Showing papers on "Sensor node published in 2002"

An energy-efficient MAC protocol for wireless sensor networks

Abstract: This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks Wireless sensor networks use battery-operated computing and sensing devices A network of these devices will collaborate for a common application such as environmental monitoring We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 80211 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important S-MAC uses three novel techniques to reduce energy consumption and support self-configuration To reduce energy consumption in listening to an idle channel, nodes periodically sleep Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes Unlike PAMAS, it only uses in-channel signaling Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley The experiment results show that, on a source node, an 80211-like MAC consumes 2-6 times more energy than S-MAC for traffic load with messages sent every 1-10 s

PEGASIS: Power-efficient gathering in sensor information systems

Abstract: Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operate the sensor network for a long period of time. In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000), a data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. If each node transmits its sensed data directly to the base station then it will deplete its power quickly. The LEACH protocol presented by W. Heinzelman et al. is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 300% when 1%, 20%, 50%, and 100% of nodes die for different network sizes and topologies.

Energy-aware wireless microsensor networks

Abstract: This article describes architectural and algorithmic approaches that designers can use to enhance the energy awareness of wireless sensor networks. The article starts off with an analysis of the power consumption characteristics of typical sensor node architectures and identifies the various factors that affect system lifetime. We then present a suite of techniques that perform aggressive energy optimization while targeting all stages of sensor network design, from individual nodes to the entire network. Maximizing network lifetime requires the use of a well-structured design methodology, which enables energy-aware design and operation of all aspects of the sensor network, from the underlying hardware platform to the application software and network protocols. Adopting such a holistic approach ensures that energy awareness is incorporated not only into individual sensor nodes but also into groups of communicating nodes and the entire sensor network. By following an energy-aware design methodology based on techniques such as in this article, designers can enhance network lifetime by orders of magnitude.

GHT: a geographic hash table for data-centric storage

Abstract: Making effective use of the vast amounts of data gathered by large-scale sensor networks will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Previous work has identified data-centric routing as one such method. In an asso-ciated position paper [23], we argue that a companion method, data-centric storage (DCS), is also a useful approach. Under DCS, sensed data are stored at a node determined by the name associated with the sensed data. In this paper, we describe GHT, a Geographic Hash Table system for DCS on sensornets. GHT hashes keys into geographic coordi-nates, and stores a key-value pair at the sensor node geographically nearest the hash of its key. The system replicates stored data lo-cally to ensure persistence when nodes fail. It uses an efficient consistency protocol to ensure that key-value pairs are stored at the appropriate nodes after topological changes. And it distributes load throughout the network using a geographic hierarchy. We evaluate the performance of GHT as a DCS system in simulation against two other dissemination approaches. Our results demonstrate that GHT is the preferable approach for the application workloads predicted in [23], offers high data availability, and scales to large sensornet deployments, even when nodes fail or are mobile.

The bits and flops of the n-hop multilateration primitive for node localization problems

Abstract: The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. Vital to the success of wireless microsensor networks is the ability of microsensors to ``collectively perform sensing and computation''. In this paper, we study one of the fundamental challenges in sensor networks, node localization. The collaborative multilateration presented here, enables ad-hoc deployed sensor nodes to accurately estimate their locations by using known beacon locations that are several hops away and distance measurements to neighboring nodes. To prevent error accumulation in the network, node locations are computed by setting up and solving a global non-linear optimization problem. The solution is presented in two computation models, centralized and a fully distributed approximation of the centralized model. Our simulation results show that using the fully distributed model, resource constrained sensor nodes can collectively solve a large non-linear optimization problem that none of the nodes can solve individually. This approach results in significant savings in computation and communication, that allows fine-grained localization to run on a low cost sensor node we have developed.

Energy-aware routing in cluster-based sensor networks

Abstract: There has been a growing interest in the applications of sensor networks. Since sensors are generally constrained in on-board energy supply, efficient management of the network is crucial in extending the life of the sensor. We present a novel approach for energy-aware and context-aware routing of sensor data. The approach calls for network clustering and assigns a less-energy-constrained gateway node that acts as a centralized network manager. Based on energy usage at every sensor node and changes in the mission and the environment, the gateway sets routes for sensor data, monitors latency throughout the cluster, and arbitrates medium access among sensors. Simulation results demonstrate that our approach can achieve substantial energy saving.

Source localization and beamforming

Abstract: Distributed sensor networks have been proposed for a wide range of applications. The main purpose of a sensor network is to monitor an area, including detecting, identifying, localizing, and tracking one or more objects of interest. These networks may be used by the military in surveillance, reconnaissance, and combat scenarios or around the perimeter of a manufacturing plant for intrusion detection. In other applications such as hearing aids and multimedia, microphone networks are capable of enhancing audio signals under noisy conditions for improved intelligibility, recognition, and cuing for camera aiming. Previous developments in integrated circuit technology have allowed the construction of low-cost miniature sensor nodes with signal processing and wireless communication capabilities. These technological advances not only open up many possibilities but also introduce challenging issues for the collaborative processing of wideband acoustic and seismic signals for source localization and beamforming in an energy-constrained distributed sensor network. The purpose of this article is to provide an overview of these issues.

PEAS: a robust energy conserving protocol for long-lived sensor networks

Abstract: Small, inexpensive sensors with limited memory, computing power and short battery lifetimes are turning into reality. Due to adverse conditions such as high noise levels, extreme humidity or temperatures, or even destructions from unfriendly entities, sensor node failures may become norms rather than exceptions in real environments. To be practical, sensor networks must last for much longer times than that of individual nodes, and have yet to be robust against potentially frequent node failures. This paper presents the design of PEAS, a simple protocol that can build a long-lived sensor network and maintain robust operations using large quantities of economical, short-lived sensor nodes. PEAS extends system functioning time by keeping only a necessary set of sensors working and putting the rest into sleep mode. Sleeping ones wake up now and then, probing the local environment and replacing failed ones. The sleeping periods are self-adjusted dynamically, so as to keep the sensors' wakeup rate roughly constant, thus adapting to high node densities.

A directionality based location discovery scheme for wireless sensor networks

Abstract: A sensor network is a large ad hoc network of densely distributed sensors that are equipped with low power wireless transceivers. Such networks can be applied for cooperative signal detection, monitoring, and tracking, and are especially useful for applications in remote or hazardous locations. This paper addresses the problem of location discovery at the sensor nodes, which is one of the central design challenges in sensor networks. We present a new method by which a sensor node can determine its location by listening to wireless transmissions from three or more fixed beacon nodes. The proposed method is based on an angle-of-arrival estimation technique that does not increase the complexity or cost of construction of the sensor nodes. We present the performance of the proposed method obtained from computer simulations.

Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks

Abstract: The paper examines the performance as well as energy consumption Issues of a wireless sensor network providing periodic data from a sensing field to a remote receiver. The sensors are assumed to be randomly deployed. We distinguish between two types of sensor organizations, one with a single layer of identical sensors (homogeneous) and one with an additional overlay of fewer but more powerful sensors (heterogeneous). We formulate the energy consumption and study their estimated lifetime based on a clustering mechanism with varying parameters related to the sensing field, e.g., size, and distance. We quantify the optimal number of clusters based on our model and show how to allocate energy between different layers.

Optimal Energy Aware Clustering in Sensor Networks

Abstract: Sensor networks is among the fastest growing technologies that have the potential of changing our lives drastically. These collaborative, dynamic and distributed computing and communicating systems will be self organizing. They will have capabilities of distributing a task among themselves for efficient computation. There are many challenges in implementation of such systems: energy dissipation and clustering being one of them. In order to maintain a certain degree of service quality and a reasonable system lifetime, energy needs to be optimized at every stage of system operation. Sensor node clustering is another very important optimization problem. Nodes that are clustered together will easily be able to communicate with each other. Considering energy as an optimization parameter while clustering is imperative. In this paper we study the theoretical aspects of the clustering problem in sensor networks with application to energy optimization. We illustrate an optimal algorithm for clustering the sensor nodes such that each cluster (which has a master) is balanced and the total distance between sensor nodes and master nodes is minimized. Balancing the clusters is needed for evenly distributing the load on all master nodes. Minimizing the total distance helps in reducing the communication overhead and hence the energy dissipation. This problem (which we call balanced k-clustering) is modeled as a mincost flow problem which can be solved optimally using existing techniques.

Maximum lifetime data gathering and aggregation in wireless sensor networks

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Energy-efficient DSPs for wireless sensor networks

Abstract: There are many new challenges to be faced in implementing signal processing algorithms and designing energy-efficient DSPs for microsensor networks. We study system partitioning of computation to improve the energy efficiency of a wireless sensor networking application. We explore system partitioning between the sensor cluster and the base station, employing computation-communication tradeoffs to reduce energy dissipation. Also we show that system partitioning of computation within the cluster can also improve the energy efficiency by using dynamic voltage scaling (DVS).

Efficient Distribution of Key Chain Commitments for Broadcast Authentication in Distributed Sensor Networks

Abstract: Broadcast authentication is a fundamental security service in distributed sensor networks. A scheme named $\mu$TESLA has been proposed for efficient broadcast authentication in such networks. However, $\mu$TESLA requires initial distribution of certain information based on unicast between the base station and each sensor node before the actual authentication of broadcast messages. Due to the limited bandwidth in wireless sensor networks, this initial unicast-based distribution severely limits the application of $\mu$TESLA in large sensor networks. This paper presents a novel technique to replace the unicast-based initialization with a broadcast-based one. As a result, $\mu$TESLA can be used in a sensor network with a large amount of sensors, as long as the message from the base station can reach these sensor nodes. This paper further explores several techniques that improve the performance, the robustness, as well as the security of the proposed method. The resulting protocol satisfies several nice properties, including low overhead, tolerance of message loss, scalability to large networks, and resistance to replay attacks as well as some known Denial of Service (DOS) attacks.

Wireless Sensor Networks with Energy Efficient Organization

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend the operational time. One important class of wireless sensor applications of deployment of large number of sensors in an area for environmental monitoring. The data collected by the sensors is sent to a central node for processing. In this paper we propose an efficient method to achieve energy savings by organizing the sensor nodes into a maximum number of disjoint dominating sets (DDS) which are activated successively. Only the sensors from the active set are responsible for monitoring the target area and for disseminating the collected data. All other nodes are into a sleep mode, characterized by a low energy consumption. We define the maximum disjoint dominating sets problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

An autonomous 16 mm/sup 3/ solar-powered node for distributed wireless sensor networks

Abstract: A 16 mm/sup 3/ autonomous solar-powered sensor node with bidirectional optical communication for distributed sensor networks has been demonstrated. The device digitizes integrated sensor signals and transmits/receives data over a free-space optical link. The system consists of three die - a 0.25 /spl mu/m CMOS ASIC, a 2.6 mm/sup 2/ SOI solar cell array, and a micromachined four-quadrant corner-cube retroreflector (CCR), allowing it to be used in a one-to-many network configuration. The CMOS ASIC includes a photosensor integrated 3 MHz oscillator, 69 pJ/bit optical receiver and 31 pJ/sample ADC.

Residual energy scan for monitoring sensor networks

Abstract: It is important to have continuously updated information about network resources and application activities in a wireless sensor network after it is deployed in an unpredictable environment. Such information can help notify users of resource depletion or abnormal activities. However, constrained by the low user-to-node ratio, limited energy and bandwidth resources, it is infeasible to extract the state of each individual node. In this paper, we propose an approach to constructing abstracted scans of sensor network health by applying in-network aggregation of network state. Specifically, we design a residual energy scan which approximately depicts the remaining energy distribution within a sensor network. Simulations show that our approach has good scalability and energy-efficiency characteristics, compared to continuously extracting the residual energy level individually from each node.

A wireless embedded sensor architecture for system-level optimization

Abstract: Emerging low power, embedded, wireless sensor devices are useful for wide range of applications, yet have very limited processing, storage, and especially energy resources. Thus, a key design challenge is to support application-specific optimizations in a highly flexible manner. Power consumption and capabilities of the radio communication layer are the dominant factors in overall system performance. This paper presents a wireless sensor node architecture to achieve high communication bandwidth with the flexibility to efficiently implement novel communication protocols. The architecture is instantiated in an operational design using commercial microcontroller and radio technology. Its ability to optimize system performance by using unconventional protocols is demonstrated by four case studies involving power management, synchronization, localization, and wake-up.

Residual Energy Scans for Monitoring Wireless Sensor Networks

Abstract: It is important to have continuously updated information about network resources and application activities in a wireless sensor network after it is deployed in an unpredictable environment. Such information can help notify users of resource depletion or abnormal activities. However, constrained by the low user-to-node ratio, limited energy and bandwidth resources, it is infeasible to extract state of each individual node. In this paper, we propose an approach to construct abstracted scans of sensor network health by applying in-network aggregation of network state. Specifically, we design a residual energy scan which approximately depicts the remaining energy distribution within a sensor network. Simulations show that our approach has good scalability and energy-efficiency characteristics, compared to continuously extracting the residual energy level individually from each node.

Low-latency multi-hop ad hoc wireless network

Abstract: A multi-radio sensor node is provided that includes two or more communication devices. The communication devices include radio frequency (RF) devices like radios. Each communication device supports simultaneous communications among multi-radio sensor nodes of respective independent network clusters. A network structure is provided that includes two or more local network clusters. Each local network cluster includes numerous multi-radio sensor nodes. Each communication device of a multi-radio sensor node supports communication among the multi-radio sensor nodes of a different one of the local network clusters so that simultaneous communications are supported among the multi-radio sensor nodes of the local network clusters. The multi-radio sensor nodes of the local network clusters determine their locations relative to the other multi-radio sensor nodes of the independent network clusters with which they communicate. The location determination includes performing timing synchronization via synchronization signals communicated among the local network clusters, and acoustic signaling.

Design of a Wireless Sensor Network for Long-term, In-Situ Monitoring of an Aqueous Environment

Abstract: An aqueous sensor network is described consisting of an array of sensor nodes that can be randomly distributed throughout a lake or drinking water reservoir. The data of an individual node is transmitted to the host node via acoustic waves using intermediate nodes as relays. Each node of the sensor network is a data router, and contains sensors capable of measuring environmental parameters of interest. Depending upon the required application, each sensor node can be equipped with different types of physical, biological or chemical sensors, allowing long-term, wide area, in situ multi-parameter monitoring. In this work the aqueous sensor network is described, with application to pH measurement using magnetoelastic sensors. Beyond ensuring drinking water safety, possible applications for the aqueous sensor network include advanced industrial process control, monitoring of aquatic biological communities, and monitoring of waste-stream effluents.

Scalable Session Key Construction Protocol for Wireless Sensor Networks

Abstract: The security of sensor network s is ever more important nowadays. In this paper we propose a new protocol BROSK to construct link dependent keys by broadcasting key negotiation messages. The link-dependent key will be negotiated in an ad-hoc scheme. Most of the proposed security protocols in sensor networks are based on point-to-point handshaking procedures to negotiate link -dependent keys, but this will influence the scalability of the network. The simulation shows that the scalability of BROSK is better than two other security protocols of sensor network, SPINS and SNAKE, and is reasonably secure. This new protocol consumes less energy by reducing the number of transmissions used for key negotiation among sensor nodes.

Wireless mesh network

Abstract: Method and apparatus for providing a wireless mesh network and network node are described. More particularly, a network having network node neighborhoods is described. A node comprises a multi-sectored antenna and a transceiver controller. Nodes are configured for installation without antenna pointing and without pre-coordination with the network. Software architecture for the node is also described.

A dual-space approach to tracking and sensor management in wireless sensor networks

Abstract: Wireless ad hoc sensor networks have the advantage of spanning a large geographical region and being able to collaboratively detect and track non-local spatio-temporal events. This paper presents a dual-space approach to event tracking and sensor resource management in sensor networks. The dual-space transformation maps a non-local phenomenon, e.g., the edge of a half-plane shadow, to a single point in the dual space, and maps locations of distributed sensor nodes to a set of lines that partitions the dual space. The detection problem becomes finding and tracking the cell that contains the point in the arrangement defined by these lines. This mechanism can be effectively used for power management of the sensor network - nodes that will not be immediately visited by an event can be turned off to save energy required for sensing, processing, and communication. The approach has been successfully demonstrated on a laboratory testbed built using the UC Berkeley motes sensors. An implemented application of detecting and tracking light shadow edges moving over a sensor field is described.

Making Sensor Networks Practical with Robots

Abstract: While wireless sensor networks offer new capabilities, there are a number of issues that hinder their deployment in practice. We argue that robotics can solve or greatly reduce the impact of many of these issues. Our hypothesis has been tested in the context of an autonomous system to care for houseplants that we have deployed in our office environment. This paper describes what we believe is needed to make sensor networks practical, the role robots can play in accomplishing this, and the results we have obtained in developing our application.

Sensing, tracking and reasoning with relations

Abstract: Suppose we have a set of sensor nodes spread over a geographical area. Assume that these nodes are able to perform processing as well as sensing and are additionally capable of communicating with each other by means of a wireless network. Though each node is an independent hardware device, they need to coordinate their sensing, computation and communication to acquire relevant information about their environment so as to accomplish some high-level task. The integration of processing makes such nodes more autonomous and the entire system, which we call a sensor net, becomes a novel type of sensing, processing, and communication engine. The sensor net architecture presented in this article starts from a high-level description of the mission or task to be accomplished and then commands individual nodes to sense and communicate in a manner that accomplishes the desired result with attention to minimizing the computational, communication, and sensing resources required. Much work remains to be done to refine and implement the relational sensing ideas presented here and validate their performance. We believe, however, that the potential pay-off for the relation-based sensing and tracking we have proposed can be large, both in terms of developing rich theories on the design and complexity of sensing algorithms, as well as in terms of the eventual impact of the deployed sensor systems.

Collaborative classification applications in sensor networks

Abstract: Distributed sensor networks are a significant technology nowadays. Inexpensive, smart devices with multiple sensors provide opportunities for instrumenting, monitoring and controlling targeting systems. Such sensor nodes have capability for acquiring and embedded-processing of variety of data forms. Collaborative signal processing and fusion algorithms are needed to aggregate the distributed data from among the nodes in the network, including possibly multiple modalities of data within a sensor node, to make decisions in a reliable and efficient manner. One of the important sensor network applications is target classification in battlefields. This paper presents improved moving vehicle target classification performance using data obtained from sensor networks with collaboration both across nodes and within a node in terms of multimodal fusion. Results show that a 50% relative improvement in classification error can be obtained using collaboration both in the case of single vehicle target and those involving multi-vehicle convoys.

Lifetime analysis of a sensor network with hybrid automata modelling

Abstract: In this paper, we focus on TinyOS, an event-based operating system for networked sensor motes. We show how to model TinyOS as a hybrid automata with HyTech and verify the correct operation of the system by using safety verification feature of HyTech. Since lifetime is an important metric for sensor nodes that are planned to be deployed once and unattended for long periods of time without maintenance, we perform power analysis of a sensor node by using trace generation feature of HyTech. Furthermore, we simulate a tree sensor network of TinyOS motes by using the programming language SHIFT to determine the lifetime of the network as a function of the distance from the central data collector.

Self-configuring localization systems

Abstract: Recent technological advances have fostered the emergence of small, low-power devices that integrate micro-sensing and actuation with on-board processing and wireless communications capabilities. Through distributed coordination, pervasive networks of micro-sensors and actuators are expected to revolutionize the ways in which we understand and construct complex physical systems. Fundamental to such coordination is localization, or the ability to establish spatial relationships among objects. In this dissertation, we address the challenges involved in localization for very large, ad hoc deployed sensor networks. Although several localization technologies have been proposed in the past few years, none Currently satisfies all our requirements because no single localization system is simultaneously scalable, ad hoc deployable and accommodating of the hardware constraints of very small devices. Our thesis is that all these issues can be solved simultaneously by a self-configuring localization system that autonomously adapts to its environmental dynamics. Our approach is based on localized adaptive algorithms that self-configure to exploit both the local processing on each sensor node, as well as the redundancy across densely-deployed sensor nodes. First, to accommodate device constraints, we adopt a low cost, hardware-independent localization approach for very small devices that leverages the existing radio (RF) communications capabilities of such devices and does not require any other sensors. Second, to scale to very large sensor networks, we develop a decentralized, self-localization methodology for devices. Instead of relying on a central server to compute their positions, devices themselves perform a localized location computation based on radio connectivity constraints to a small number of nearby beacons (nodes with known positions), obtained by listening to radio broadcast advertisements of beacons. Third, we need to ensure a uniform localization granularity in dynamic, unpredictable environments with numerous radio propagation vagaries. One solution to this problem is to extensively instrument and model the environment, a priori. Unfortunately, this approach does not scale well. Instead, we advocate and develop a self-configuring mechanism in which beacons themselves measure and adapt to their environment and availability of neighboring beacons. Finally, we quantitatively analyze the impact of beacon density on localization. We show that proximity based localization using only local information saturates at a threshold beacon density μthresh. We develop various self-configuring algorithms for incremental beacon placement for sparse beacon deployment. For dense beacon deployment, it is desirable to keep the operational beacon density close to μthresh to reduce the probability of self-interference amongst beacons and to conserve energy. We develop a parameterized algorithm (tunable according to radio parameters) to adjust the duty cycle of beacons based on the availability of other beacons in the neighborhood to realize a low operational density. These techniques form the bases of our self-configuring localization system. We have implemented it as a user-level library on two test-beds, Radiometrix RPC-418 radios, and motes with RFM radios. We evaluate and demonstrate the effectiveness of our localization system in terms of the performance of the basic localization algorithms, as well as the beacon placement techniques to adapt it to noisy environments.