Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.

This paper introduces the basics of energy harvesters and demonstrates two specific vibratory-type energy harvesters developed at the University of Hyogo. The fabrication and evaluation results of the vibratory-type energy harvesters, which employ electrostatic and electromagnetic mechanisms, are described. The aim of developing these devices is to realize a power source for an autonomous human monitoring system. The results of harvesting from actual human activities obtained using a data logger are also described. Moreover, challenges in the power management of electronic circuitry used for energy harvesting are briefly discussed.

We have developed a dedicated onboard “sensor” utilizing wireless communication devices for collision avoidance around road intersections. The “sensor” estimates the positions of transmitters on traffic participants by comparing the strengths of signals received by four ZigBee receivers installed at the four corners of a vehicle. On-board sensors involving cameras cannot detect objects in non line-of-sight (NLOS) area caused by buildings and other vehicles. Although infrastructure sensors for vehicle-to-infrastructure (V2I) cooperative systems can detect such hidden objects, they are substantially more expensive than on-board sensors. The on-board wireless “sensor” developed in this work would function as an alternative tool for collision avoidance around intersections. Herein, we extend our previous work by considering a road surface reflection model to improve the estimation accuracy. By using this model, we succeeded in reducing the error mismatches between the observed data and the calibration data of the estimation algorithm. The proposed system will be realized on the basis of these enhancements.

Existing MANET routing protocols may not be efficient for mobile sensor networks (MSNs) since they generate too much control traffic by relying on flooding or route maintenance messages. Furthermore, peer-to-peer communication patterns assumed in MANET would exacerbate the traffic around sink nodes in MSNs. In this paper we propose traffic adaptive routing (TAR) for MSNs; it can reduce the control packets by analyzing and predicting the source, volume, and the patterns of both traffic and mobility. Through its analysis and the prediction of mobility, TAR also copes with dynamic topology changes by carrying out a fast route recovery process. Our theoretical analysis shows that TAR can effectively reduce unnecessary control packet flooding by 53% on average when compared to AODV. We implement TAR on NS-2. Our experimental evaluation confirms that TAR can not only improve the network and energy performance for MSNs but also can be a practical routing solution for MANET and WSNs compared to the existing ad hoc routing protocols.

The noise in digital images acquired by image sensors has complex characteristics due to the variety of noise sources. However, most noise reduction methods assume that an image has additive white Gaussian noise (AWGN) with a constant standard deviation, and thus such methods are not effective for use with image signal processors (ISPs). To efficiently reduce the noise in an ISP, we estimate a unified noise model for an image sensor that can handle shot noise, dark-current noise, and fixed-pattern noise (FPN) together, and then we adaptively reduce the image noise using an adaptive Smallest Univalue Segment Assimilating Nucleus ( SUSAN ) filter based on the unified noise model. Since our noise model is affected only by image sensor gain, the parameters for our noise model do not need to be re-configured depending on the contents of image. Therefore, the proposed noise model is suitable for use in an ISP. Our experimental results indicate that the proposed method reduces image sensor noise efficiently.

A variety of ubiquitous computing devices, such as radio frequency identification (RFID) and wireless sensor network (WSN), are generating huge and significant events that should be rapidly processed for business excellence. In this paper, we describe how complex event processing (CEP) technology can be applied to ubiquitous process management based on context-awareness. To address the issue, we propose a method for context-aware event processing using event processing language (EPL) statement. Specifically, the semantics of a situation drive the transformation of EPL statement templates into executable EPL statements. The proposed method is implemented in the domain of ubiquitous cold chain logistics management. With the proposed method, context-aware event processing can be realized to enhance business performance and excellence in ubiquitous computing environments.

This paper presents a low-power LDPC decoder that can be used in Multimedia Wireless Sensor Networks. Three low power design techniques are proposed in the decoder design: a layered decoding algorithm, a modified Benes network and a modified memory bypassing scheme. The proposed decoder is implemented in TSMC 0.13 µm, 1.2 V CMOS process. Experiments show that when the clock frequency is 32 MHz, the power consumption of the proposed decoder is 38.4 mW, the energy efficiency is 53.3 pJ/bit/ite and the core area is 1.8 mm2.

In Wireless Sensor Networks (WSNs), sensor nodes consume their limited battery energy to send and receive data packets for data transmission. If some sensor nodes transmit data packets more frequently due to imbalance in the network topology or traffic flows, they experience higher energy consumption. And if the sensor nodes are not recharged, they will be turned off from the lack of battery energy which will degrade network sustainability. In order to resolve this problem, this paper proposes an Energy-aware MAC Protocol (EMP), which adaptively decides on the size of the channel polling cycle consisting of the sleep state (not to communicate with its target node) and the listening state (to awaken to receive data packets), according to the network traffic condition. Moreover, in accordance with the remaining energy state of the sensor node, the minimum size of the channel polling cycle is increased for better energy saving. For performance evaluation and comparison, we develop a Markov chain-based analytical model and an event-driven simulator. Simulation results show that a sensor node with EMP effectively reduces its energy consumption in imbalanced network condition and traffic flows, while latency somewhat increases under insufficient remaining energy. As a consequence, a holistic perspective for enhanced network sustainability can be studied in consideration of network traffic condition as well as the remaining energy states of sensor nodes.

In this paper, performances of two different virtual multiple-input multiple-output (MIMO) transmission schemes — spatial multiplexing (SM) and space-time block coding (STBC) — in a correlated wireless sensor network are analyzed. By utilizing a complex Wishart distribution, we investigate the statistical properties of a correlated virtual MIMO channel between the sensors and data collector that is used in the performance analysis of each MIMO transmission mode. Distributed sensors then transmit their data cooperatively to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and spatial correlation among the sensors. Furthermore, after analyzing the energy efficiencies of SM and STBC, we propose a new energy efficient mode switching rule between SM and STBC. Finally, by analytically deriving the required transmit energy of the proposed adaptive transmission scheme, the manner in which the spatial correlation influences the energy consumption is shown. This suggests a cooperating node scheduling protocol that makes energy consumption less sensitive to the variation of the spatial correlation.

Design of acoustic modem becomes increasingly important in underwater sensor networks' development. This paper presents the design of a reconfigurable acoustic modem, by defining modulation and demodulation as reconfigurable modules, the proposed modem changes its modulation scheme and data rate to provide reliable and energy efficient communication. The digital system, responsible for signal processing and control, is implemented on Xilinx Virtex5 FPGA. Hardware and software co-verification shows that the modem works correctly and can self-configure to BFSK and BPSK mode. Partial reconfiguration design method improves flexibility of algorithm design, and slice, LUT, register, DSP, RAMB are saved by 17%, 25%, 22%, 25%, 25% respectively.

With the increased deployment of wireless sensor networks (WSNs) in location-based services, the need for accurate localization of sensor nodes is gaining importance. Sensor nodes in a WSN localize themselves with the help of anchors that know their own positions. Some anchors may be malicious and provide incorrect information to the sensor nodes. In this case, accurate localization of a sensor node may be severely affected. In this study, we propose a secure and lightweight localization method. In the proposed method, uncertainties in the estimated distance between the anchors and a sensor node are taken into account to improve localization accuracy. That is, we minimize the weighted summation of the residual squares. Simulation results show that our method is very effective for accurate localization of sensor nodes. The proposed method can accurately localize a sensor node in the presence of malicious anchors and it is computationally efficient.

Many broadcast encryption schemes have been proposed for conventional networks. However, those schemes are not suitable for wireless sensor networks, which have very limited resources such as communication, computation, and storage. In this paper, we propose an efficient and practical identity-based broadcast encryption scheme for sensor networks by exploiting the characteristics of sensor networks: in the deployment stage, the set of neighboring sensor nodes are determined and most communications are conducted among the neighbors due to radio power limitations of the nodes. The proposed scheme features the following achievements: (1) all of the public keys and private keys are of constant size; (2) it satisfies all the security requirements for sensor networks. The proposed scheme is optimal in the sense that it requires no pairing operation when adopting pre-computation.

In many wireless sensor applications, skyline monitoring queries that continuously retrieve the skyline objects as well as the complete set of nodes that reported them play an important role. This paper presents SKYMON, a novel energy-efficient monitoring approach. The basic idea is to prune nodes that cannot yield a skyline result at the sink, as indicated by their (error bounded) prediction values, to suppress unnecessary sensor updates. Every node is associated with a prediction model, which is maintained at both the node and the sink. Sensors check sensed data against model-predicted values and transmit prediction errors to the sink. A data representation scheme is then developed to calculate an approximate view of each node's reading based on prediction errors and prediction values, which facilitates safe node pruning at the sink. We also develop a piecewise linear prediction model to maximize the benefit of making the predictions. Our proposed approach returns the exact results, while deceasing the number of queried nodes and transferred data. Extensive simulation results show that SKYMON substantially outperforms the existing TAG-based approach and MINMAX approach in terms of energy consumption.

This article describes the frequency response and the applications of the optical electric-field sensor consisting of a 1 mm1 mm1 mm CdTe crystal mounted on the tip of an optical fiber, which theoretically possesses the potential to cover the frequency band from below megahertz to terahertz. We utilize a capacitor, GTEM-Cell, and standard gain horn antennas for applying a free-space electric field to the optical sensor at frequencies from 20 kHz to 1 GHz, from 1 GHz to 18 GHz, and from 10 to 180 GHz, respectively. An electric-field measurement demonstrates its flat frequency response within a 6-dB range from 20 kHz to 50 GHz except for the resonance due to the piezo-electric effect at a frequency around 1 MHz. The sensitivity increases due to the resonance of the radio frequency wave propagating in the crystal at the frequencies higher than 50 GHz. These experimental results demonstrate that the optical electric-field sensor is a superior tool for the wide-band measurement which is impossible with conventional sensors such as a dipole, a loop, and a horn antenna. In transient electrostatic discharge measurements, electric-field mapping, and near-field antenna measurements, the optical electric-field sensor provide the useful information for the deterioration diagnosis and the lifetime prognosis of electric circuits and devices. These applications of the optical electric-field sensor are regarded as promising ways for sowing the seeds of evolution in electric-field measurements for antenna measurement, EMC, and EMI.

Multi-sensory communications with haptics attract a number of researchers in recent years. To provide services of the communications with high realistic sensations, the researchers focus on the quality of service (QoS) control, which keeps as high quality as possible, and the quality of experience (QoE) assessment, which is carried out to investigate the influence on user perception and to verify the effectiveness of QoS control. In this paper, we report the present status of studies on multi-sensory communications with haptics. Then, we divide applications of the communications into applications in virtual environments and those in real environments, and we mainly describe collaborative work and competitive work in each of the virtual and real environments. We also explain QoS control which is applied to the applications and QoE assessment carried out in them. Furthermore, we discuss the future directions of studies on multi-sensory communications.

In this paper, to provide scalability and mobility of sinks and events, we propose a new independent structure-based routing protocol which exploits a k-level Independent Grid Structure (IGS) for data dissemination from sources to sinks. Beside the k-level IGS, the proposed protocol does not to construct any additional routing structure irrespective of the number and the movement of both sinks and events. The proposed protocol also allows query or report packets to be sent to only a few grid headers in the k-level IGS and provides aggregation and multicasting of report packets by the k-level IGS. Simulation results show that the proposed protocol is superior to other protocols regarding to energy-efficiency.

In this paper we propose MR-MAC, a new multiple reservation MAC protocol for asynchronous duty cycling wireless sensor networks. In MR-MAC, the receiver transmits a collection packet to the senders when it wakes up that asks for the number of packets each sender wants to send. Then each sender replies to the receiver according to the scheduled sequence with a short report packet. After getting the number of packets from each sender, the receiver assigns multiple batch transmission (MBT) for the senders and begins to initiate the transmissions. The senders then transmit packets to the receiver in a batch style as scheduled so that packets can be delivered to the receiver as fast as possible. Experiments on a Tmote-sky testbed show that our protocol outperforms other protocols in diverse performance metrics such as throughput, latency and energy efficiency.

To reduce the power dissipation of the receiver in accordance with the intensity of the received signal, we developed the first intra-symbol intermittent (ISI) radio-frequency (RF) front end with 0.35-µm CMOS technology. In the demodulation mechanism, the RF output of the low-noise amplifier (LNA) is down-converted to an intermediate frequency (IF) by the mixer, and the LNA and mixer operate synchronously and intermittently within the length of a single symbol. Because the time-averaged power consumption is proportional to the operating time, the demodulation can be performed with low power by making the total operating time short. We experimentally demonstrate that demodulation (BPSK: 9.6 kbps) is properly achieved with the operating-time ratio of 12%. This ISI operation of the RF front end is enabled by a newly devised fast-transition LNA and mixer. A theoretical analysis of aliasing noise reveals that RF ISI operation is more useful than current-control with continuous operation and that an operating-time ratio of 10% is optimal.

This paper proposes a distributed TDMA slot scheduling algorithm with power control, which the slot allocation priority is controlled by distance measurement information. In the proposed scheme, Lamport's bakery algorithm for mutual exclusion is applied for prioritized slot allocation based on the distance measurement information between nodes, and a packet-based transmission power control scheme is combined. This aims at achieving media access control methods which can construct a local network practically by limiting the scope. The proposed scheme can be shown as a possible replacement of DRAND algorithm for Z-MAC scheme in a distance-measurement-oriented manner. The scheme can contribute to the efficient TDMA slot allocation.

In this paper, we present Greedy Routing for Maximum Lifetime (GRMax) [1],[2] which can use the limited energy available to nodes in a Wireless Sensor Network (WSN) in order to delay the dropping of packets, thus extend the network lifetime. We define network lifetime as the time period until a source node starts to drop packets because it has no more paths to the destination [3]. We introduce the new concept of Network Connectivity Aiming (NCA) node. The primary goal of NCA nodes is to maintain network connectivity and avoid network partition. To evaluate GRMax, we compare its performance with Geographic and Energy Aware Routing (GEAR) [4], which is an energy efficient geographic routing protocol and Greedy Perimeter Stateless Routing (GPSR) [5], which is a milestone among geographic routing protocol. We evaluate and compare the performance of GPSR, GEAR, and GRMax using OPNET Modeler version 15. The results show that GRMax performs better than GEAR and GPSR with respect to the number of successfully delivered packets and the time period before the nodes begin to drop packets. Moreover, with GRMax, there are fewer dead nodes in the system and less energy is required to deliver packets to destination node (sink).