Processing structures required in sensing are designed to convert real-world information into useful information, and there are various restrictions and performance goals depending on physical restrictions and the target applications. On the other hand, network technologies are mainly designed for data exchange in the information world, as is seen in packet communications, and do not go well with sensing structures from the viewpoints of real-time properties, spatial continuity, etc. This indicates the need for understanding the architectures and restrictions of sensor technologies and network technologies when aiming to fuse these technologies. This paper clarifies the differences between these processing structures, proposes some issues to be addressed in order to achieve real fusion of them, and presents future directions toward real fusion of sensor technologies and network technologies.

In practical settings of wireless sensor networks, it is often feasible to consider heterogeneous deployments of devices with different capabilities. Under prescribed cost constraints, we analyze such heterogenous deployments and present how they impact the coverage of a sensor network including spatial correlation effect. We derive expressions for the heterogeneous mixture of devices that maximizes the lifetime coverage in both single-hop direct and multi-hop communication models. Our results show that using an optimal mixture of many inexpensive low-capability devices and some expensive high-capability devices can significantly extend the duration of a network's sensing performance, especially in a network with low spatial correlation.

Two-dimensional (2D) communication is a novel physical communication form that utilizes the surface as a communication medium to provide both data and power transmission service to the sensor devices placed on the surface's top. In previous works, we developed 2D communication systems that utilize separated channels for data and power transmission. Though this assignment of different channels can achieve strong network performance, the sensor devices must be equipped with two or more interfaces to simultaneously receive the power and data signals, which significantly complicates and enlarges those devices. Moreover, when a channel is used for the power supply, it not only continually monopolizes the wireless frequency resource, it is also likely to cause interference with the other signal source in the case of the input power continually being sent out above a certain level. In this paper, we develop a novel 2D communication sensor system by using a single-carrier frequency for both power and data transmission, equipped with the wireless module for the two together in a compact body. To enable a sensor node that concurrently receives energy and data communication, we propose an enhancement scheme based on the IEEE802.15.4 MAC protocol standard. Through both computer simulation and actual measurement of the output power, we evaluate the performance of power supply and data transmission over the developed 2D communication sensor system.

Recently wireless sensor networks (WSN) has risen as one of the advanced candidate technologies in order to provide more efficient structure health monitoring (SHM) solution in construction sites. In this paper, we proposed WSN monitoring framework in building sites based on 3D visualization and Augmented Reality (AR) in mobile devices. The proposed system applies 3D visualization and AR technology to camera-enabled mobile devices in WSN environment in order to gather much more information than before. Based on the proposed system, we made an experiment to validate the effectiveness of 3D and AR mode using collected data in IEEE 802.15.4-based WSN.

Random scattering of sensors may cause some location not to be covered. In such a case, it is useful to make use of mobile sensors that can move to eliminate the coverage holes. Wang et al [1]. proposed self-deployment schemes of mobile sensors by using Voronoi polygon. However, some coverage holes still remain after the execution of the schemes. We propose a new self-deployment scheme using the centroid (geometric center) of each sensor's Voronoi polygon as the moving target position. The performance evaluation shows that the proposed scheme achieves better results than the existing schemes in terms of fast coverage expansion.

In wireless sensor networks (WSNs), geographic routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Geographic routing with location errors may produce serious problems such as disconnected links and data transmission delays. In this letter, we present an efficient location error compensation algorithm for the geographic routing. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.

A new best-relay selection scheme is proposed in this letter in order to maintain a reliable cooperative communications for ubiquitous sensor networks in indoor environments. The suggested technique relies on eigenvalue decomposition to select the best relay. The simulation results confirm that the performance of the proposed approach is better than that of the previous scheme in indoor environments.

We consider a distributed transmission of data packet to a sink where the distance of a sensor node to a sink is much longer than the maximum communication range of each sensor node. We give a simple modification to the transmitter, i.e., multiplication of random phase before the transmission. Thanks to Turbo Code, it is possible to extend the transmission range as the received amplitude varies symbol by symbol for our scheme while whole data packet may be lost for the conventional scheme. In this letter, we report the experimental results of our scheme equivalently developed using visible light communication.

In clustered sensor networks, because CHs (Cluster Heads) are the collection points of data, they are likely to be compromise targets of attackers. So, they need to be changed through a CH election scheme as frequently as possible. Besides, because the compromised nodes must try to become a CH, a CH election scheme should prevent them from being a CH. This paper presents a secure CH election scheme for clustered sensor networks, which changes the CH role nodes securely by excluding the compromised nodes from CH candidates. In the proposed scheme, each node gives marks for behavior of all other nodes in the same CH election region and exchanges the mark list with them. Then, each node computes the average marks for all nodes in the region, and nodes whose average mark is less than a specific threshold are excluded from CH candidates. A CH is elected among the remaining candidates. Simulation results show that our scheme provides strong resilience against misbehavior of compromised nodes and reduces energy consumption of nodes. Another simulation results show that our scheme well operates in the environment where some packets are often lost.

This paper presents an autonomous traffic engineering framework, named ATE, a highly efficient data dissemination mechanism for multipath data forwarding in Wireless Sensor Networks (WSNs). The proposed ATE has several salient features. First, ATE utilizes three coordinating schemes: an incipient congestion inference scheme, an accurate link quality estimation scheme and a dynamic traffic diversion scheme. It significantly minimizes packet drops due to congestion by dynamically and adaptively controlling the data traffic over congested nodes and/or poorer quality links, and by opportunistically exploiting under-utilized nodes for traffic diversion, while minimizing the estimation and measurement overhead. Second, ATE can provide with high application fidelity of the network even for increasing values of bit error rates and node failures. The proposed link quality estimation and congestion inference schemes are light weight and distributed, improving the energy efficiency of the network. Autonomous Traffic Engineering has been evaluated extensively via NS-2 simulations, and the results have shown that ATE provides a better performance with minimum overhead than those of existing approaches.

Developing an adaptive 3-dimensional (3D) topology control algorithm is important because most wireless nodes are mobile and deployed in buildings. Moreover, in buildings, wireless link qualities and topologies change frequently due to various objects and the interference from other wireless devices. Previous topology control algorithms can suffer significant performance degradation because they only use the Euclidean distance for the topology construction. In this paper, we propose a novel adaptive 3D topology control algorithm for wireless ad-hoc sensor networks, especially in indoor environments. The proposed algorithm adjusts the minimum transmit power adaptively with considering the interference effect. To construct the local topology, each node divides the 3D space, a sphere centered at itself, into k equal cones by using Platonic solid (i.e., regular k-hedron) and selects the neighbor that requires the lowest transmit power in each cone. Since the minimum transmit power values depend on the effect of interferences, the proposed algorithm can adjust topology adaptively and preserve the network connectivity reliably. To evaluate the performance of algorithms, we conduct various experiments with simulator and real wireless platforms. The experimental results show that the proposed algorithm is superior to the previous algorithms in terms of the packet delivery ratio and the energy consumption with relatively low complexity.

Slow development in battery technology and rapid advances in ultra-capacitor design have motivated us to investigate the possibility of using capacitors as the sole energy storage for wireless sensor nodes to support ubiquitous computing. The starting point of this work is TwinStar, which uses ultra-capacitor as the only energy storage unit. To efficiently use the harvested energy, we design and implement feedback control techniques to match the activity of sensor nodes with the dynamic energy supply from environments. We conduct system evaluation by deploying sensor devices under three typical real-world settings -- indoor, outdoor, and mobile backpack under a wide range of system settings. Results indicate our feedback control can effectively utilize energy and ensure system sustainability. Nodes running feedback control have longer operational time than the ones running non-feedback control.

Ubiquitous technologies such as sensor network and RFID have enabled companies to realize more rapid and agile manufacturing and service systems. In this paper, we addresses how the huge amount of real-time events coming from these devices can be filtered and integrated to business process such as manufacturing, logistics, and supply chain process. In particular, we focus on complex event processing of sensor and RFID events in order to integrate them to business rules in business activities. We also illustrate a ubiquitous event processing system, named ueFilter, which helps to filter and aggregate sensor event, to detect event patterns from sensors and RFID by means of event pattern languages (EPL), and trigger event-condition-action (ECA) in logistics processes.

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 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-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.

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.