This paper presents a novel cross-layer approach to explore selection diversity for distributed clustering based wireless sensor networks (WSNs) by selecting a proper cluster-head. We develop and analyze an instantaneous channel state information (CSI) based cluster-head selection algorithm for a distributed, dynamic and randomized clustering based WSN. The proposed cluster-head selection scheme is also random and capable to distribute the energy uses among the nodes in the network. We present an analytical approach to evaluate the energy efficiency and system lifetime of our proposal. Analysis shows that the proposed scheme outperforms the performance of additive white Gaussian noise (AWGN) channel under Rayleigh fading environment. This proposal also outperforms the existing cooperative diversity protocols in terms of system lifetime and implementation complexity.

A network of sensors can be used to obtain state based data from the area in which they are deployed. To reduce costs, the data sent via intermediate sensors to a sink are often aggregated. In this letter, we introduce Self-Construction of Aggregation Tree (SCAT) scheme which uses a novel data aggregation scheme utilizing the knowledge of the mobile node and the infrastructure (static node tree) in gathering the data from the mobile node. The static nodes can construct a near- optimal aggregation tree by themselves, using the knowledge of the mobile node, which is a process similar to forming the centralized aggregation tree.

In this letter, we develop an anycast-based emergency service for healthcare wireless sensor networks. The new service could operate with sensors to detect and activate an alarm system based on predefined conditions that are specific to the patient and the disease. The new service is implemented on 802.15.4 ZigBee which usually has large control overhead and long transmission times. To improve the service performance, our service identifies the closest emergency service provider to alleviate the control overhead and achieve immediate assistance when a patient requests for an emergency service. We also increase the reliability of packet transmission by using a Recovery Point scheme. Our simulations and experiment demonstrate that our scheme is efficient and feasible for healthcare wireless sensor networks.

Wireless sensor networks with a star network topology are commonly applied for health monitoring systems. To determine the condition of a patient, sensor nodes are attached to the body to transmit the data to a coordinator. However, this process is inefficient because the coordinator is always communicating with each sensor node resulting in a data processing workload for the coordinator that becomes much greater than that of the sensor nodes. In this paper, a method is proposed to reduce the number of data transmissions from the sensor nodes to the coordinator by establishing a threshold for data from the biological signals to ensure that only relevant information is transmitted. This results in a dramatic reduction in power consumption throughout the entire network.

A fuel-supply system using movable fuel-supply vehicles (FSVs) is proposed and its performance is evaluated. Both FSVs and vehicles requesting fuel are equipped with networked sensors. The sensors in FSVs are location sensors, and those in vehicles requesting fuel are for determining the remaining amount of fuel and the location of the vehicle. The time from when a fuel request is generated until the request is satisfied is the most basic performance metric for this system. Explicit formulas for the probabilistic distribution of this request time are also derived. Numerical examples show that the number of movable FSVs can be smaller than that of fixed fuel stations by about 80% or more than two orders of magnitude. This result suggests that movable FSVs may reduce the cost of the fuel supply infrastructure for alternative-fuel vehicles such as fuel-cell vehicles.

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

In this letter, we propose an energy efficient hybrid architecture, the Hybrid MAC-based Robust Architecture (HMR), for wireless sensor networks focusing on MAC layer's scheduling and adaptive security suite as a security sub layer. A hybrid MAC layer with TDMA and CSMA scheduling is designed to prolong network life time, and the multi-channel TDMA based active/sleep scheduling is presented. We also present the security related functionalities needed to employ a flexible security suite to packets dynamically. Implementation and testbed of the proposed framework based on IEEE 802.15.4 are shown as well.

Many applications of wireless sensor networks (WSNs) require secure group communications. The WSNs are normally operated in unattended, harsh, or hostile environment. The adversaries may easily compromise some sensor nodes and abuse their shared keys to inject false sensing reports or modify the reports sent by other nodes. Once a malicious node is detected, the group key should be renewed immediately for the network security. Some strategies have been proposed to develop the group rekeying protocol, but most of existing schemes are not suitable for sensor networks due to their high overhead and poor scalability. In this paper, we propose a new group rekeying protocol for hierarchical WSNs with renewable network devices. Compared with existing schemes, our rekeying method possesses the following features that are particularly beneficial to the resource-constrained large-scale WSNs: (1) robustness to the node capture attack, (2) reactive rekeying capability to malicious nodes, and (3) low communication and storage overhead.

This letter proposes a novel mobile sensor deployment scheme for maximizing coverage. The basic idea is to force mobile sensors to move to predetermined target points that are the optimal layout in a distributed manner using Voronoi diagram data structure. A simulation shows that the result of the proposed scheme is quite close to the optimal result and outperforms previous works.

Security and privacy of wireless sensor networks are key research issues recently. Most existing researches regarding wireless sensor networks security consider homogenous sensor networks. To achieve better security and performance, we adopt a heterogeneous wireless sensor network (HWSN) model that consists of physically different types of sensor nodes. This paper presents a secure message distribution scheme with configurable privacy for HWSNs, which takes advantage of powerful high-end sensor nodes. The scheme establishes a message distribution topology in an efficient and secure manner. The sensor node only need generate one signature for all the messages for all the users, which can greatly save the communication and computation cost of the sensor node. On the other hand, the user can only know the messages that let him know based on a pre-set policy, which can meet the requirement of the privacy. We show that the scheme has small bandwidth requirements and it is resilient against the node compromise attack.

Multiple hop based routing in homogeneous sensor networks with a single sink suffers performance degradation and severe security threats with the increase of the size of sensor networks. Large-scale sensor networks need to be deployed with multiple powerful nodes as sinks and they should be scheduled to move to different places during the lifetime of the networks. Existing routing mechanisms lack of such supports for large-scale sensor networks. In this paper, we propose a heterogeneous network model where multiple mesh nodes are deployed in a sensor network, and sensed data are collected through two tiers: firstly from a source sensor node to the closest mesh node in a multiple-hop fashion (called sensor routing), and then from the mesh node to the base station through long-distance mesh routing (called mesh routing). Based on this network model, we propose an energy-efficient and secure protocol for the sensor routing that can work well in large-scale sensor networks and resist most of attacks. Experiments demonstrate that our routing protocol significantly reduces average hops for data transmission. Our lightweight security mechanism enables the routing protocol to defend most attacks against sensor networks.

This paper presents an ultra-low-power single-chip sensor-node VLSI for wireless-sensor-network applications. A communication centric design approach has been introduced to reduce the power consumption of the RF circuits and the entire sensor network system, through a vertical cooperative design among circuits, architecture, and communication protocols. The sensor-node LSI features a synchronous media access control (MAC) protocol and integrates a transceiver, i8051 microcontroller, and dedicated MAC processor. The test chip occupies 33 mm2 in a 180-nm CMOS process, including 1.38 M transistors. It dissipates 58.0 µW under a network environment.

In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a dynamic programming based algorithm and prove it is optimal in special cases where the correlation only exists between p immediate adjacent observations.

This paper proposes a sensing system for a behavior detection system using an ultrasonic oscillosensor and an air pressure sensor. The ultrasonic oscillosensor sensor has a cylindrical tank filled with water. It detects the vibration of the target object from the signal reflected from the water surface. This sensor can detect a biological vibration by setting to the bottom bed frame. The air pressure sensor consists of a polypropylene sheet and an air pressure sensor, and detects the pressure information by setting under the bed's mattress. An increase (decrease) in the load placed on the bed is detected by the increase (decrease) in the pressure of the air held in the tube attached to the sheet. We propose a behavior detection system using both sensors, complementally. The system recognizes three states (nobody in bed, keeping quiet in bed, moving in bed) using both sensors, and we detect the behavior before getting out of bed by recognized these states. Fuzzy logic plays a primary role in the system. As the fundamental experiment, we applied the system to five healthy volunteers, the system successfully recognized three states, and detected the behavior before getting out of bed. As the clinical experiment, we applied the system to four elderly patients with dementia, the system exactly detected the behavior before getting out of the bed with enough time for medical care support.

Wireless sensor networks are subject to node and link failures for a variety of reasons. This paper proposes a k-disjoint-path routing algorithm that varies the number of disjoint paths (k) in order to meet a target-delivery ratio of critical events and to reduce energy consumption. The proposed algorithm sends packets to the base station through a single path without the occurrence of critical events, however, it sends packets to the base station through k disjoint paths (k>1) under the occurrence of critical events, where k is computed from a well-defined fault model. The proposed algorithm detects the occurrence of critical events by monitoring collected data patterns. The simulation results reveal that the proposed algorithm is more resilient to random node failure and patterned failure than other routing algorithms, and it also decreases energy consumption much more than the multi-path and path-repair algorithms.

A dynamic coding mechanism is presented to implement distributed signature based IDS (Intrusion Detection System) in IP-USN (IP-based Ubiquitous Sensor Networks). The proposed scheme allows the creation of a lightweight IDS in terms of storage, messaging and energy consumption, which make it appropriate for resource constrained sensor devices.

Energy efficient routing is one of the key design issues to prolong the lifetime of wireless sensor networks (WSNs) since sensor nodes can not be easily re-charged once they are deployed. During routing process, the routes with only few hops or with too many hops are not energy efficient. Hop-based routing algorithms can largely improve the energy efficiency of multi-hop routing in WSNs because they can determine the optimal hop number as well as the corresponding intermediate nodes during multi-hop routing process under medium or high density network. In this paper, we not only focus on studying the relationship between energy consumption and hop number from theoretical point of view but also provide a practical selection criterion of the sub-optimal hop number under practical sensor network so as to minimize the energy consumption. We extend the theoretical deduction of optimal hop number and propose our Hop-based Energy Aware Routing (HEAR) algorithm which is totally distributed and localized. Simulation results show that our HEAR algorithm can reduce the average energy consumption about 10 times compared to the direct transmission algorithm and 2 to 10 times than other algorithms like LEACH and HEED under various network topologies.

In this paper, Cellular Neural Networks using genetic algorithm (GA-CNNs) are designed for CMOS image noise reduction. Cellular Neural Networks (CNNs) could be an efficient way to apply to the image processing technique, since CNNs have high-speed parallel signal processing characteristics. Adaptive CNNs structure is designed for the reduction of Photon Shot Noise (PSN) changed according to the average number of photons, and the design of templates for adaptive CNNs is based on the genetic algorithm using real numbers. These templates are optimized to suppress PSN in corrupted images. The simulation results show that the adaptive GA-CNNs more efficiently reduce PSN than do the other noise reduction methods and can be used as a high-quality and low-cost noise reduction filter for PSN. The proposed method is designed for real-time implementation. Therefore, it can be used as a noise reduction filter for many commercial applications. The simulation results also show the feasibility to design the CNNs template for a variety of problems based on the statistical image model.

The precise noise modeling of complementary metal oxide semiconductor image sensor (CMOS image sensor: CIS) is a significant key in understanding the noise source mechanisms, optimizing sensor design, designing noise reduction circuit, and enhancing image quality. Therefore, this paper presents an accurate random telegraph signal (RTS) noise analysis model and a novel quantitative evaluation method in motion picture for the visual sensory evaluation of CIS. In this paper, two main works will be introduced. One is that the exposure process of a video camera is simulated, in which a Gaussian noise and an RTS noise in pinned-photodiode CMOS pixels are modeled in time domain and spatial domain; the other is that a new video quality evaluation method for RTS noise is proposed. Simulation results obtained reveal that the proposed noise modeling for CIS can approximate its physical process and the proposed video quality evaluation method for RTS noise performs effectively as compared to other evaluation methods. Based on the experimental results, conclusions on how the spatial distribution of an RTS noise affects the quality of motion picture are carried out.

This paper is concerned with the estimation of radio communication distance when both the transmitter and receiver are arbitrarily distributed on a random rough surface such as desert, terrain, sea surface and so on. First, we simulate electromagnetic wave propagation along the rough surface by using the discrete ray tracing method (DRTM) proposed by authors recently. Second, we determine three parameters by conjugate gradient method (CGM) combined with the method of least-squares. Finally, we derive an analytical expression which can estimate the maximum communication distance when the input power of a transmitter and the minimum detectable electric intensity of a receiver are specified. Random rough surfaces are assumed to be Gaussian, pn-th order power law or exponential distributions.