We consider how to accurately estimate the position of targets that exist in closed areas such as a room. In the past, arranging the sensors in a straight line would trigger large position estimation errors in the same direction of the straight line. However, this arrangement is useful because of easy setting, wirings, and space limitations. In this paper, we show a novel algorithm which can reduce the error using signals from reflection objects such as walls. The algorithm uses ellipse relations among sensors, targets and reflection points. Using ellipse relations, the algorithm estimates the positions of the reflection points which are assumed to be the locations of the virtual sensors. So in spite of the straight sensor arranging, the sensors are virtually distributed such as surrounding the targets. In this paper, we show the algorithm and error reduction performances as determined from computer simulations.

In the received signal strength-based ranging algorithms, distance is estimated from a path loss model, in which the path loss exponent is considered a key parameter. The conventional RSS-based algorithms generally assume that the path loss exponent is known a priori. However, this assumption is not acceptable in the real world because the channel condition depends on the current wireless environment. In this paper, we propose an accurate estimation method of the path loss exponent that results in minimizing distance estimation errors in varying environments. Each anchor node estimates the path loss exponent for its transmission coverage by the sequential rearrangement of the received signal strengths of all sensor nodes within its coverage. Simulation results show that the proposed method can accurately estimate the actual path loss exponent without any prior knowledge and provides low distance estimation error.

This paper presents the design and performance evaluation of a power-controlled topology optimization and channel assignment scheme for Hybrid MAC (abbreviated PTOCA) in wireless sensor networks that require comparatively high data rate communications. In order to maximize the network performance, PTOCA is designed with a cross-layer concept of MAC and network layers, which provides multi-channel TDMA scheduling based on the information of the network topology optimized by transmission power control. The simulation results show that by using the proposed scheme, the network throughput and energy efficiency can be significantly improved. PTOCA is also more effective in improving the network performance when the nodes are uniformly deployed on the sensor field rather than when they are randomly distributed.

Temporal and spatial (geographical) fluctuations, which are present in the traffic of wireless sensor networks (WSNs), have a significant affect on the transmission performance and power consumption of WSNs. Several medium access control (MAC) mechanisms have been proposed for IEEE802.15.4 cluster-based WSNs to counter the temporal and spatial traffic fluctuations. However, these mechanisms cannot always achieve simultaneous improvement in both transmission performance and power consumption. In this paper, we propose two enhanced 2-level active period control mechanisms, BI&CAP control and BI&SD&CAP control, to achieve higher system performance than conventional control mechanisms. Various computer simulation results demonstrate the effectiveness of the proposed mechanisms for WSNs with various traffic fluctuations.

Wireless Sensor Networks (WSNs) are gradually moving toward the adoption of clustered heterogeneous designs, incorporating a mixture of variety kinds of sensor nodes with different radio coverage and battery capacity. Compared with homogeneous networks, heterogeneous networks are able to reduce the initial cost of the network or prolong the network lifetime. The architecture and routing protocol for this type of heterogeneous WSN should be energy aware in order to prolong the lifetime of the network. However, most of the existing clustering methods consider only initial energy of the sensor nodes and ignore the non-uniform energy drainage caused by many-to-one traffic near sink and/or cluster heads in heterogeneous network environment. In this paper, we propose a new clustering method for WSN with heterogeneous node types which selects cluster heads considering not only the transmission power and residual energy of each node but also those of its adjacent nodes. Simulation experiments show that the proposed method increases network lifetime by 80% and 60% more than that of the CC and HEED, respectively.

This paper proposed a novel platform for sensor nodes to resolve the energy and latency challenges. It consists of a processor, an adaptive compressing module and several compression accelerators. We completed the proposed chip in a 0.18µm HJTC CMOS technology. Compared to the software-based solution, the hardware-assisted compression reduces over 98% energy and 212% latency. Besides, we balanced the energy and latency metric using an adaptive module. According to the scheduling algorithm, the module tunes the state of the compression accelerator, as well as the sampling frequency of the online sensor. For example, given a 9µs constraint for a 1-byte operation, it reduces 34% latency while the energy overheads are less than 5%.

Traffic adaptive 2-level active period control has been proposed to enhance system performance in cluster-based wireless sensor networks (WSNs) employing IEEE 802.15.4 medium access control (MAC) under temporal and spatial (geographical) non-uniform traffic environments. This paper proposes an adaptive method of controlling the backoff window for traffic adaptive 2-level active period control. The proposed method adjusts the size of the backoff window according to the length of the current active period, which is determined by 2-level active period control, and the time position for channel access in the active period. The results evaluated through computer simulations reveal that the proposed method can improve throughput as well as achieve high energy efficiency in cluster-based WSNs with non-uniform traffic distributions.

Many methods have been researched to prolong the lifetime of sensor networks that use mobile technologies. In the mobile sink research, there are the track based methods and the anchor points based methods as representative operation methods for mobile sinks. However, most existing methods decrease the Quality of Service (QoS) and lead to routing hotspots in the vicinity of the mobile sinks. The main reason is that they use static mobile sink movement paths that ignore the network environment such as the query position and the data priority. In this paper, we propose a novel mobile sink operation method that solves the problems of the existing methods. In our method, the probe priority of the mobile sink is determined from data priority to increase the QoS. The mobility of sink used to reduce the routing hotspot. Experiments show that the proposed method reduces the query response time and improves the network lifetime much more than the existing methods.

These days, cheap and intelligent sensors, networked through wireless links and deployed in large numbers, provide unprecedented opportunities for monitoring and controlling homes, cities and the environment. Networked sensors also offer a broad range of applications. Localization capability is essential in most wireless sensor networks applications; for instance in environmental monitoring applications such as animal habitat monitoring, bush fire surveillance, water quality monitoring and precision agriculture, the measurement data are meaningless without accurate knowledge of where they are obtained. Localization techniques are used to determine location information by estimating the location of each sensor node. Distance measurement errors are commonly known to affect the accuracy of the estimated location; resulting in errors that may be due to inherent or environmental factors. Trilateration [1] is a well-known method for localizing nodes by using the distances to three anchor nodes; yet it performs poorly when they are many distance measurement errors. Therefore, we propose the LRD (Localization with Ratio-Distance) algorithm, which performs strongly even in the presence of many measurement errors associated with the estimated distance to anchor nodes. Simulations using the OPNET Modeler show that LRD is more accurate than trilateration.

This paper addresses the problem of sensor selection in wireless sensor networks (WSN) subject to a distortion constraint. To do so, first, a cost function is derived based on the spatial correlation obtained using the best estimation of the event source. Then, a new adaptive algorithm is proposed in which the number of active sensors is adaptively determined and the best topology of the active set is selected based on the add-one-sensor-node-at-a-time method. Simulations results show that the active sensors selected using the proposed cost function have less event distortion. Also, it is shown that the proposed sensor selection algorithm is near optimum and it has better performance than other algorithms with regard to the computational burden and distortion.

Wireless sensor networks (WSN) is composed of so many small sensor nodes which have limited resources. So the technique that raises energy efficiency is the key to prolong the network life time. In the paper, we propose an agent based framework which takes the biological characteristics of gene. The gene represents an operation policy to control agent behavior. Agents are aggregated to reduce duplicate transmissions in active period. And it selects next hop based on the information of neighbor agents. Among neighbors, the node which has enough energy is given higher priority. The base station processes genetic evolution to refine the behavior policy of agent. Each agent is taken latest gene and spread recursively to find the optimal gene. Our proposed framework yields sensor nodes that have the properties of self-healing, self-configuration, and self-optimization. Simulation results show that our proposed framework increases the lifetime of each node.

Existing time synchronization schemes in sensor networks were all developed to be energy-efficient, precise, and robust, but none of them were developed with security in mind. We have developed a secure, accurate and energy-efficient time synchronization protocol (SAEP). SAEP achieves accurate time synchronization service with significantly reducing the number of message exchanges. Also, it safeguards against Byzantine failure, in which nodes drop, modify, or delay time information in an attempt to disrupt the time synchronization service in multi-hop networks. SAEP takes a distributed approach where each sensor independently makes decisions based only on the information collected from multiple adjacent nodes, thus achieving a high level of resistance to various attacks while minimizing the energy cost. We investigate the misbehavior of a maliciously compromised node and analyze how SAEP can combat these attacks. In our experiment SAEP outperforms the existing time synchronization protocol in accuracy, energy consumption and it is even resilient to multiple capture attacks.

In ubiquitous sensor networks, extra energy savings can be achieved by selecting the filtering solution to counter the attack. This adaptive selection process employs a fuzzy rule-based system for selecting the best solution, as there is uncertainty in the reasoning processes as well as imprecision in the data. In order to maximize the performance of the fuzzy system the membership functions should be optimized. However, the efforts required to perform this optimization manually can be impractical for commonly used applications. This paper presents a GA-based membership function optimizer for fuzzy adaptive filtering (GAOFF) in ubiquitous sensor networks, in which the efficiency of the membership functions is measured based on simulation results and optimized by GA. The proposed optimization consists of three units; the first performs a simulation using a set of membership functions, the second evaluates the performance of the membership functions based on the simulation results, and the third constructs a population representing the membership functions by GA. The proposed method can optimize the membership functions automatically while utilizing minimal human expertise.

A sensor network consisting of a number of palm-sized nodes with small electric and magnetic sensors has been proposed to monitor local electromagnetic activities in space plasmas. In the present study, a compact loop antenna system is designed and fabricated for use in sensor nodes that can capture magnetic vector fields from ELF to MF frequencies. The performance of the developed system is shown to be sufficient to allow measurement of the magnetic field activity around artificial structures in addition to intense natural plasma waves in geospace.

Secure access is one of the key concerns of wireless sensor networks (WSNs). In WSNs, because there are many dynamically mutable attributes, continuous access decisions and dynamic attribute updates should be important properties of access control. In addition, WSNs need low-complexity authentication protocols because of the constrained resources. However, the authentication protocols of most current security access schemes have relatively high complexity. More importantly, the access control models of existing schemes cannot provide attribute mutability and continuous decisions dynamically. To address above issues, we propose a dynamic secure access mechanism for WSNs. Firstly, we design a lightweight secure authentication protocol and dynamic access control based on security token and usage control (UCON), respectively. Then, the agent technology is adopted to implement the proposed secure access scheme. Secondly, we analyze the probability of the dynamic attribute update and decisions. Thirdly, we implement an instance of UCON. The implementation results indicate the feasibility of using UCON in WSNs. Finally, by evaluating and comparing with current schemes, the authentication protocol in our scheme presents several advantages including the low expenses in calculation, storage and communication. To our best knowledge, this paper is the first to realize next generation dynamic access control with attribute mutability and continuous decisions in WSNs.

A micro-power active-RFID LSI with an all-digital RF-transmitting scheme achieves experimental 10-m-distance communication with a 1-Mbps data rate in the 300-MHz frequency band. The IC consists of an RF transmitter and a power supply circuit. The RF transmitter generates wireless signals without a crystal. The power supply circuit controls the energy flow from the battery to the IC and offers intermittent operation of the RF transmitter. The IC draws 1.6 µA from a 3.4-V supply and is implemented in a 0.2-µm CMOS process in an area of 1 mm2. The estimated lifetime of the IC is over ten years with a coin-size battery.

This letter proposes a novel decision fusion algorithm for cooperative spectrum sensing in cognitive radio sensor networks where a reinforcement learning algorithm is utilized at the fusion center to estimate the sensing performance of local spectrum sensing nodes. The estimates are then used to determine the weights of local decisions for the final decision making process that is based on the Chair-Vashney optimal decision fusion rule. Simulation results show that the sensing accuracy of the proposed scheme is comparable to that of the Chair-Vashney optimal decision fusion based scheme even though it does not require any knowledge of prior probabilities and local sensing performance of spectrum sensing nodes.

In the present paper, we propose an object tracking method called scenario-type hypothesis object tracking. In the proposed method, an indoor monitoring region is divided into multiple closed micro-cells using sensor nodes that can detect objects and their moving directions. Sensor information is accumulated in a tracking server through wireless multihop networks, and object tracking is performed at the tracking server. In order to estimate the trajectory of objects from sensor information, we introduce a novel concept of the virtual world, which consists of virtual micro-cells and virtual objects. Virtual objects are generated, transferred, and deleted in virtual micro-cells according to sensor information. In order to handle specific movements of objects in micro-cells, such as slowdown of passing objects in a narrow passageway, we also consider the generation of virtual objects according to interactions among virtual objects. In addition, virtual objects are generated when the tracking server estimates loss of sensor information in order to decrease the number of object tracking failures. Through simulations, we confirm that the ratio of successful tracking is improved by up to 29% by considering interactions among virtual objects. Furthermore, the tracking performance is improved up to 6% by considering loss of sensor information.

We describe a parameter estimation method for a target object in an area that sensors monitor. The parameters to be estimated are the perimeter length, size, and parameter determined by the interior angles of the target object. The estimation method does not use sensor location information, only the binary information on whether each sensor detects the target object. First, the sensing area of each sensor is assumed to be line-segment-shaped, which is a model of an infrared distance measurement sensor. Second, based on the analytical results of assuming line-segment-shaped sensing areas, we developed a unified equation that works with general sensing areas and general target-object shapes to estimate the parameters of the target objects. Numerical examples using computer simulation show that our method yields accurate results.

In this work, an ultra-wideband impulse radio (UWB-IR) transceiver with accurate time-of-arrival (TOA) estimation for a ranging/positioning system was developed for wireless sensor network applications. The system uses an impulse radio characterized by a low duty cycle and direct-sequence spreading, which enable very precise ranging and good receiver sensitivity. An algorithm enabling the TOA of the first-path signal to be measured accurately in a multi-path environment with simple, low-power and low cost implementations was proposed. UWB chips with CMOS 0.18-µm technology and UWB transceiver modules performed that the accuracy of the proposed ranging system is 18.5 cm in a closed space.