large scale wireless sensor network deployment. Cane toads were mistakenly introduced in Australia in 1935. Their uncanny ability to survive in diverse climates and lack of natural predators in the Australian ecosystem have promoted unhindered growth of cane toads for the last 68 years. This application is of tremendous importance to Australia because cane toads are endangering native species and the ecosystem. We comment on how wireless sensor network technology can address long-term research challenges for cane-toad monitoring, and propose a novel framework for planning sensor deployment to meet application, economic and networking objectives.