The wireless sensor network is a resource-constrained self-organizing system that consists of a large number of tiny sensor nodes. Due to the low-cost and low-power nature of sensor nodes, sensor nodes are failure-prone when sensing and processing data. Most presented fault-tolerant research for wireless sensor networks focused on crash faults or power faults and less on Byzantine faults. Hence, in this paper, we propose a power-saving data aggregation algorithm for Byzantine faults to provide power savings and high success rates even in the environment with high fault rates. The algorithm utilizes the concept of Byzantine masking quorum systems to mask the erroneous values and to finally determine the correct value. Our simulation results demonstrate that when the fault rate of sensor nodes is up to 50%, our algorithm still has 48% success rate to obtain the correct value. Under the same condition, other fault-tolerant algorithms are almost failed.

In this paper we propose a novel functional amplifier suitable for low-power wireless receivers in a wireless sensor network. This amplifier can change input threshold level as carrier sensing level, since it has a minimum input amplitude to be amplified. A simple rail-to-rail output is suitable for a subsequent digital interface. The target frequency is 433 MHz, and the maximum voltage gain is 11 dB. The standby power is 39.5 nW, and the active power is 352 µW. The chip area is 8224 µm2.

We analyze the performance of an opportunistic transmission strategy for Wireless Sensor Networks (WSNs). We consider a transmission strategy called Binary Decision-Based Transmission (BDT), which is a common form of opportunistic transmission. The BDT scheme initiates transmission only when the channel quality exceeds the optimum threshold to avoid unsuccessful transmissions that waste energy. We formulate the Markov Decision Process (MDP) to identify an optimum threshold for transmission decisions in the BDT scheme.

This letter proposes a simple modification of LEACH protocol to exploit its multi-hop scenario for user cooperation. Instead of a single cluster-head we propose M cluster-heads in each cluster to obtain the diversity of order M. All cluster-heads gather data from all sensor nodes within the cluster using the same technique as LEACH. Cluster-heads transmit gathered data cooperatively towards the destination or higher order cluster-head. We propose a code combining based cooperative protocol. We also develop the upper bounds on frame error rate (FER) for our proposal. Simulation and analysis show that our proposal can significantly prolong the system lifetime.

This paper presents a multi functional range finder employing dual imager core on a single chip. Each imager core has functionalities of 2-D imaging and 3-D capture using the light section method with combinations of the dual imager core. The presented chip achieves, 2-D imaging mode, 3-D capture mode with the conventional light-section method, high-speed 3-D capture mode with the stereo matching mode, and 2-D and 3-D simultaneous capture mode. We demonstrate 58 fps 2-D imaging with 8 bit gray scale, and 24.8 rangemaps/s 3-D range-finder with the maximum range error of 1.619 mm and the standard deviation of 0.385 mm at 700 mm.

This paper proposes a one-way ranging method using reference-based broadcasting messages. The method is based on impulse radio UWB (Ultra-wideband) for wireless sensor networks. The proposed method reduces traffic overheads and increases the ranging accuracy using frequency offsets and counter information based on virtually synchronized counters between RNs (Reference Nodes) and MNs (Mobile Nodes). Simulation results show that the proposed method can alleviate the ranging errors comparing to SDS-TWR (Symmetric Double-Sided Two-Way Ranging) method in terms of the frequency offset.

Secure sensor localization is a prerequisite for many sensor networks to retrieve trustworthy data. However, most of existing node positioning systems were studied in trust environment and are therefore vulnerable to malicious attacks. In this work, we develop a robust node positioning mechanism(ROPM) to protect localization techniques from position attacks. Instead of introducing countermeasures for every possible internal or external attack, our approach aims at making node positioning system attack-tolerant by removing malicious beacons. We defeat internal attackers and external attackers by applying different strategies, which not only achieves robustness to attacks but also dramatically reduces the computation overhead. Finally, we provide detailed theoretical analysis and simulations to evaluate the proposed technique.

To solve the problem of distributed multisensor fusion, the optimal linear methods can be used in Gaussian noise models. In practice, channel noise distributions are usually non-Gaussian, possibly heavy-tailed, making linear methods fail. By combining a classical tool of optimal linear fusion and a robust statistical method, the two-stage MAD robust fusion (MADRF) algorithm is proposed. It effectively performs both in symmetrically and asymmetrically contaminated Gaussian channel noise with contamination parameters varying over a wide range.

Recently, the result of TinyECCK (Tiny Elliptic Curve Cryptosystem with Koblitz curve) shows that both field multiplication and reduction over GF(2m) are related to a heavy amount of duplicated memory accesses and that reducing the number of these duplications noticeably improves the performance of elliptic curve operations such as scalar multiplications, signing and verification. However, in case that the underlying word size is extended from 8-bit to 16-bit or 32-bit, the efficiency of the techniques proposed in TinyECCK is decreased because the number of memory accesses to load or store an element in GF(2m) is significantly reduced. Therefore, in this paper, we propose a technique which makes left-to-right (ltr) comb method which is widely used as an efficient multiplication algorithm over GF(2m) suitable for extended word sizes and present TinyECCK16 (Tiny Elliptic Curve Cryptosystem with Koblitz curve on 16-bit word) which is implemented with the proposed multiplication algorithm on 16-bit Tmote Sky mote. The proposed algorithm is faster than typical ltr comb method by 15.06% and the 16-bit version of the algorithm proposed in TinyECCK by 5.12% over GF(2163).

Pairing-based cryptography provides us many novel cryptographic applications such as ID-based cryptosystems and efficient broadcast encryptions. The security problems in ubiquitous sensor networks have been discussed in many papers, and pairing-based cryptography is a crucial technique to solve them. Due to the limited resources in the current sensor node, it is challenged to optimize the implementation of pairings on sensor nodes. In this paper we present an efficient implementation of pairing over MICAz, which is widely used as a sensor node for ubiquitous sensor network. We improved the speed of ηT pairing by using a new efficient multiplication specialized for ATmega128L, called the block comb method and several optimization techniques to save the number of data load/store operations. The timing of ηT pairing over GF(2239) achieves about 1.93 sec, which is the fastest implementation of pairing over MICAz to the best of our knowledge. From our dramatic improvement, we now have much high possibility to make pairing-based cryptography for ubiquitous sensor networks practical.

In this paper, the problem of density estimation and clustering in sensor networks is considered. It is assumed that measurements of the sensors can be statistically modeled by a common Gaussian mixture model. This paper develops a distributed variational Bayesian algorithm (DVBA) to estimate the parameters of this model. This algorithm produces an estimate of the density of the sensor data without requiring the data to be transmitted to and processed at a central location. Alternatively, DVBA can be viewed as a distributed processing approach for clustering the sensor data into components corresponding to predominant environmental features sensed by the network. The convergence of the proposed DVBA is then investigated. Finally, to verify the performance of DVBA, we perform several simulations of sensor networks. Simulation results are very promising.

In this letter, we propose a novel approach using wireless sensor networks (WSNs) to enhance the safety and efficiency of four-way stop-sign-controlled (FWSC) intersections. The proposed algorithm provides right of way (RoW) and crash avoidance information by means of an intelligent WSN system. The system is composed of magnetic sensors, embedded in the center of a lane, with relay nodes and a base station placed on the side of the road. The experimental results show that the vehicle detection accuracy is over 99% and the sensor node battery life expectancy is over 3 years for traffic of 5,800 vehicles per day. For the traffic application we consider, a strong effect is observed as the projected conflict rate was reduced by 72% compared to an FWSC intersection operated with only driver perception.

Sensor networks have promising applications such as battlefield surveillance, biological detection, and emergency navigation, etc. Crucial problems in sensor networks are energy-efficiency and collision avoidance in wireless communication. To deal with the problems, we consider a self-stabilizing solution to the construction of k disjoint sense-sleep trees, where range adjustment and the use of GPS are allowed. Each root is determined by its identifier and is distinguished by its color, the identification of a tree. Using a dominating k-partition rule, each non-root node first determines a color irrelevant to the root. Then, the non-root node determines a parent node that is equally colored with minimal distance. If there is no appropriate parent, the range is extended or shrunk until the nearest parent is determined. Finally, we perform a simulation.

Clustering the sensor nodes is one of the most popular and effective approaches for applications that must support hundreds or thousands of nodes. The conventional algorithms consider various parameters to evenly distribute the energy load. However, energy consumption problem of the cluster head still remains. In this paper, we propose a novel clustering approach that periodically elects cluster heads with assistant nodes. The assistant nodes substitute for each cluster head to transmit sensor readings to the base station. Performance evaluations show that our proposed clustering algorithm achieves about 10-40% better performance than the existing clustering algorithms in terms of lifetime.

This letter presents the variation of localization error to network parameters, the number of range estimation results from anchor nodes (ANs) and average distance between ANs in centralized Wireless Sensor Network (WSN). In sensor network, ANs estimate the relative range to Target Node (TN) using Time-Of-Arrival (TOA) information of Ultra WideBand (UWB) radio and a fusion center determines the final localization of TN based on estimation results reported. From simulation results, the variation of localization error, which is defined as the difference between localization result of TN and its actual location, is represented as the function of number of estimation results to average distance between ANs. The distribution of localization error is matched to the Rician distribution whose K-factor value is given by the proposed formula as well. Finally, the normalized error function for the efficient localization network design is characterized.

This paper focuses on optical integration technology and its application in optical microsensors used in biomedical fields. The integration is based on the hybrid integration approach, achieving high performance, small size and weight, and lower cost. First, we describe the key technologies used in hybrid integration, namely passive alignment technology, low temperature bonding technology, and packaging technology for realizing advanced microsensors. Then, we describe an integrated laser Doppler flowmeter that can monitor blood flow in human skin.

In the proposed scheme, every sensor establishes communications keys with its neighbors after deployment. They are selectively employed for intra-cluster communications, and the employed keys are determined by local topology of clusters. Thus, our scheme periodically changes the local topology of clusters so as to renew the intra-cluster communication keys. Besides, new Cluster Heads (CHs) easily share a key with the Base Station (BS) by informing the BS of their member information without sending key materials. Simulation results prove that our approach has strong resiliency against the increase of compromised sensors. It also achieves a performance gain in terms of energy.

Wireless sensor networks (WSNs) have attracted a significant amount of interest from many researchers because they have great potential as a means of obtaining information of various environments remotely. WSNs have a wide range of applications, such as natural environmental monitoring in forest regions and environmental control in office buildings. In WSNs, hundreds or thousands of micro-sensor nodes with such resource limitations as battery capacity, memory, CPU, and communication capacity are deployed without control in a region and used to monitor and gather sensor information of environments. Therefore, a scalable and efficient network control and/or data gathering scheme for saving energy consumption of each sensor node is needed to prolong WSN lifetime. In this paper, assuming that sensor nodes synchronize to intermittently communicate with each other only when they are active for realizing the long-term employment of WSNs, we propose a new synchronization scheme for gathering sensor information using chaotic pulse-coupled neural networks (CPCNN). We evaluate the proposed scheme using computer simulations and discuss its development potential. In simulation experiments, the proposed scheme is compared with a previous synchronization scheme based on a pulse-coupled oscillator model to verify its effectiveness.

For many sensor network applications such as military, homeland security, it is necessary for users (sinks) to access sensor networks while they are moving. However, sink mobility brings new challenges to secure routing in large-scale sensor networks. Mobile sinks have to constantly propagate their current location to all nodes, and these nodes need to exchange messages with each other so that the sensor network can establish and maintain a secure multi-hop path between a source node and a mobile sink. This causes significant computation and communication overhead for sensor nodes. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. In this paper, we propose a secure and energy-efficient data dissemination protocol -- Secure COodination-based Data dissEmination (SCODE) -- for mobile sinks in sensor networks. We take advantages of coordination networks (grid structure) based on Geographical Adaptive Fidelity (GAF) protocol to construct a secure and efficient routing path between sources and sinks. Our security analysis demonstrates that the proposed protocol can defend against common attacks in sensor network routing such as replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Our performance evaluation both in mathematical analysis and simulation shows that the SCODE significantly reduces communication overhead and energy consumption while the latency is similar compared with the existing routing protocols, and it always delivers more than 90 percentage of packets successfully.

For successful data collection in wireless sensor networks, it is important to ensure that the required delivery ratio is maintained while keeping a fair rate for every sensor. Furthermore, emerging high-rate applications might require complete reliability and the transfer of large volume of data, where persistent congestion might occur. These requirements demand a complete but efficient solution for data transport in sensor networks which reliably transports data from many sources to one or more sinks, avoids congestion and maintains fairness. In this paper, we propose congestion-aware and rate-controlled reliable transport (CRRT), an efficient and low-overhead data transport mechanism for sensor networks. CRRT uses efficient MAC retransmission to increase one-hop reliability and end-to-end retransmission for loss recovery. It also controls the total rate of the sources centrally, avoids the congestion in the bottleneck based on congestion notifications from intermediate nodes and centrally assigns the rate to the sources based on rate assignment policy of the applications. Performance of CRRT is evaluated in NS-2 and simulation results demonstrate the effectiveness of CRRT.