Showing papers on "Sensor node published in 2003"

LEAP: efficient security mechanisms for large-scale distributed sensor networks

Abstract: In this paper, we describe LEAP (Localized Encryption and Authentication Protocol), a key management protocol for sensor networks that is designed to support in-network processing, while at the same time restricting the security impact of a node compromise to the immediate network neighborhood of the compromised node. The design of the protocol is motivated by the observation that different types of messages exchanged between sensor nodes have different security requirements, and that a single keying mechanism is not suitable for meeting these different security requirements. LEAP supports the establishment of four types of keys for each sensor node -- an individual key shared with the base station, a pairwise key shared with another sensor node, a cluster key shared with multiple neighboring nodes, and a group key that is shared by all the nodes in the network. The protocol used for establishing and updating these keys is communication- and energy-efficient, and minimizes the involvement of the base station. LEAP also includes an efficient protocol for inter-node traffic authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding in-network processing and passive participation. We analyze the performance and the security of our scheme under various attack models and show our schemes are very efficient in defending against many attacks.

Energy efficient schemes for wireless sensor networks with multiple mobile base stations

Abstract: One of the main design issues for a sensor network is conservation of the energy available at each sensor node We propose to deploy multiple, mobile base stations to prolong the lifetime of the sensor network We split the lifetime of the sensor network into equal periods of time known as rounds Base stations are relocated at the start of a round Our method uses an integer linear program to determine new locations for the base stations and a flow-based routing protocol to ensure energy efficient routing during each round We propose four metrics and evaluate our solution using these metrics Based on the simulation results we show that employing multiple, mobile base stations in accordance with the solution given by our schemes would significantly increase the lifetime of the sensor network

Data-centric storage in sensornets with GHT, a geographic hash table

Abstract: Making effective use of the vast amounts of data gathered by large-scale sensor networks (sensornets) will require scalable, self-organizing, and energy-efficient data dissemination algorithms. For sensornets, where the content of the data is more important than the identity of the node that gathers them, researchers have found it useful to move away from the Internet's point-to-point communication abstraction and instead adopt abstractions that are more data-centric. This approach entails naming the data and using communication abstractions that refer to those names rather than to node network addresses [1,11]. Previous work on data-centric routing has shown it to be an energy-efficient data dissemination method for sensornets [12]. Herein, 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 first define DCS and predict analytically where it outperforms other data dissemination approaches. We then describe GHT, a Geographic Hash Table system for DCS on sensornets. GHT hashes keys into geographic coordinates, and stores a key-value pair at the sensor node geographically nearest the hash of its key. The system replicates stored data locally 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 we analytically predict, offers high data availability, and scales to large sensornet deployments, even when nodes fail or are mobile.

Fault-tolerant clustering of wireless sensor networks

Abstract: During the past few years distributed wireless sensor networks have been the focus of considerable research for both military and civil applications. Sensors are generally constrained in on-board energy supply therefore efficient management of the network is crucial to extend the life of the system. Sensors' energy cannot support long haul communication to reach a remote command site, thus they require multi-tier architecture to forward data. An efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high-energy node called a gateway as cluster-head. Failures are inevitable in sensor networks due to the inhospitable environment and unattended deployment. However, failures in higher level of hierarchy e.g. cluster-head cause more damage to the system because they also limit accessibility to the nodes that are under their supervision. In this paper we propose an efficient mechanism to recover sensors from a failed cluster. Our approach avoids a full-scale re-clustering and does not require deployment of redundant gateways.

Using predictable observer mobility for power efficient design of sensor networks

Abstract: In this paper, we explore a novel avenue of saving power in sensor networks based on predictable mobility of the observer (or data sink). Predictable mobility is a good model for public transportation vehicles (buses, shuttles and trains), which can act as mobile observers in wide area sensor networks. To understand the gains due to predictable mobility, we model the data collection process as a queuing system, where random arrivals model randomness in the spatial distribution of sensors. Using the queuing model, we analyze the success in data collection, and quantify the power consumption of the network. Even though the modeling is performed for a network which uses only single hop communication, we show that the power savings over a static sensor network are significant. Finally, we present a simple observer-driven communication protocol, which follows naturally from the problem formulation and can be used to achieve the predicted power savings.

Tracking a moving object with a binary sensor network

Abstract: In this paper we examine the role of very simple and noisy sensors for the tracking problem. We propose a binary sensor model, where each sensor's value is converted reliably to one bit of information only: whether the object is moving toward the sensor or away from the sensor. We show that a network of binary sensors has geometric properties that can be used to develop a solution for tracking with binary sensors and present resulting algorithms and simulation experiments. We develop a particle filtering style algorithm for target tracking using such minimalist sensors. We present an analysis of fundamental tracking limitation under this sensor model, and show how this limitation can be overcome through the use of a single bit of proximity information at each sensor node. Our extensive simulations show low error that decreases with sensor density.

Query Processing in Sensor Networks.

Abstract: Smart sensors are small wireless computing devices that sense information such as light and humidity at extremely high resolutions. A smart sensor query-processing architecture using database technology can facilitate deployment of sensor networks. Smart-sensor technology enables a broad range of ubiquitous computing applications. Their low cost, small size, and untethered nature lets them sense information at previously unobtainable resolutions. We discuss about query processing in sensor networks.

Survey on wireless sensor network devices

Abstract: Wireless sensor networks are networks of compact microsensors with wireless communication capability. These small devices are relatively cheap with the potential to be disseminated in large quantities. Emerging applications of data gathering range from the environmental to the military. As autonomous devices they can provide pervasive distributed and collaborative network of computer nodes. Architectural challenges are posed for designers such as computational power, energy consumption, energy sources, communication channels and sensing capabilities. Embedded Systems provide the computational platform for hardware and software components to interact with the environment and other nodes. This survey presents the current state-of-the-art for wireless sensor nodes, investigating and analyzing these challenges. We discuss the characteristics and requirements for a sensor node mainly processing, communications, power and sensing components. In this survey we present a comprehensive comparative study of sensor nodes platforms, energy management techniques, off-the-shelf microcontrollers, battery types and radio devices.

Connected sensor cover: self-organization of sensor networks for efficient query execution

Abstract: Spatial query execution is an essential functionality of a sensor network, where a query gathers sensor data within a specific geographic region. Redundancy within a sensor network can be exploited to reduce the communication cost incurred in execution of such queries. Any reduction in communication cost would result in an efficient use of the battery energy, which is very limited in sensors. One approach to reduce the communication cost of a query is to self-organize the network, in response to a query, into a topology that involves only a small subset of the sensors sufficient to process the query. The query is then executed using only the sensors in the constructed topology.In this article, we design and analyze algorithms for such self-organization of a sensor network to reduce energy consumption. In particular, we develop the notion of a connected sensor cover and design a centralized approximation algorithm that constructs a topology involving a near-optimal connected sensor cover. We prove that the size of the constructed topology is within an log n factor of the optimal size, where n is the network size. We also develop a distributed self-organization version of our algorithm, and propose several optimizations to reduce the communication overhead of the algorithm. Finally, we evaluate the distributed algorithm using simulations and show that our approach results in significant communication cost reduction.

A Wireless Sensor Network.

Abstract: The Wireless sensor network play a vital role in collecting a Real – Time data, monitoring environmental conditions based on technology adoption. These sensor network is the combination of sensing, computation, and communication through a single tiny device. Here many tiny nodes assemble and configure themselves. It also controls actuators that extend control from cyberspace into the physical world. Here the sensor nodes communicate with the local peers rather than the high – power control tower or base station. Instead, of relying on a predeployed infrastructure, each individual sensor or actuator become part of the overall infrastructure. Here we have three hardware platforms that addresses the needs of wireless sensor netwoks. The operating system here uses an event based execution to support concurrency. The platform serves as a baseline and does not contain any hardware accelerators. . First platform serves as a baseline and it produces Operating system concepts for refining concurrency mechanisms. The second node validates the architectural designs and improve the communicational rates. The third node represents the full realization of the general architecture. Keywords— node, platform, concurrency.

A Self-Localization Method for Wireless Sensor Networks

Abstract: We consider the problem of locating and orienting a network of unattended sensor nodes that have been deployed in a scene at unknown locations and orientation angles. This self-calibration problem is solved by placing a number of source signals, also with unknown locations, in the scene. Each source in turn emits a calibration signal, and a subset of sensor nodes in the network measures the time of arrival and direction of arrival (with respect to the sensor node's local orientation coordinates) of the signal emitted from that source. From these measurements we compute the sensor node locations and orientations, along with any unknown source locations and emission times. We develop necessary conditions for solving the self-calibration problem and provide a maximum likelihood solution and corresponding location error estimate. We also compute the Cramer-Rao bound of the sensor node location and orientation estimates, which provides a lower bound on calibration accuracy. Results using both synthetic data and field measurements are presented.

Design and implementation of a framework for efficient and programmable sensor networks

Abstract: Wireless ad hoc sensor networks have emerged as one of the key growth areas for wireless networking and computing technologies. So far these networks/systems have been designed with static and custom architectures for specific tasks, thus providing inflexible operation and interaction capabilities. Our vision is to create sensor networks that are open to multiple transient users with dynamic needs. Working towards this vision, we propose a framework to define and support lightweight and mobile control scripts that allow the computation, communication, and sensing resources at the sensor nodes to be efficiently harnessed in an application-specific fashion. The replication/migration of such scripts in several sensor nodes allows the dynamic deployment of distributed algorithms into the network. Our framework, SensorWare, defines, creates, dynamically deploys, and supports such scripts. Our implementation of SensorWare occupies less than 180Kbytes of code memory and thus easily fits into several sensor node platforms. Extensive delay measurements on our iPAQ-based prototype sensor node platform reveal the small overhead of SensorWare to the algorithms (less than 0.3msec in most high-level operations). In return the programmer of the sensor network receives compactness of code, abstraction services for all of the node's modules, and in-built multi-user support. SensorWare with its features apart from making dynamic programming possible it also makes it easy and efficient without restricting the expressiveness of the algorithms.

A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks

Abstract: We propose a novel approach to reducing energy consumption in sensor networks using a distributed adaptive signal processing framework and efficient algorithm. While the topic of energy-aware routing to alleviate energy consumption in sensor networks has received attention recently (C. Toh, 2001; R. Shah et al., 2002), in this paper, we propose an orthogonal approach to previous methods. Specifically, we propose a distributed way of continuously exploiting existing correlations in sensor data based on adaptive signal processing and distributed source coding principles. Our approach enables sensor nodes to blindly compress their readings with respect to one another without the need for explicit and energy-expensive intersensor communication to effect this compression. Furthermore, the distributed algorithm used by each sensor node is extremely low in complexity and easy to implement (i.e., one modulo operation), while an adaptive filtering framework is used at the data gathering unit to continuously learn the relevant correlation structures in the sensor data. Our simulations show the power of our proposed algorithms, revealing their potential to effect significant energy savings (from 10%-65%) for typical sensor data corresponding to a multitude of sensor modalities.

Wireless Sensor Network Designs

Abstract: Preface About the Author 1. Networked Embedded Systems 2. Smart Sensor Networks 3. Power-Aware Wireless Sensor Networks 4. Routing in Wireless Sensor Networks 5. Distributed Sensor Networks 6. Clustering Techniques in Wireless Sensor Networks 7. Security Protocols for Wireless Sensor Networks 8. Operating Systems for Embedded Applications 9. Network Support for Embedded Applications 10. Applications of Wireless Sensor Networks References Index

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. In this paper we study node localization, a component technology that would enhance the effectiveness and capabilities of this new class of networks. The n-hop multilateration primitive 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-quality tradeoffs for target tracking in wireless sensor networks

Abstract: We study the tradeoffs involved in the energy-efficient localization and tracking of mobile targets by a wireless sensor network. Our work focuses on building a framework for evaluating the fundamental performance of tracking strategies in which only a small portion of the network is activated at any point in time. We first compare naive network operation with random activation and selective activation. In these strategies the gains in energy-savings come at the expense of increased uncertainty in the location of the target, resulting in reduced quality of tracking. We show that selective activation with a good prediction algorithm is a dominating strategy that can yield orders-of-magnitude energy savings with negligible difference in tracking quality. We then consider duty-cycled activation and show that it offers a flexible and dynamic tradeoff between energy expenditure and tracking error when used in conjunction with selective activation.

Mobile-agent-based collaborative signal and information processing in sensor networks

Abstract: In this paper, we develop an energy-efficient, fault-tolerant approach for collaborative signal and information processing (CSIP) among multiple sensor nodes using a mobile-agent-based computing model. In this model, instead of each sensor node sending local information to a processing center for integration, as is typical in client/server-based computing, the integration code is moved to the sensor nodes through mobile agents. The energy efficiency objective and the fault tolerance objective always conflict with each other and present unique challenge to the design of CSIP algorithms. In general, energy-efficient approaches try to limit the redundancy in the algorithm so that minimum amount of energy is required for fulfilling a certain task. On the other hand, redundancy is needed for providing fault tolerance since sensors might be faulty, malfunctioning, or even malicious. A balance has to be struck between these two objectives. We discuss the potential of mobile-agent-based collaborative processing in providing progressive accuracy while maintaining certain degree of fault tolerance. We evaluate its performance compared to the client/server-based collaboration from perspectives of energy consumption and execution time through both simulation and analytical study. Finally, we take collaborative target classification as an application example to show the effectiveness of the proposed approach.

A performance evaluation of intrusion-tolerant routing in wireless sensor networks

Abstract: This paper evaluates the performance of INSENS, an INtrusion-tolerant routing protocol for wireless SEnsor Networks. Security in sensor networks is important in battlefield monitoring and home security applications to prevent intruders from eavesdropping, from tampering with sensor data, and from launching denial-of-service (DOS) attacks against the entire network. The resilience of INSENS's multipath performance against various forms of communication-based attacks by intruders is evaluated in simulation. Within the context of INSENS, the paper evaluates implementations on the motes of the RC5 and AES encryption standards, an RC5-based scheme to generate message authentication codes (MACs), and an RC5-based generation of one-way sequence numbers.

An evaluation of multi-resolution storage for sensor networks

Abstract: Wireless sensor networks enable dense sensing of the environment, offering unprecedented opportunities for observing the physical world. Centralized data collection and analysis adversely impact sensor node lifetime. Previous sensor network research has, therefore, focused on in network aggregation and query processing, but has done so for applications where the features of interest are known a priori. When features are not known a priori, as is the case with many scientific applications in dense sensor arrays, efficient support for multi-resolution storage and iterative, drill-down queries is essential.Our system demonstrates the use of in-network wavelet-based summarization and progressive aging of summaries in support of long-term querying in storage and communication-constrained networks. We evaluate the performance of our linux implementation and show that it achieves: (a) low communication overhead for multi-resolution summarization, (b) highly efficient drill-down search over such summaries, and (c) efficient use of network storage capacity through load-balancing and progressive aging of summaries.

Boundary estimation in sensor networks: theory and methods

Abstract: Sensor networks have emerged as a fundamentally new tool for monitoring spatially distributed phenomena. This paper investigates a strategy by which sensor nodes detect and estimate non-localized phenomena such as "boundaries" and "edges"(e.g., temperature gradients, variations in illumination or contamination levels). A general class of boundaries, with mild regularity assumptions, is considered, and theoretical bounds on the achievable performance of sensor network based boundary estimation are established. A hierarchical boundary estimation algorithm is proposed that achieves a near-optimal balance between mean-squared error and energy consumption.

Maximum mutual information principle for dynamic sensor query problems

Abstract: In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and show that the principle of mutual information maximization follows naturally from the expected uncertainty minimization criterion in a Bayesian filtering framework. This equivalence results in a computationally feasible approach to state estimation in sensor networks. We illustrate the application of the proposed dynamic sensor selection method to both discrete and linear Gaussian models for distributed tracking as well as to stationary target localization using acoustic arrays.

Adaptive and decentralized operator placement for in-network query processing

Abstract: In-network query processing is critical for reducing network traffic when accessing and manipulating sensor data It requires placing a tree of query operators such as filters and aggregations but also correlations onto sensor nodes in order to minimize the amount of data transmitted in the network In this paper, we show that this problem is a variant of the task assignment problem for which polynomial algorithms have been developed These algorithms are however centralized and cannot be used in a sensor network We describe an adaptive and decentralized algorithm that progressively refines the placement of operators by walking through neighbor nodes Simulation results illustrate the potential benefits of our approach They also show that our placement strategy can achieve near optimal placement onto various graph topologies despite the risks of local minima

Wireless sensor placement for reliable and efficient data collection

Abstract: Sensors can be paired with radio units and deployed to form a wireless ad-hoc sensor network. Actual deployments must consider the coverage that can be achieved with a given number of sensors: this coverage varies with the range of the radios and the maximum allowable distance between any point in the area and the nearest sensor. Deployments must also preserve connectivity in spite of possible failure or energy depletion in a subset of the units. This paper presents and analyzes a variety of regular deployment topologies, including circular and star deployments as well as deployments in square, triangular, and hexagonal grids.

Critical density thresholds for coverage in wireless sensor networks

Abstract: Sensor networks are deployed to monitor the physical world and to provide relevant data to the users. An important question in such networks is to estimate the number of sensors required to achieve complete coverage of the desired region. The number of sensors required would depend upon the physical characteristics of the individual sensors as well as the nature of the target. In this paper, we address the problem of finding the critical density of sensors for complete coverage. We use an exposure-based model to find the number of sensors required to cover an area for given sensor and target characteristics. The accuracy of the results is established via simulations.

Performance evaluation of load-balanced clustering of wireless sensor networks

Abstract: Wireless sensor networks have received increasing attention in recent few years. In many military and civil applications of sensor networks, sensors are constrained in onboard energy supply and are left unattended. Energy, size and cost constraints of such sensors limit the communication range. Therefore, multi-hop wireless connectivity is required to forward data on their behalf to a remote command site. In this paper, we investigate the performance of an algorithm to network these sensors into well defined clusters with less-energy-constrained gateway nodes acting as clusterheads as well as to balance the load among these gateways. Load balanced clustering increases the system stability and improves the communication between different nodes in the system. To evaluate the efficiency of this approach, we studied the performance of sensor networks by applying various different routing protocols. Simulation results shows that irrespective of the routing protocol used, this approach improves the lifetime of the system.

Location tracking in a wireless sensor network by mobile agents and its data fusion strategies

Abstract: The wireless sensor network is an emerging technology that may greatly facilitate human life by providing ubiquitous sensing, computing, and communication capability, through which people can more closely interact with the environment wherever he/she goes. To be context-aware, one of the central issues in sensor networks is location tracking, whose goal is to monitor the roaming path of a moving object. While similar to the location-update problem in PCS networks, this problem is more challenging in two senses: (1) there are no central control mechanism and backbone network in such environment, and (2) the wireless communication bandwidth is very limited. In this paper, we propose a novel protocol based on the mobile agent paradigm. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object. The agent is mobile since it will choose the sensor closest to the object to stay. The agent may invite some nearby slave sensors to cooperatively position the object and inhibit other irrelevant (i.e., farther) sensors from tracking the object.As a result, the communication and sensing overheads are greatly reduced. Our prototyping of the location-tracking mobile agent based on IEEE 802.11b NICs and our experimental experiences are also reported.

Topology-aware placement and role assignment for energy-efficient information gathering in sensor networks

Abstract: Consider a network of energy-constrained wireless nodes, capable of sensing and communicating, to be deployed over an area to be monitored. There is a set of points or regions of interest in that are, each of which must be sensed (covered) by at least one node. The nodes are allowed to perform in-network data aggregation. As a node may or may not cover one or more points/regions of interest, we allow nodes to assume two roles sensor (nodes that sense their vicinity and generate data packets) and relay (nodes that only aggregate and transmit data packets). We consider the problem of placing nodes in the monitoring area and assigning roles to them such that the system lifetime is maximized, while ensuring that each point/region of interest is covered by at least one sensor node. This is the maximum lifetime sensor deployment problem with coverage constraints. The paper presents a novel algorithm to solve this problem and provides experimental results to demonstrate the effectiveness of the proposed algorithm.