The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.

Packet loss and energy dissipation are two major challenges of designing large-scale wireless sensor networks. Since sensing data is spatially correlated, compressed sensing (CS) is a promising reconstruction scheme to provide low-cost packet error correction and load balancing. In this letter, assuming a multi-hop network topology, we present a CS-oriented data aggregation scheme with a new measurement matrix which balances energy consumption of the nodes and allows for recovery of lost packets at fusion center without additional transmissions. Comparisons with existing methods show that the proposed scheme offers higher recovery precision and less energy consumption on TinyOS.

Recently, the border security systems attract attention as large-scale monitoring system in wireless sensor networks (WSNs). In the border security systems whose aim is the monitoring of illegal immigrants and the information management in long-period, it deploys a lot of sensor nodes that have the communication and sensing functions in the detection area. Hence, the border security systems are necessary to reduce the power consumption of the whole system in order to extend the system lifetime and accurately monitor the track of illegal immigrants. In this paper, we propose two effective barrier coverage construction methods by switch dynamically operation modes of sensor nodes to reduce the operating time of the sensing function that wastes a lot of power consumption. We carry out performance evaluations by computer simulations to show the effectiveness of two proposed methods and show that the proposed methods are suitable for the border security systems.

In general, the sensor network has a many-to-one communication architecture wherein each node transmits its data to a sink. This leads the congested nodes to die early and nodes nears the sink suffer from significant traffic concentrations. In this paper, we propose a cross-layer based routing and MAC protocol which is compatible with the IEEE 802.15.4 standard without additional overhead. The key mechanism is to provide dynamic route discovery and route maintenance operations to avoid and mitigate the most congested nodes by monitoring link status such as link delay, buffer occupancy and residential energy. In addition, the proposed protocol also provides a dynamic tuning of BE (Binary Exponent) and frame retransmission opportunities according to the hop distance to the sink node to mitigate funnel effects. We conducted simulations, verifying the performance over existing protocols.

We propose a natural synchronization scheme for wireless uncoupled devices, without any signal exchange among them. Our proposed scheme only uses natural environmental fluctuations, such as the temperature or humidity of the air, the environmental sounds, and so on, for the synchronization of the uncoupled devices. This proposed synchronization is realized based on the noise-induced synchronization phenomenon, uncoupled nonlinear oscillators synchronize with each other only by adding identical common noises to each of them. Based on the theory of this phenomenon, the oscillators can also be synchronized by noise sequences, which are not perfectly identical signals. Since the environmental natural fluctuations collected at neighboring locations are similar to each other and cross-correlation becomes high, our proposed scheme enabling synchronization only by natural environmental fluctuations can be realized. As an application of this proposed synchronization, we introduce wireless sensor networks, for which synchronization is important for reducing power consumption by intermittent data transmission. We collect environmental fluctuations using the wireless sensor network devices. Our results show that the wireless sensor network devices can be synchronized only by the independently collected natural signals, such as temperature and humidity, at each wireless sensor device.

In wireless sensor networks, energy depletion of bottleneck nodes which have more data packets to relay than others, dominates the network lifetime referred to as the funnel effect problem. To overcome this problem, multiple sink methods have been proposed where sensor nodes send observed data packets toward several sinks to distribute traffic load of bottleneck nodes. If both of the topology and the traffic pattern are symmetric, bottleneck nodes are located near sinks. However, in a general sensor network with an asymmetric topology and/or an asymmetric traffic pattern, bottleneck nodes may exist any place in the network. In this paper, we propose DCAM (DispersiveCast of packets to Avoid bottleneck nodes for Multiple sink sensor network), which is a load balancing method to improve lifetime of a sensor network with an asymmetric topology and an asymmetric traffic pattern. DCAM first finds bottleneck nodes, and then balances the load on the bottleneck nodes. Selected nodes send data packets to several sinks dispersively according to some criteria. The criteria classify DCAM into three variations: DCAM with probability (DCAM-P), DCAM with moving boarder (DCAM-MB), and DCAM with round-robin (DCAM-RR). This paper gives details of the DCAM methods, and thereafter evaluates them with asymmetric topologies and asymmetric traffic patterns. To deal with these dynamic asymmetry, the topology is modeled by a grid network with virtual holes that are defined as vacant places of nodes in the network. Asymmetry of traffic pattern is modeled by defining a hot area where nodes have heavier data traffic than the others. The evaluations are conducted as changing hot-area traffic patterns as well as fixing hot-area patterns. The results show that DCAM improves network lifetime up to 1.87 times longer than the conventional schemes, (i.e., nearest sink transmissions and optimal dispersive cast of packet). We also discuss DCAM on several aspects such as overhead, energy consumption, and applications.

Wireless sensor network (WSN) using network coding is vulnerable to pollution attacks. Existing authentication schemes addressing this attack either burden the sensor node with a higher computation overhead, or fail to provide an efficient way to mitigate two recently reported attacks: tag pollution attacks and repetitive attacks, which makes them inapplicable to WSN. This paper proposes an efficient hybrid cryptographic scheme for WSN with securing network coding. Our scheme can resist not only normal pollution attacks, but the emerging tag pollution and repetitive attacks in an efficient way. In particular, our scheme is immediately suited for distributing multiple generations using a single public key. Experimental results show that our scheme can significantly improve the computation efficiency at a sensor node under the two above-mentioned attacks.

Many applications of wireless sensor networks (WSNs) require secure communication. The tree-based key management scheme, which is a symmetric key scheme, provides backward and forward secrecy. The sensor nodes in the communication group share a secret key for encrypting messages. When the sensor nodes are added to or evicted from the group, the group key has to be updated by sending rekeying messages. In this paper, we propose a method of key tree structure (KTS) generation by considering the addition and eviction ratio of sensor nodes to reduce the number of rekeying messages, which is influenced by the structure of the tree. For this, we define an extension of an existing tree structure such as a binary or ternary tree and generate KTS using an A* algorithm. To reduce the energy consumed by the message transmission, we also exploit genetic algorithm (GA) to build a secure communication group by considering the KTS. In the paper, we show the effectiveness of the proposed method compared with the existing structure via the simulation in terms of memory usage, the number of rekeying messages and energy consumption.

In this letter, a distributed TDMA-based data gathering scheme for wireless sensor networks, called DTDGS, is proposed in order to avoid transmission collisions, achieve high levels of power conservation and improve network lifetime. Our study is based on corona-based network division and a distributed TDMA-based scheduling mechanism. Different from a centralized algorithm, DTDGS does not need a centralized gateway to assign the transmission time slots and compute the route for each node. In DTDGS, each node selects its transmission slots and next-hop forwarding node according to the information gathered from neighbor nodes. It aims at avoiding transmission collisions and balancing energy consumption among nodes in the same corona. Compared with previous data gathering schemes, DTDGS is highly scalable and energy efficient. Simulation results show high the energy efficiency of DTDGS.

Reprogramming for wireless sensor networks is essential to upload new code or to alter the functionality of existing code. To overcome the weakness of the centralized approach of the traditional solutions, He et al. proposed the notion of distributed reprogramming where multiple authorized network users are able to reprogram sensor nodes without involving the base station. They also gave a novel distributed reprogramming protocol called SDRP by using identity-based signature, and provided a comprehensive security analysis for their protocol. In this letter, unfortunately, we demonstrate that SDRP is insecure as the protocol fails to satisfy the property of authenticity and integrity of code images, the most important security requirement of a secure reprogramming protocol.

Recently, environmental monitoring applications or home automation systems often deal with wireless sensor data. These applications deal with multi-dimensional sensing data and most processing operations involves skyline queries. In this paper, we focus on skyline queries in WSNs. However, as the number of data dimensions increases, the results of skyline queries become unmanageably large which reduces the lifetime of the sensor network. To solve these problems, we propose a novel k-dominant skyline query processing method using filtering mechanisms. The filter is designed by considering the data property and the data transmission cost. Extensive experiments show that our proposed method results in significant performance improvements over the existing method.

Optimizing lifetime of a wireless sensor network has received considerable attention in recent years. In this paper, using the feasibility and simplicity of grid-based clustering and routing schemes, we investigate optimizing lifetime of a two-dimensional wireless sensor network. Thus how to determine the optimal grid sizes in order to prolong network lifetime becomes an important problem. At first, we propose a model for lifetime of a grid in equal-grid model. We also consider that nodes can transfer packets to a grid which is two or more grids away in order to investigate the trade-off between traffic and transmission energy consumption. After developing the model for an adjustable-grid scenario, in order to optimize lifetime of the network, we derive the optimal values for dimensions of the grids. The results show that if radio ranges are adjusted appropriately, the network lifetime in adjustable-grid model is prolonged compared with the best case where an equal-grid model is used.

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.

Duty-cycle MAC protocols achieve high energy-efficiency. However, duty-cycle MACs introduce significant end-to-end delivery latency. Recently proposed protocols such as RMAC and PRMAC improve the latency of duty-cycle MAC protocols by employing a mechanism of multi-hop wakeup reservation to allow a packet to be forwarded over multiple hops in a single communication cycle. However, these protocols can not efficiently handle cross traffic bursts which are common in applications with space-correlated event detection. If there are multiple packets to send in each flow, most of the data packets will be seriously postponed. This paper proposes a multi-channel pipelined routing-enhanced MAC protocol, called MPR-MAC, to handle this problem. By jointly employing channel diversity and time diversity, MPR-MAC allows cross data flows to forward multiple packets respectively in a single communication cycle without interfering with each other. Simulation results show the advantage of MPR-MAC in handling cross data flows and the significant performance upgrade in terms of end-to-end latency and energy efficiency.

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 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.

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.

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.

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.