Showing papers on "Sensor node published in 2012"

Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection

Abstract: We propose a highly scalable cluster-based hierarchical trust management protocol for wireless sensor networks (WSNs) to effectively deal with selfish or malicious nodes. Unlike prior work, we consider multidimensional trust attributes derived from communication and social networks to evaluate the overall trust of a sensor node. By means of a novel probability model, we describe a heterogeneous WSN comprising a large number of sensor nodes with vastly different social and quality of service (QoS) behaviors with the objective to yield "ground truth" node status. This serves as a basis for validating our protocol design by comparing subjective trust generated as a result of protocol execution at runtime against objective trust obtained from actual node status. To demonstrate the utility of our hierarchical trust management protocol, we apply it to trust-based geographic routing and trust-based intrusion detection. For each application, we identify the best trust composition and formation to maximize application performance. Our results indicate that trust-based geographic routing approaches the ideal performance level achievable by flooding-based routing in message delivery ratio and message delay without incurring substantial message overhead. For trust-based intrusion detection, we discover that there exists an optimal trust threshold for minimizing false positives and false negatives. Furthermore, trust-based intrusion detection outperforms traditional anomaly-based intrusion detection approaches in both the detection probability and the false positive probability.

Making sensor networks immortal: an energy-renewal approach with wireless power transfer

Abstract: Wireless sensor networks are constrained by limited battery energy. Thus, finite network lifetime is widely regarded as a fundamental performance bottleneck. Recent breakthrough in the area of wireless power transfer offers the potential of removing this performance bottleneck, i.e., allowing a sensor network to remain operational forever. In this paper, we investigate the operation of a sensor network under this new enabling energy transfer technology. We consider the scenario of a mobile charging vehicle periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions. We study an optimization problem, with the objective of maximizing the ratio of the wireless charging vehicle (WCV)'s vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and provide a number of important properties. Subsequently, we develop a near-optimal solution by a piecewise linear approximation technique and prove its performance guarantee.

A Survey of Localization in Wireless Sensor Network

Abstract: Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network.

E-SAP: Efficient-Strong Authentication Protocol for Healthcare Applications Using Wireless Medical Sensor Networks

Abstract: A wireless medical sensor network (WMSN) can sense humans' physiological signs without sacrificing patient comfort and transmit patient vital signs to health professionals' hand-held devices. The patient physiological data are highly sensitive and WMSNs are extremely vulnerable to many attacks. Therefore, it must be ensured that patients' medical signs are not exposed to unauthorized users. Consequently, strong user authentication is the main concern for the success and large scale deployment of WMSNs. In this regard, this paper presents an efficient, strong authentication protocol, named E-SAP, for healthcare application using WMSNs. The proposed E-SAP includes: (1) a two-factor (i.e., password and smartcard) professional authentication; (2) mutual authentication between the professional and the medical sensor; (3) symmetric encryption/decryption for providing message confidentiality; (4) establishment of a secure session key at the end of authentication; and (5) professionals can change their password. Further, the proposed protocol requires three message exchanges between the professional, medical sensor node and gateway node, and achieves efficiency (i.e., low computation and communication cost). Through the formal analysis, security analysis and performance analysis, we demonstrate that E-SAP is more secure against many practical attacks, and allows a tradeoff between the security and the performance cost for healthcare application using WMSNs.

Improvement of LEACH protocol for WSN

Abstract: In wireless sensor networks, sensor nodes always have a limited power resource. The energy consumed by transferring data from the sensor node to its destination raises as a critical issue in designing reasonable wireless sensor network routing protocols. In this paper we propose a revised cluster routing algorithm named E-LEACH to enhance the hierarchical routing protocol LEACH. In the E-LEACH algorithm, the original way of the selection of the cluster heads is random and the round time for the selection is fixed. In the E-LEACH algorithm, we consider the remnant power of the sensor nodes in order to balance network loads and changes the round time depends on the optimal cluster size. The simulation results show that our proposed protocol increases network lifetime at least by 40% when compared with the LEACH algorithm.

On renewable sensor networks with wireless energy transfer: The multi-node case

Abstract: Wireless energy transfer based on magnetic resonant coupling is a promising technology to replenish energy to sensor nodes in a wireless sensor network (WSN). However, charging sensor node one at a time poses a serious scalability problem. Recent advances in magnetic resonant coupling shows that multiple nodes can be charged at the same time. In this paper, we exploit this multi-node wireless energy transfer technology to address energy issue in a WSN. We consider a wireless charging vehicle (WCV) periodically traveling inside a WSN and charging sensor nodes wirelessly. We propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal cells. The WCV visits these cells and charge sensor nodes from the center of a cell. We pursue a formal optimization framework by jointly optimizing traveling path, flow routing and charging time. By employing discretization and a novel Reformulation-Linearization Technique (RLT), we develop a provably near-optimal solution for any desired level of accuracy.

BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Wireless Sensor Networks

Abstract: Injecting false data attack is a well known serious threat to wireless sensor network, for which an adversary reports bogus information to sink causing error decision at upper level and energy waste in en-route nodes. In this paper, we propose a novel bandwidth-efficient cooperative authentication (BECAN) scheme for filtering injected false data. Based on the random graph characteristics of sensor node deployment and the cooperative bit-compressed authentication technique, the proposed BECAN scheme can save energy by early detecting and filtering the majority of injected false data with minor extra overheads at the en-route nodes. In addition, only a very small fraction of injected false data needs to be checked by the sink, which thus largely reduces the burden of the sink. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed scheme in terms of high filtering probability and energy saving.

On Received-Signal-Strength Based Localization with Unknown Transmit Power and Path Loss Exponent

Abstract: In this letter, we consider the received-signal-strength (RSS) based localization problem with unknown transmit power and unknown path loss exponent (PLE). For the case of unknown transmit power, we derive a weighed least squares (WLS) formulation to jointly estimate the sensor node location and the transmit power, based on the unscented transformation (UT). For the case of unknown PLE, we propose an alternating estimation procedure to alternatively estimate the sensor node location and the PLE. The estimation procedure can also be applied to the case when both the transmit power and the PLE are unknown. Simulation results confirm the effectiveness of the proposed method.

Data Aggregation in Wireless Sensor Network

Abstract: The fast advancement of hardware technology has enabled the development of tiny and powerful sensor nodes, which are capable of sensing, computation and wireless communication. This revolutionizes the deployment of wireless sensor network for monitoring some area and collecting regarding information. However, limited energy constraint presents a major challenge such vision to become reality. Data communication between nodes consumes a large portion of the total energy consumption of the WSNs. Consequently, Data Aggregation techniques can greatly help to reduce the energy consumption by eliminating redundant data traveling back to the base station (sink).This paper signifies the various data aggregation techniques in wireless sensor network and implementation of a data aggregation technique in wireless sensor networks. The main goal of data aggregation is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. To provide energy efficiency we have designed energy efficient data aggregation method named E-BIN. We have considered a cluster-based wireless sensor network. Our method executes on each cluster independently and provides an energy efficient data aggregation in a cluster and hence maximize network lifetime for whole network.

Dynamic Duty-Cycle Scheduling Schemes for Energy-Harvesting Wireless Sensor Networks

Abstract: In this letter, we propose two novel dynamic duty-cycle scheduling schemes (called DSR and DSP) in order to reduce sleep latency, while achieving balanced energy consumption among sensor nodes in wireless sensor networks (WSNs) with energy harvesting capability. In DSR, each sensor node is allowed to adjust its duty-cycle according to the current amount of residual energy only. Since the residual energy of nodes in energy-harvesting WSNs can increase over time due to their harvesting opportunity, the estimation of prospective increase in their residual energy is useful to achieve our goal. Hence, DSP allows each of sensor nodes to reduce its duty-cycle more aggressively in proportion to such an increase. Through NS-2 simulations, we verified that our proposed schemes outperform the duty-cycle scheduling scheme used in a representative existing MAC protocol such as RI-MAC.

Mobile Sensor Node Deployment and Asynchronous Power Management for Wireless Sensor Networks

Abstract: Mobile sensor node deployment and power management are important issues in the wireless sensor network system. This study designs a mobile sensor node platform to achieve a highly accurate localization mechanism by using ultrasonic, dead reckoning, and radio frequency information which is processed through a particle filter algorithm. Mobile sensor node with accurate localization ability is of great interest to basic research works and applications, such as sensor deployment, coverage management, dynamic power management, etc. In this paper, we propose an efficient mobile sensor node deployment method, grid deployment, where the map is divided into multiple individual grids and the weight of each grid is determined by environmental factors such as predeployed nodes, boundaries, and obstacles. The grid with minimum values is the goal of the mobile node. We also design an asynchronous power management strategy in our sensor node to reduce power consumption of the sensor network. Several factors such as probability of event generation, battery status, coverage issues, and communication situations have also been taken into consideration. In network communication, we propose an asynchronous awakening scheme so that each node is free to switch on or off its components according to observed event statistics and make a tradeoff between communication and power consumption. The deepest sleep state period is determined by the residual power. By combining these methods, the power consumption of the sensor node can be reduced.

Two-Tiered Constrained Relay Node Placement in Wireless Sensor Networks: Computational Complexity and Efficient Approximations

Abstract: In wireless sensor networks, relay node placement has been proposed to improve energy efficiency. In this paper, we study two-tiered constrained relay node placement problems, where the relay nodes can be placed only at some prespecified candidate locations. To meet the connectivity requirement, we study the connected single-cover problem where each sensor node is covered by a base station or a relay node (to which the sensor node can transmit data), and the relay nodes form a connected network with the base stations. To meet the survivability requirement, we study the 2-connected double-cover problem where each sensor node is covered by two base stations or relay nodes, and the relay nodes form a 2-connected network with the base stations. We study these problems under the assumption that R \ge 2r > 0, where R and r are the communication ranges of the relay nodes and the sensor nodes, respectively. We investigate the corresponding computational complexities, and propose novel polynomial time approximation algorithms for these problems. Specifically, for the connected single-cover problem, our algorithms have {\cal O}(1)-approximation ratios. For the 2-connected double-cover problem, our algorithms have {\cal O}(1)-approximation ratios for practical settings and {\cal O}(\ln n)-approximation ratios for arbitrary settings. Experimental results show that the number of relay nodes used by our algorithms is no more than twice of that used in an optimal solution.

Dynamic Power Management in Wireless Sensor Networks: State-of-the-Art

Abstract: In the last few years, interest in wireless sensor networks has increased considerably. These networks can be useful for a large number of applications, including habitat monitoring, structural health monitoring, pipeline monitoring, transportation, precision agriculture, supply chain management, and many more. Typically, a wireless sensor network consists of a large number of simple nodes which operate with exhaustible batteries, unattended. Manual replacement or recharging the batteries is not an easy or desirable task. Hence, how energy is utilized by the various hardware subsystems of individual nodes directly affects the scope and usefulness of the entire network. This paper provides a comprehensive assessment of state-of-the-art of dynamic power management (DPM) in wireless sensor networks. It investigates aspects of power dissipation in a node and analyses the strength and limitations of selective switching, dynamic frequency, and voltage scaling.

On-the-Fly calibration of low-cost gas sensors

Abstract: Air quality monitoring is extremely important as air pollution has a direct impact on human health. Low-cost gas sensors are used to effectively perceive the environment by mounting them on top of mobile vehicles, for example, using a public transport network. Thus, these sensors are part of a mobile network and perform from time to time measurements in each others vicinity. In this paper, we study three calibration algorithms that exploit co-located sensor measurements to enhance sensor calibration and consequently the quality of the pollution measurements on-the-fly. Forward calibration, based on a traditional approach widely used in the literature, is used as performance benchmark for two novel algorithms: backward and instant calibration. We validate all three algorithms with real ozone pollution measurements carried out in an urban setting by comparing gas sensor output to high-quality measurements from analytical instruments. We find that both backward and instant calibration reduce the average measurement error by a factor of two compared to forward calibration. Furthermore, we unveil the arising difficulties if sensor calibration is not based on reliable reference measurements but on sensor readings of low-cost gas sensors which is inevitable in a mobile scenario with only a few reliable sensors. We propose a solution and evaluate its effect on the measurement accuracy in experiments and simulation.

Methods and apparatus to enhance reliability in millimeter wave wideband communications

Abstract: A network node in a wireless network performs a method for enhancing reliability in wireless communication. The method includes determining, at a first network node, that a current link with a second network node is broken. The method also includes attempting, at the first network node, to recover the current link. The method further includes, upon a determination that the current link is not recoverable, establishing, at the first network node, a new link with the second network node according to one of a plurality of switching rules, the switching rules ordered according to a priority among the switching rules.

A Qualitative Comparison of Different Logical Topologies for Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) are formed by a large collection of power-conscious wireless-capable sensors without the support of pre-existing infrastructure, possibly by unplanned deployment. With a sheer number of sensor nodes, their unattended deployment and hostile environment very often preclude reliance on physical configuration or physical topology. It is, therefore, often necessary to depend on the logical topology. Logical topologies govern how a sensor node communicates with other nodes in the network. In this way, logical topologies play a vital role for resource-constraint sensor networks. It is thus more intuitive to approach the constraint minimizing problems from (logical) topological point of view. Hence, this paper aims to study the logical topologies of WSNs. In doing so, a set of performance metrics is identified first. We identify various logical topologies from different application protocols of WSNs, and then compare the topologies using the set of performance metrics.

SenShare: transforming sensor networks into multi-application sensing infrastructures

Abstract: Sensor networks are typically purpose-built, designed to support a single running application. As the demand for applications that can harness the capabilities of a sensor-rich environment increases, and the availability of sensing infrastructure put in place to monitor various quantities soars, there are clear benefits in a model where infrastructure can be shared amongst multiple applications. This model however introduces many challenges, mainly related to the management of the communication of the same application running on different network nodes, and the isolation of applications within the network. In this work we present SenShare, a platform that attempts to address the technical challenges in transforming sensor networks into open access infrastructures capable of supporting multiple co-running applications. SenShare provides a clear decoupling between the infrastructure and the running application, building on the concept of overlay networks. Each application operates in an isolated environment consisting of an in-node hardware abstraction layer, and a dedicated overlay sensor network. We further report on the deployment of SenShare within our building, which presently supports the operation of multiple sensing applications, including office occupancy monitoring and environmental monitoring.

A modular 1mm 3 die-stacked sensing platform with optical communication and multi-modal energy harvesting

Abstract: Wireless sensor nodes have many compelling applications such as smart buildings, medical implants, and surveillance systems. However, existing devices are bulky, measuring >1cm3, and they are hampered by short lifetimes and fail to realize the “smart dust” vision of [1]. Smart dust requires a mm3-scale, wireless sensor node with perpetual energy harvesting. Recently two application-specific implantable microsystems [2][3] demonstrated the potential of a mm3-scale system in medical applications. However, [3] is not programmable and [2] lacks a method for re-programming or re-synchronizing once encapsulated. Other practical issues remain unaddressed, such as a means to protect the battery during the time period between system assembly and deployment and the need for flexible design to enable use in multiple application domains. To this end, we propose a 1.0mm3 general-purpose heterogeneous sensor node platform with a stackable multi-layer structure that includes a new, ultra-low power I2C (Inter-Integrated Circuit) interface for inter-layer communication. The system has an ultra-low-power optical wakeup receiver and GOC (Global Optical Communication), which enables re-programming and synchronization. It also includes an ultra-low power PMU (Power Management Unit) with BOD (BrownOut Detector) to prevent processor malfunctions and battery damage. The BOD also controls a POR (Power-On Reset) module in other layers to enable a proper reset sequence. Image and temperature sensors are implemented, but the modularity of the system allows end-users to easily replace or add layers to incorporate specific circuits in appropriate technologies as needed.

A batteryless 19μW MICS/ISM-band energy harvesting body area sensor node SoC

Abstract: Recent advances in ultra-low power chip design techniques, many originally targeting wireless sensor networks, will enable a new generation of body-worn devices for health monitoring. We utilize the state-of-the-art in low power RF transmitters, low voltage boost circuits, subthreshold processing, biosignal front-ends, dynamic power management, and energy harvesting to realize an integrated reconfigurable wireless body-area-sensor node (BASN) SoC capable of autonomous power management for battery-free operation.

Smart parking service based on Wireless Sensor Networks

Abstract: In this paper, we present the design and implementation of a prototype system of Smart Parking Services based on Wireless Sensor Networks (WSNs) that allows vehicle drivers to effectively find the free parking places. The proposed scheme consists of wireless sensor networks, embedded web-server, central web-server and mobile phone application. In the system, low-cost wireless sensors networks modules are deployed into each parking slot equipped with one sensor node. The state of the parking slot is detected by sensor node and is reported periodically to embedded web-server via the deployed wireless sensor networks. This information is sent to central web-server using Wi-Fi networks in real-time, and also the vehicle driver can find vacant parking lots using standard mobile devices.

Optimal mode selection for cognitive radio sensor networks with RF energy harvesting

Abstract: This paper investigates an optimal mode selection policy for cognitive radio sensor networks powered by RF energy harvesting. The RF energy harvesting enables the sensor node to operate with a potentially perpetual lifetime. We assume that the sensor node harvests RF energy received from the primary network and it cannot carry out RF energy harvesting and opportunistic spectrum access at the same time. Therefore, the sensor node should decide whether to access the spectrum or to harvest RF energy in each time slot to maximize an expected total throughput. We develop the optimal mode selection policy by casting this decision making problem in the framework of partially observable Markov decision process (POMDP). Numerical results show that the developed optimal policy finds a balance between obtaining the immediate throughput and harvesting the RF energy for future use.

A Survey on Virtualization of Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.

A survey of Wireless Sensor Networks

Abstract: This essay gives a brief introduction of the Wireless Sensor Network, including its features, application, system structure, the analysis of energy dissipation behavior, the key technologies of the Wireless Sensor Network, and node location methods. What is more, it also analyses existing problems and development orientation in the future.

Analytic comparison of wake-up receivers for WSNs and benefits over the wake-on radio scheme

Abstract: Since in most wireless sensor network (WSN) scenarios nodes must operate autonomously for months or years, power management of the radio (usually consuming the largest amount of node's energy) is crucial. In particular, reducing the power consumption during listening plays a fundamental role in the whole energy balance of a sensor node, since shutting down the receiver when no messages are expected can remarkably increase the autonomy. Idle listening is a hard challenge because incoming messages are often unpredictable and developers have to trade off low power consumption and high quality of service. This paper is focusing on benefits of introducing a wake-up receiver over simple duty-cycling (wake-on radio). We analyze and compare the existing wake-up receiver prototypes and explore their benefits using simulations of two typical scenarios: with and without addressing requirements. A particular approach outperforms other solutions in terms of lifetime extension because of its very low power consumption (1$\mu$W). We also evaluate the overhead of the addressing capability, which sometimes has a non-negligible impact on the performance.

An optimal energy allocation algorithm for energy harvesting wireless sensor networks

Abstract: With the use of energy harvesting technologies, the lifetime of a wireless sensor network (WSN) can be prolonged significantly. Unlike a traditional WSN powered by non-rechargeable batteries, the energy management policy of an energy harvesting WSN needs to take into account the energy replenishment process. In this paper, we study the energy allocation for sensing and transmission in an energy harvesting sensor node with a rechargeable battery and a finite data buffer. The sensor node aims to maximize the total throughput in a finite horizon subject to time-varying energy harvesting rate, energy availability in the battery, and channel fading. We formulate the energy allocation problem as a sequential decision problem and propose an optimal energy allocation (OEA) algorithm using dynamic programming. We conduct simulations to compare the performance between our proposed OEA algorithm and the channel-aware energy allocation (CAEA) algorithm from [1]. Simulation results show that the OEA algorithm achieves a higher throughput than the CAEA algorithm under different settings.

Spatial Gaussian Process Regression With Mobile Sensor Networks

Abstract: This paper presents a method of using Gaussian process regression to model spatial functions for mobile wireless sensor networks. A distributed Gaussian process regression (DGPR) approach is developed by using a sparse Gaussian process regression method and a compactly supported covariance function. The resultant formulation of the DGPR approach only requires neighbor-to-neighbor communication, which enables each sensor node within a network to produce the regression result independently. The collective motion control is implemented by using a locational optimization algorithm, which utilizes the information entropy from the DGPR result. The collective mobility of sensor networks plus the online learning capability of the DGPR approach also enables the mobile sensor network to adapt to spatiotemporal functions. Simulation results are provided to show the performance of the proposed approach in modeling stationary spatial functions and spatiotemporal functions.