Wireless Sensor and Actor Networks (WSAN) are commonly used to monitor physical parameters and execute opportune actions in response to specific events. In order to achieve this goal it is necessary to implement efficient coordination and cooperation among the network nodes (i.e. sensors and actors) with the aim of reducing the energy consumption and improving the response time of the system. This work propose a clustering mechanism that organizes the sensor nodes to form clusters where the mobile actors nodes in the WSAN perform the cluster head role. The proposal considers the mobility aspect of the actor nodes and implements a mechanism to dynamically change the geographical location of the actors while trying to reduce the load in terms of the number of sensors within each cluster, all this with the aim of extending the network lifetime.

In sensor networks, many studies have been proposed to process in-network aggregation efficiently. Unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. Therefore, it is very difficult to process the skyline queries in sensor networks. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approaches get rid of unnecessary data transmission by deploying filters to whole sensors. However, network lifetime is reduced due to energy consumption for transmitting filters. In this paper, we propose a lazy filtering-based in-network skyline query processing algorithm to reduce energy consumption by transmitting filters. Our algorithm creates the skyline filter table (SFT) in the data gathering process which sends data from sensor nodes to the base station and filters out unnecessary data transmissions using it. The experimental results show that our algorithm reduces false positive by 53% and improves network lifetime by 44% on average over the existing method.

In this letter, we discuss a forwarding method for maximizing network lifetime, which combines multi-hop forwarding and direct forwarding with a direct/multi-hop forwarding ratio of each sensor node. The direct forwarding ratio refers to the forwarding amount ratio of sensor nodes' own data directly towards a sink node in one packet/instance data generation rate. We tackle an optimization problem to determine the direct forwarding ratio of each sensor node, maximizing network lifetime, as well as nearly guaranteeing energy consumption balancing characteristics. The optimization problem is tackled through the Lagrange multiplier approach. We found that the direct forwarding ratio is overall inversely proportional to the increase of node index in h < i ≤ N case. Finally, we compare energy consumption and network lifetime of the proposed forwarding method with other existing forwarding methods. The numerical results show that the proposed forwarding method balances energy consumption in most of the sensor nodes, comparing with other existing forwarding methods, such as multi-hop forwarding and direct forwarding. The proposed forwarding method also maximizes network lifetime.

Sensor network terminals are installed in large numbers in field, and they transmit data periodically by radio. Such terminals must be miniaturized, and power must be saved so that each device can be operated by battery for several years. As one way to satisfy these two conditions, in this research we propose a terminal design that eliminates the receiver circuit. Because there is no receiver circuit, circuitry can be miniaturized, and power can be saved because there is no need to consume power to receive signals. However, the terminals cannot perform carrier detection and reception acknowledgement because there is no receiver circuit. We propose following two new protocols to solve this problem.1. Terminal transmission times are randomized to prevent frequent collisions between specific terminals due to the lack of carrier detection. 2. Since all packet losses due to collision cannot be prevented with (1), data from a number of past transmissions is included in each packet so that a later packet can provide transmission data even if a packet is lost.In this report, we describe the proposed protocol, and evaluate its performance by simulation. Furthermore, we actually prototype the system and evaluate the prototype's performance.

In-network data aggregation is one of the most important issues for achieving energy-efficiency in wireless sensor networks since sensor nodes in the surrounding region of an event may generate redundant sensed data. The redundant sensed data should be aggregated before being delivered to the sink to reduce energy consumption. Which node should be selected as a Data Aggregation Node (DAN) for achieving the best energy efficiency is a difficult issue. To address this issue, this letter proposes a scheme to select a DAN for achieving energy-efficiency in an event region. The proposed scheme uses an analytical model to select the sensor node that has the lowest total energy consumption for gathering data from sensor nodes and for forwarding aggregated data to a sink, as a DAN. Analysis and simulation results show that the proposed scheme is superior to other schemes.

Time synchronization is an essential service for wireless sensor networks (WSNs). However, fixed-period time synchronization can not serve multiple users efficiently in terms of energy consumption. This paper proposes a lightweight precision-adaptive protocol for cluster-based multi-user networks. It consists of a basic average time synchronization algorithm and an adaptive control loop. The basic average time synchronization algorithm achieves 1 µs instantaneous synchronization error performance. It also prolongs re-synchronization period by taking the average of two specified nodes' local time to be cluster global time. The adaptive control loop realizes diverse levels of synchronization precision based on the proportional relationship between sync error and re-synchronization period. Experimental results show that the proposed precision-adaptive protocol can respond to the sync error bound change within 2 steps. It is faster than the exponential convergence of the adaptive protocols based on multiplicative iterations.

This paper is concerned with the packet transmission scheduling problem for repeating all-to-all broadcasts in Underwater Sensor Networks (USN) in which there are n nodes in a transmission range. All-to-all communication is one of the most dense communication patterns. It is assumed that each node has the same size packet. Unlike the terrestrial scenarios, the propagation time in underwater communications is not negligible. We define all-to-all broadcast as the one where every node transmits packets to all the other nodes in the network except itself. So, there are in total n(n - 1) packets to be transmitted for an all-to-all broadcast. The optimal transmission scheduling is to schedule in a way that all packets can be transmitted within the minimum time. In this paper, we propose an efficient packet transmission scheduling algorithm for underwater acoustic communications using the property of long propagation delay.

In a WSAN (Wireless Sensor and Actuator Network), most resources, including sensors and actuators, are designed for certain applications in a dedicated environment. Many researchers have proposed to use of gateways to infer and annotate heterogeneous data; however, such centralized methods produce a bottlenecking network and computation overhead on the gateways that causes longer response time in activity processing, worsening performance. This work proposes two distribution inference mechanisms: regionalized and sequential inference mechanisms to reduce the response time in activity processing. Finally, experimental results for the proposed inference mechanisms are presented, and it shows that our mechanisms outperform the traditional centralized inference mechanism.

In this paper, we propose a novel filtering method for processing continuous skyline queries in wireless sensor network environments. The existing filtering methods on such environments use filters that are based on router paths. However, these methods do not have a major effect on reducing data for sensor nodes to transmit to the base station, because the filters are applied to not the whole area but a partial area. Therefore, we propose a novel and efficient method to dramatically reduce the data transmissions of sensors through applying an effective filter with low costs to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.

Motivated by the needs of modern agriculture, in this paper we present CropNET, a wireless multimedia sensor network system for agriculture monitoring. Both hardware and software designs of CropNET are tailored for sensing in wide farmland without human supervision. We have carried out multiple rounds of deployments. The evaluation results show that CropNET performs well and facilitates modern agriculture.

There has been much interest in a spatial query which acquires sensor readings from sensor nodes inside specified geographical area of interests. A centralized approach performs the spatial query at a server after acquiring all sensor readings. However, it incurs high wireless transmission cost in accessing all sensor nodes. Therefore, various in-network spatial search methods have been proposed, which focus on reducing the wireless transmission cost. However, the in-network methods sometimes incur unnecessary wireless transmissions because of dead space, which is spatially indexed but does not contain real data. In this paper, we propose a hybrid spatial query processing algorithm which removes the unnecessary wireless transmissions. The main idea of the hybrid algorithm is to find results of a spatial query at a server in advance and use the results in removing the unnecessary wireless transmissions at a sensor network. We compare the in-network method through several experiments and clarify our algorithm's remarkable features.

Novel thermopiles based on modulation doped AlGaAs/InGaAs, AlGaN/GaN, and ZnMgO/ZnO heterostructures are proposed and designed for the first time, for uncooled infrared image sensor application. These devices are expected to offer high performances due to both the superior Seebeck coefficient and the excellently high mobility of 2DEG and 2DHG due to high purity channel layers at the heterojunction interface. The AlGaAs/InGaAs thermopile has the figure-of-merit Z of as large as 1.110-2/K (ZT = 3.3 over unity at T = 300 K), and can be realized with a high responsivity R of 15,200 V/W and a high detectivity D* of 1.8109 cmHz1/2/W with uncooled low-cost potentiality. The AlGaN/GaN and the ZnMgO/ZnO thermopiles have the advantages of high sheet carrier concentration due to their large polarization charge effects (spontaneous and piezo polarization charges) as well as of a high Seebeck coefficient due to their strong phonon-drag effect. The high speed response time τ of 0.9 ms with AlGaN/GaN, and also the lower cost with ZnMgO/ZnO thermopiles can be realized. The modulation-doped heterostructure thermopiles presented here are expected to be used for uncooled infrared image sensor applications, and for monolithic integrations with other photon detectors such as InGaAs, GaN, and ZnO PiN photodiodes, as well as HEMT functional integrated circuit devices.

Recently, the importance of data sharing structures in autonomous distributed networks has been increasing. A wireless sensor network is used for managing distributed data. This type of distributed network requires effective information exchanging methods for data sharing. To reduce the traffic of broadcasted messages, reduction of the amount of redundant information is indispensable. In order to reduce packet loss in mobile ad-hoc networks, QoS-sensitive routing algorithm have been frequently discussed. The topology of a wireless network is likely to change frequently according to the movement of mobile nodes, radio disturbance, or fading due to the continuous changes in the environment. Therefore, a packet routing algorithm should guarantee QoS by using some quality indicators of the wireless network. In this paper, a novel information exchanging algorithm developed using a hash function and a Boolean operation is proposed. This algorithm achieves efficient information exchanges by reducing the overhead of broadcasting messages, and it can guarantee QoS in a wireless network environment. It can be applied to a routing algorithm in a mobile ad-hoc network. In the proposed routing algorithm, a routing table is constructed by using the received signal strength indicator (RSSI), and the neighborhood information is periodically broadcasted depending on this table. The proposed hash-based routing entry management by using an extended MAC address can eliminate the overhead of message flooding. An analysis of the collision of hash values contributes to the determination of the length of the hash values, which is minimally required. Based on the verification of a mathematical theory, an optimum hash function for determining the length of hash values can be given. Simulations are carried out to evaluate the effectiveness of the proposed algorithm and to validate the theory in a general wireless network routing algorithm.

In wireless sensor networks, adversaries can easily launch application layer attacks, such as false data injection attacks and false vote insertion attacks. False data injection attacks may drain energy resources and waste real world response efforts. False vote insertion attacks would prevent reporting of important information on the field. In order to minimize the damage from such attacks, several prevention based solutions have been proposed by researchers, but may be inefficient in normal condition due to their overhead. Thus, they should be activated upon detection of such attacks. Existing detection based solutions, however, does not address application layer attacks. This paper presents a scheme to adaptively counter false data injection attacks and false vote insertion attacks in sensor networks. The proposed scheme consists of two sub-units: one used to detect the security attacks and the other used to select efficient countermeasures against the attacks. Countermeasures are activated upon detection of the security attacks, with the consideration of the current network status and the attacks. Such adaptive countering approach can conserve energy resources especially in normal condition and provide reliability against false vote insertion attacks.

In this study, a new scanning method for measuring field distributions is proposed. In this method, measurement positions are automatically decided by a magnetic tracker. This method obtains field distributions in real-time, and can display field distribution map successively by interpolating.

In this paper, we study the problem of processing continuous range queries in a hierarchical wireless sensor network. Recently, as the size of sensor networks increases due to the growth of ubiquitous computing environments and wireless networks, building wireless sensor networks in a hierarchical configuration is put forth as a practical approach. Contrasted with the traditional approach of building networks in a "flat" structure using sensor devices of the same capability, the hierarchical approach deploys devices of higher-capability in a higher tier, i.e., a tier closer to the server. While query processing in flat sensor networks has been widely studied, the study on query processing in hierarchical sensor networks has been inadequate. In wireless sensor networks, the main costs that should be considered are the energy for sending data and the storage for storing queries. There is a trade-off between these two costs. Based on this, we first propose a progressive processing method that effectively processes a large number of continuous range queries in hierarchical sensor networks. The proposed method uses the query merging technique proposed by Xiang et al. as the basis. In addition, the method considers the trade-off between the two costs. More specifically, it works toward reducing the storage cost at lower-tier nodes by merging more queries and toward reducing the energy cost at higher-tier nodes by merging fewer queries (thereby reducing "false alarms"). We then present how to build a hierarchical sensor network that is optimal with respect to the weighted sum of the two costs. This allows for a cost-based systematic control of the trade-off based on the relative importance between the storage and energy in a given network environment and application. Experimental results show that the proposed method achieves a near-optimal control between the storage and energy and reduces the cost by 1.002 -- 3.210 times compared with the cost achieved using the flat (i.e., non-hierarchical) setup as in the work by Xiang et al.

In the area of wireless sensor networks, the efficient spatial query processing based on the locations of sensor nodes is required. Especially, spatial queries on two sensor networks need a distributed spatial join processing among the sensor networks. Because the distributed spatial join processing causes lots of wireless transmissions in accessing sensor nodes of two sensor networks, our goal of this paper is to reduce the wireless transmissions for the energy efficiency of sensor nodes. In this paper, we propose an energy-efficient distributed spatial join algorithm on two heterogeneous sensor networks, which performs in-network spatial join processing. To optimize the in-network processing, we also propose a Grid-based Rectangle tree (GR-tree) and a grid-based approximation function. The GR-tree reduces the wireless transmissions by supporting a distributed spatial search for sensor nodes. The grid-based approximation function reduces the wireless transmissions by reducing the volume of spatial query objects which should be pushed down to sensor nodes. Finally, we compare naive and existing approaches through extensive experiments and clarify our approach's distinguished features.

In ubiquitous sensor networks, the estimation accuracy of a node location is limited due to the presence of non-line-of-sight (NLOS) paths. To mitigate the NLOS effects, this letter proposes a simple algorithm where NLOS identification is carried out using angle-of-arrival (AOA). Simulation results show that the use of AOA improves NLOS identification rates and location estimation accuracy.

In modern sensor networks, key management is essential to transmit data from sensors to the sink securely. That is, sensors are likely to be compromised by attackers, and a key management scheme should renew the keys for communication as frequently as possible. In clustered sensor networks, CHs (Cluster Heads) tend to become targets of compromise attack because they collect data from sensors and deliver the aggregated data to the sink. However, existing key renewal schemes do not change the CH role nodes, and thus they are vulnerable to the compromise of CHs. Our scheme is called DIRECT (DynamIc key REnewal using Cluster head elecTion) because it materializes the dynamic key renewals through secure CH elections. In the scheme, the network is divided into sectors to separate CH elections in each sector from other sectors. Then, sensors establish pairwise keys with other sensors in their sector for intra-sector communication. Every CH election round, all sensors securely elect a CH in their sector by defeating the malicious actions of attackers. Therefore, the probability that a compromised node is elected as a CH decreases significantly. The simulation results show that our approach significantly improves the integrity of data, energy efficiency, and network longevity.

We have fabricated VDP (van der Pauw) stress sensors on (111) silicon surfaces. This work focuses on a study of strain effects in VDP stress sensors, which were generally ignored in previous works, for the precise measurements of die stresses in electronic packages. The stress sensitivity was observed to be approximately 10% larger for p-type VDP sensors compared to n-type VDP sensors.