Showing papers on "Sensor node published in 2009"

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 802.11 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 802.11-like MAC consumes 2–6 times more energy than S-MAC for traffic load with messages sent every 1–10s.

Energy conservation in wireless sensor networks: A survey

Abstract: In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

Compressive data gathering for large-scale wireless sensor networks

Abstract: This paper presents the first complete design to apply compressive sampling theory to sensor data gathering for large-scale wireless sensor networks. The successful scheme developed in this research is expected to offer fresh frame of mind for research in both compressive sampling applications and large-scale wireless sensor networks. We consider the scenario in which a large number of sensor nodes are densely deployed and sensor readings are spatially correlated. The proposed compressive data gathering is able to reduce global scale communication cost without introducing intensive computation or complicated transmission control. The load balancing characteristic is capable of extending the lifetime of the entire sensor network as well as individual sensors. Furthermore, the proposed scheme can cope with abnormal sensor readings gracefully. We also carry out the analysis of the network capacity of the proposed compressive data gathering and validate the analysis through ns-2 simulations. More importantly, this novel compressive data gathering has been tested on real sensor data and the results show the efficiency and robustness of the proposed scheme.

Distributed Consensus Filtering in Sensor Networks

Abstract: In this paper, a new filtering problem for sensor networks is investigated. A new type of distributed consensus filters is designed, where each sensor can communicate with the neighboring sensors, and filtering can be performed in a distributed way. In the pinning control approach, only a small fraction of sensors need to measure the target information, with which the whole network can be controlled. Furthermore, pinning observers are designed in the case that the sensor can only observe partial target information. Simulation results are given to verify the designed distributed consensus filters.

A survey on localization for mobile wireless sensor networks

Abstract: Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

Mercury: a wearable sensor network platform for high-fidelity motion analysis

Abstract: This paper describes Mercury, a wearable, wireless sensor platform for motion analysis of patients being treated for neuromotor disorders, such as Parkinson's Disease, epilepsy, and stroke. In contrast to previous systems intended for short-term use in a laboratory, Mercury is designed to support long-term, longitudinal data collection on patients in hospital and home settings. Patients wear up to 8 wireless nodes equipped with sensors for monitoring movement and physiological conditions. Individual nodes compute high-level features from the raw signals, and a base station performs data collection and tunes sensor node parameters based on energy availability, radio link quality, and application specific policies.Mercury is designed to overcome the core challenges of long battery lifetime and high data fidelity for long-term studies where patients wear sensors continuously 12 to 18 hours a day. This requires tuning sensor operation and data transfers based on energy consumption of each node and processing data under severe computational constraints. Mercury provides a high-level programming interface that allows a clinical researcher to rapidly build up different policies for driving data collection and tuning sensor lifetime. We present the Mercury architecture and a detailed evaluation of two applications of the system for monitoring patients with Parkinson's Disease and epilepsy.

An energy-aware routing protocol in wireless sensor networks

Abstract: The most important issue that must be solved in designing a data gathering algorithm for wireless sensor networks (WSNS) is how to save sensor node energy while meeting the needs of applications/users. In this paper, we propose a novel energy-aware routing protocol (EAP) for a long-lived sensor network. EAP achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all the nodes. EAP introduces a new clustering parameter for cluster head election, which can better handle the heterogeneous energy capacities. Furthermore, it also introduces a simple but efficient approach, namely, intra-cluster coverage to cope with the area coverage problem. We use a simple temperature sensing application to evaluate the performance of EAP and results show that our protocol significantly outperforms LEACH and HEED in terms of network lifetime and the amount of data gathered.

Wireless Sensor Networks: A Survey

Abstract: Wireless Sensor Networks (WSN), an element of pervasive computing, are presently being used on a large scale to monitor real-time environmental status. However these sensors operate under extreme energy constraints and are designed by keeping an application in mind. Designing a new wireless sensor node is extremely challenging task and involves assessing a number of different parameters required by the target application, which includes range, antenna type, target technology, components, memory, storage, power, life time, security, computational capability, communication technology, power, size, programming interface and applications. This paper analyses commercially (and research prototypes) available wireless sensor nodes based on these parameters and outlines research directions in this area.

Non-line-of-sight underwater optical wireless communication network.

Abstract: The growing need for ocean observation systems has stimulated considerable interest within the research community in advancing the enabling technologies of underwater wireless communication and underwater sensor networks. Sensors and ad hoc sensor networks are the emerging tools for performing extensive data-gathering operations on land, and solutions in the subsea setting are being sought. Efficient communication from the sensors and within the network is critical, but the underwater environment is extremely challenging. Addressing the special features of underwater wireless communication in sensor networks, we propose a novel non-line-of-sight network concept in which the link is implemented by means of back-reflection of the propagating optic signal at the ocean-air interface and derive a mathematical model of the channel. Point-to-multipoint links can be achieved in an energy efficient manner and broadcast broadband communications, such as video transmissions, can be executed. We show achievable bit error rates as a function of sensor node separation and demonstrate the feasibility of this concept using state-of-the-art silicon photomultiplier detectors.

Effects of Denial-of-Sleep Attacks on Wireless Sensor Network MAC Protocols

Abstract: Wireless platforms are becoming less expensive and more powerful, enabling the promise of widespread use for everything from health monitoring to military sensing. Like other networks, sensor networks are vulnerable to malicious attack. However, the hardware simplicity of these devices makes defense mechanisms designed for traditional networks infeasible. This paper explores the denial-of-sleep attack, in which a sensor node's power supply is targeted. Attacks of this type can reduce the sensor lifetime from years to days and have a devastating impact on a sensor network. This paper classifies sensor network denial-of-sleep attacks in terms of an attacker's knowledge of the medium access control (MAC) layer protocol and ability to bypass authentication and encryption protocols. Attacks from each classification are then modeled to show the impacts on four sensor network MAC protocols, i.e., Sensor MAC (S-MAC), Timeout MAC (T-MAC), Berkeley MAC (B-MAC), and Gateway MAC (G-MAC). Implementations of selected attacks on S-MAC, T-MAC, and B-MAC are described and analyzed in detail to validate their effectiveness and analyze their efficiency. Our analysis shows that the most efficient attack on S-MAC can keep a cluster of nodes awake 100% of the time by an attacker that sleeps 99% of the time. Attacks on T-MAC can keep victims awake 100% of the time while the attacker sleeps 92% of the time. A framework for preventing denial-of-sleep attacks in sensor networks is also introduced. With full protocol knowledge and an ability to penetrate link-layer encryption, all wireless sensor network MAC protocols are susceptible to a full domination attack, which reduces the network lifetime to the minimum possible by maximizing the power consumption of the nodes' radio subsystem. Even without the ability to penetrate encryption, subtle attacks can be launched, which reduce the network lifetime by orders of magnitude. If sensor networks are to meet current expectations, they must be robust in the face of network attacks to include denial-of-sleep.

Efficient Convex Relaxation Methods for Robust Target Localization by a Sensor Network Using Time Differences of Arrivals

Abstract: We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem. We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.

An estimation of sensor energy consumption

Abstract: A comprehensive energy model for wireless sensor networks is provided by considering seven key energy consumption sources some of which are ignored by currently available models. We demonstrate the importance of using such a comprehensive model by comparing it to other existing energy models in terms of the lifetime of a sensor node. We use our model to evaluate energy consumption and node lifetime for a sensor network with fixed configuration and we validate this evaluation by simulation. We show that existing energy models over-estimate life expectancy of a sensor node by 30-58% and also yield an "optimised" number of clusters which is too large. We further make the following two observations: 1) the optimal number of clusters increases with the increase of free space fading energy, 2) for sensor networks with 100 sensors over an area of 10 4 -10 5 (m 2 ), finding the optimal number of clusters becomes less important when free space fading energy is very low (less than 1670 pJ/bit/m 2 ), while for larger networks, on the other hand, cluster optimization is still important even if free space fading energy is low. Guidelines for efficient and reliable sensor network design as well as extension to a sensor network with rotating cluster heads are provided.

Transient-based identification of wireless sensor nodes

Abstract: Identification of wireless sensor nodes based on the characteristics of their radio transmissions can provide an additional layer of security in all-wireless multi-hop sensor networks. Reliable identification can be means for the detection and/or prevention of wormhole, Sybil and replication attacks, and can complement cryptographic message authentication protocols. In this paper, we investigate the feasibility of transient-based identification of CC2420 wireless sensor nodes. We propose a new technique for transient-based identification and show that it enables reliable and accurate sensor node recognition with an Equal Error Rate as low as 0.0024 (0.24%). We investigate the performance of our technique in terms of parameters such as distance, antenna polarization and voltage and analyze how these parameters affect the recognition accuracy. Finally, we study the feasibility of certain types of impersonation attacks on the proposed technique.

Wireless electricity for electronic devices

Abstract: A system and method for the wirelessly charging electronic devices. For example, the electronic device may be a pulse oximeter with a wireless sensor. The wireless sensor may include a sensor power source adapted to power the wireless sensor. The wireless sensor may also include a sensor charging device adapted to receive a wireless electromagnetic charging signal and charge the power source via the wireless electromagnetic charging signal.

Clock Synchronization in Wireless Sensor Networks: An Overview

Abstract: The development of tiny, low-cost, low-power and multifunctional sensor nodes equipped with sensing, data processing, and communicating components, have been made possible by the recent advances in micro-electro-mechanical systems (MEMS) technology. Wireless sensor networks (WSNs) assume a collection of such tiny sensing devices connected wirelessly and which are used to observe and monitor a variety of phenomena in the real physical world. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization protocols for WSNs.

Energy-efficient link-layer jamming attacks against wireless sensor network MAC protocols

Abstract: A typical wireless sensor node has little protection against radio jamming. The situation becomes worse if energy-efficient jamming can be achieved by exploiting knowledge of the data link layer. Encrypting the packets may help to prevent the jammer from taking actions based on the content of the packets, but the temporal arrangement of the packets induced by the nature of the protocol might unravel patterns that the jammer can take advantage of, even when the packets are encrypted.By looking at the packet interarrival times in three representative MAC protocols, S-MAC, LMAC, and B-MAC, we derive several jamming attacks that allow the jammer to jam S-MAC, LMAC, and B-MAC energy efficiently. The jamming attacks are based on realistic assumptions. The algorithms are described in detail and simulated. The effectiveness and efficiency of the attacks are examined. In addition, we validate our simulation model by comparing its results with measurements obtained from actual implementation on our sensor node prototypes. We show that it takes little effort to implement such effective jammers, making them a realistic threat.Careful analysis of other protocols belonging to the respective categories of S-MAC, LMAC, and B-MAC reveals that those protocols are, to some extent, also susceptible to our attacks. The result of this investigation provides new insights into the security considerations of MAC protocols.

Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

Abstract: Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. The challenge in using collaborative beamforming in WSNs is the uncertainty regarding the sensor node locations. However, the actual sensor node spatial distribution can be modeled by a properly selected probability density function (pdf). In this paper, we model the spatial distribution of sensor nodes in a cluster of WSN using Gaussian pdf. Gaussian pdf is more suitable in many WSN applications than, for example, uniform pdf which is commonly used for flat ad hoc networks. The average beampattern and its characteristics, the distribution of the beampattern level in the sidelobe region, and the distribution of the maximum sidelobe peak are derived using the theory of random arrays. We show that both the uniform and Gaussian sensor node deployments behave qualitatively in a similar way with respect to the beamwidths and sidelobe levels, while the Gaussian deployment gives wider mainlobe and has lower chance of large sidelobes.

EARQ: Energy Aware Routing for Real-Time and Reliable Communication in Wireless Industrial Sensor Networks

Abstract: Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

Distance measurement and error estimation scheme for RSSI based localization in Wireless Sensor Networks

Abstract: With the advent of Wireless Sensor Networks (WSN's) covering a whole gamut of applications which is getting broader by the day and it is indeed necessary to study the nuances in WSN out of which aforementioned is one. WSN's consists of large number of deployed sensor nodes and a base node for aggregating data from deployed sensor nodes. Wireless Sensor Network's (WSN) are attribute based and they are not concerned about the location of deployed sensor node from which the base node is receiving the data. In certain specific applications like health monitoring systems, tracking systems and dynamic networks, the location of transmitting node is essential. Location of the deployed sensor nodes can be found either by TOA, TDOA or Received Signal Strength (RSS) measurements. In this paper we tried to estimate the approximated distances of deployed sensor nodes using RSS measurements. The estimated distances can be further used for locating the position of deployed sensor nodes. The working model has been realised in TinyOs and RSS measurements are made using Telosb nodes.

A soft computing approach to localization in wireless sensor networks

Abstract: In this paper, we propose two intelligent localization schemes for wireless sensor networks (WSNs) The two schemes introduced in this paper exhibit range-free localization, which utilize the received signal strength (RSS) from the anchor nodes Soft computing plays a crucial role in both schemes In the first scheme, we consider the edge weight of each anchor node separately and combine them to compute the location of sensor nodes The edge weights are modeled by the fuzzy logic system (FLS) and optimized by the genetic algorithm (GA) In the second scheme, we consider the localization as a single problem and approximate the entire sensor location mapping from the anchor node signals by a neural network (NN) The simulation and experimental results demonstrate the effectiveness of the proposed schemes by comparing them with the previous methods

Method, apparatus and computer program for power control to mitigate interference

Abstract: A network determines that a first radio node communicating on a radio resource with a second radio node is interfering with a third radio node communicating on the radio resource with the network. The network manages the interference by controlling transmit power of at least one of the first radio node and the third radio node. It may be by sending a command that indicates an amount by which the first or second radio node is to decrease its transmit power; and/or that indicates an amount by which the third radio node is to boost its transmit power. The network can measure a sounding signal it triggers from the first radio node, measure and compare to a threshold that guarantees a QoS for the third radio node, and compute appropriate backoff or boost values. The first and second radio nodes may be using device-to-device communications or a femto network.

An Efficient Lossless Compression Algorithm for Tiny Nodes of Monitoring Wireless Sensor Networks

Abstract: Energy is a primary constraint in the design and deployment of wireless sensor networks (WSNs), since sensor nodes are typically powered by batteries with a limited capacity. Energy efficiency is generally achieved by reducing radio communication, for instance, limiting transmission/reception of data. Data compression can be a valuable tool in this direction. The limited resources available in a sensor node demand, however, the development of specifically designed compression algorithms. In this paper, we propose a simple lossless entropy compression (LEC) algorithm which can be implemented in a few lines of code, requires very low computational power, compresses data on the fly and uses a very small dictionary whose size is determined by the resolution of the analog-to-digital converter. We have evaluated the effectiveness of LEC by compressing four temperature and relative humidity data sets collected by real WSNs, and solar radiation, seismic and ECG data sets. We have obtained compression ratios up to 70.81% and 62.08% for temperature and relative humidity data sets, respectively, and of the order of 70% for the other data sets. Then, we have shown that LEC outperforms two specifically designed compression algorithms for WSNs. Finally, we have compared LEC with gzip, bzip2, rar, classical Huffman and arithmetic encodings.

Wireless Body Sensor Network With Adaptive Low-Power Design for Biometrics and Healthcare Applications

Abstract: A four-levels hierarchical wireless body sensor network (WBSN) system is designed for biometrics and healthcare applications. It also separates pathways for communication and control. In order to improve performance, a communication cycle is constructed for synchronizing the WBSN system with the pipeline. A low-power adaptive process is a necessity for long-time healthcare monitoring. It includes a data encoder and an adaptive power conserving algorithm within each sensor node along with an accurate control switch system for adaptive power control. The thermal sensor node consists of a micro control unit (MCU), a thermal bipolar junction transistor sensor, an analog-to-digital converter (ADC), a calibrator, a data encoder, a 2.4-GHz radio frequency transceiver, and an antenna. When detecting ten body temperature or 240 electrocardiogram (ECG) signals per second, the power consumption is either 106.3 ?W or 220.4 ?W. By switching circuits, multi sharing wireless protocol, and reducing transmission data by data encoder, it achieves a reduction of 99.573% or 99.164% in power consumption compared to those without using adaptive and encoding modules. Compared with published research reports and industrial works, the proposed method is 69.6% or 98% lower than the power consumption in thermal sensor nodes which consist only of a sensor and ADC (without MCU, 2.4-GHz transceiver, modulator, demodulator, and data encoder) or wireless ECG sensor nodes which selected Bluetooth, 2.4-GHz transceiver, and Zigbee as wireless protocols.

Towards a classification of energy aware MAC protocols for wireless sensor networks

Abstract: Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. Provided that, the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit. MAC protocols for sensor networks differ greatly from typical wireless networks access protocols in many issues. MAC protocols for sensor networks must have built-in power conservation, mobility management, and failure recovery strategies. Furthermore, sensor MAC protocols should make performance trade-off between latency and throughput for a reduction in energy consumption to maximize the lifetime of the network. This is in general achieved through duty cycling the radio transceiver. Many MAC protocols with different objectives were proposed for wireless sensor networks in the literature. Most of these protocols take into account the energy efficiency as a main objective. There is much more innovative work should be done at the MAC layer to address the hard unsolved problems. In this paper, we first outline and discuss the specific requirements and design trade-offs of a typical wireless sensor MAC protocol by describing the properties of WSN that affect the design of MAC layer protocols. Then, a typical collection of wireless sensor MAC protocols presented in the literature are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally, we present research directions and identify open issues for future medium access research. Copyright © 2009 John Wiley & Sons, Ltd.

T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks

Abstract: In wireless sensor networks, power is the most essential resource because each sensor node has limited batteries. Many kinds of existing clustering protocols have been developed to balance and maximize lifetime of the sensor nodes in wireless sensor networks. These protocols select cluster heads periodically, and they considered only `How can we select cluster heads energy-efficiently?' or `What is the best selection of cluster heads?' without considering energy-efficient period of the cluster heads replacement. Unnecessary head selection may dissipate limited battery power of the entire sensor networks. In this paper, we present T-LEACH, which is a threshold-based cluster head replacement scheme for clustering protocols of wireless sensor networks. T-LEACH minimizes the number of cluster head selection by using threshold of residual energy. Reducing the amount of head selection and replacement cost, the lifetime of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that T-LEACH outperformed LEACH in terms of balancing energy consumption and network lifetime.

A comparative review of wireless sensor network mote technologies

Abstract: In the past 10 years, wireless sensor networks have grown from a theoretical concept to a burgeoning modern technology. In this paper, we present a comparative review of several wireless sensor network motes. We analyze these WSN devices under a number of different parameters and criteria, including processing ability, expected lifetime and measurement capabilities. We compare and contrast the selected WSN motes under these different headings, highlighting the individual mote's performance under each category

Radio-triggered Wake-ups with Addressing Capabilities for Extremely Low Power Sensor Network Applications

Abstract: Sensor network applications are generally characterized by long idle durations and intermittent communication patterns. The traffic loads are typically so low that overall idle duration energy consumption dominates. Low duty cycle MAC protocols are used in order to reduce the energy consumption in idle periods. However, lowering the duty cycle value in favour of energy consumption results in increased latency, which makes this approach undesirable for many practical applications. In this paper, we propose Radio Triggered Wake-up with Addressing Capabilities (RTWAC) that allows suppressing the idle duration current consumption. Our solution consists of an external low-cost hardware wake-up circuit attached to the microcontroller of a sensor node. In order to communicate with a sensor node, a special kind of out-of-band modulated wake-up signal is transmitted. The modulated signal contains data that enables to distinguish between differently addressed nodes in order to avoid undesired node wake-ups. Furthermore, we advocate the idea of combining RTWAC to a MAC protocol running on the normal sensor node radio in order to simultaneously achieve low energy consumption and low latency for reliable data communication.

On Balancing Energy Consumption in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) require protocols that make judicious use of the limited energy capacity of the sensor nodes. In this paper, the potential performance improvement gained by balancing the traffic throughout the WSN is investigated. We show that sending the traffic generated by each sensor node through multiple paths, instead of a single path, allows significant energy conservation. A new analytical model for load-balanced systems is complemented by simulation to quantitatively evaluate the benefits of the proposed load-balancing technique. Specifically, we derive the set of paths to be used by each sensor node and the associated weights (i.e., the proportion of utilization) that maximize the network lifetime.

Compressed RF Tomography for Wireless Sensor Networks: Centralized and Decentralized Approaches

Abstract: Radio Frequency (RF) tomography refers to the process of inferring information about an environment by capturing and analyzing RF signals transmitted between nodes in a wireless sensor network In the case where few available measurements are available, the inference techniques applied in previous work may not be feasible Under certain assumptions, compressed sensing techniques can accurately infer environment characteristics even from a small set of measurements This paper introduces Compressed RF Tomography, an approach that combines RF tomography and compressed sensing for monitoring in a wireless sensor network We also present decentralized techniques which allow monitoring and data analysis to be performed cooperatively by the nodes The simplicity of our approach makes it attractive for sensor networks Experiments with simulated and real data demonstrate the capabilities of the approach in both centralized and decentralized scenarios