One challenging issue of sensor networks is extension of overall network system lifetimes. In periodic data gathering applications, the typical sensor node spends more time in the idle state than active state. Consequently, it is important to decrease power consumption during idle time. In this study, we propose a scheduling scheme based on the history of RTS/CTS exchange during the setup phase. Scheduling the transmission during transfer phase enables each node to turn off its RF circuit during idle time. By tracing ongoing RTS/CTS exchange during the steady phase, each node knows the progress of the data transfer process. Thereby, it can wait to receive packets for data aggregation. Simulation results show a 160-260% longer system lifetime with the proposed scheduling scheme compared to the existing approaches.

Congestion in WSN increases the energy dissipation rates of sensor nodes as well as the loss of packets and thereby hinders fair and reliable event detection. We find that one of the key reasons of congestion in WSN is allowing sensing nodes to transfer as many packets as possible. This is due to the use of CSMA/CA that gives opportunistic medium access control. In this paper, we propose an energy efficient congestion avoidance protocol that includes source count based hierarchical and load adaptive medium access control and weighted round robin packet forwarding. We also propose in-node fair packet scheduling to achieve fair event detection. The results of simulation show our scheme exhibits more than 90% delivery ratio even under bursty traffic condition which is good enough for reliable event perception.

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes, with the goal of deceiving the base station or depleting the resources of forwarding nodes. Several research solutions have been recently proposed to detect and drop such forged reports during the forwarding process. Each design can provide the equivalent resilience in terms of node compromising. However, their energy consumption characteristics differ from each other. Thus, employing only a single filtering scheme for a network is not a recommendable strategy in terms of energy saving. In this paper, we propose a fuzzy-based adaptive filtering scheme selection method for energy saving. A fuzzy rule-based system is exploited to choose one of three filtering schemes by considering the false traffic ratio, the security threshold value, distance, and the detection power of the filtering scheme. The adaptive selection of the filtering schemes can conserve energy, and guarantee sufficient resilience.

Reliable end-to-end delivery service is one of the most important issues for wireless sensor networks in large-scale deployments. In this paper, a reliable data transport protocol, called the Data Forwarding Protocol (DFP), is proposed to improve the end-to-end delivery rate with minimum transport overhead for recovering from data loss in large-scale wireless sensor environments consisting of low speed mobile sensor nodes. The key idea behind this protocol is the establishment of multi-split connection on an end-to-end route, through the Agent Host (AH), which plays the role of a virtual source or a sink node. In addition, DFP applies the local error control and the local flow control mechanisms to multi-split connections, according to network state. Extensive simulations are carried out via ns-2 simulator. The simulation results demonstrate that DFP not only provide up to 30% more reliable data delivery, but also reduces the number of retransmission generated by data loss, compared with the TCP-like end-to-end approach.

A single-chip ubiquitous sensor network (USN) system-on-a-chip (SoC) for small program memory size and low power has been proposed and integrated in a 0.18-µm CMOS technology. Proposed single-chip USN SoC is mainly consists of radio for 868/915 MHz, analog building block, complete digital baseband physical layer (PHY) and media access control (MAC) functions. The transceiver's analog building block includes a low-noise amplifier, mixer, channel filter, receiver signal-strength indication, frequency synthesizer, voltage-controlled oscillator, and power amplifier. In addition, digital building block consists of differential binary phase-shift keying (DPSK) modulation, demodulation, carrier frequency offset compensation, auto-gain control, embedded 8-bit microcontroller, and digital MAC function. Digital MAC function supports 128 bit advanced encryption standard (AES), cyclic redundancy check (CRC), inter-symbol timing check, MAC frame control, and automatic retransmission. These digital MAC functions reduce the processing power requirements of embedded microcontroller and program memory size by up to 56%. The cascaded noise figure and sensitivity of the overall receiver are 9.5 dB and -99 dBm, respectively. The overall transmitter achieves less than 6.3% error vector magnitude (EVM). The current consumption is 14 mA for reception mode and 16 mA for transmission mode.

Recent advances in wireless technologies and electronic devices have enabled the development of low-cost and large-scale wireless sensor networks. Many recent studies have targeted wireless sensor networks, but forwarding messages while satisfying both delay and reliability constraints remains an unsatisfied goal. Although most existing proposals aim at resiliency in multi-hop networks, improvement of network performance such as throughput and latency, and load balancing, supporting multiple forwarding strategies satisfying various demands is not discussed. We propose a forwarding method for messages with delay and reliability constraints on a single wireless sensor network. We evaluate message loss rate by using computer simulation and by implementing the proposed method on actual sensor nodes. Our results show that the proposed method achieves lower message loss rate for messages with delay and reliability constraints than that for best-efforts messages on a network with error-prone wireless links.

We propose LPDD (Lifetime Prediction Directed Diffusion), a novel energy-aware routing protocol for sensor networks that aims at increasing network survivability without a significant increase in latency. The key concept behind the protocol is the adaptive selection of routes by predicting the battery lifetime of the minimum energy nodes along the routes.

Ubiquitous sensor networks (USNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient network. We propose a sleep scheduling scheme for balancing energy consumption rates in a single hop cluster based network using Analytical Hierarchy Process (AHP). We consider three factors contributing to the optimal nodes scheduling decision and they are the distance to cluster head (CH), residual energy, and sensing coverage overlapping, respectively. We also propose an integrated sleep scheduling and geographical multi-path routing scheme for USNs by AHP. The sleep scheduling is redesigned to adapt the multi-hop case. For the proposed routing protocol, the distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection. The proposed schemes are observed to improve network lifetime and conserve energy without compromising desired coverage. In the multi-hop case, it can further reduce the packet loss rate and link failure rate since the buffer capacity is considered.

In this paper, we investigate the critical low coverage problem of position aware localized efficient broadcast in mobile ad hoc ubiquitous sensor networks and propose a generic framework for it. The framework is to determine a small subset of nodes and minimum transmission radiuses based on snapshots of network state (local views) along the broadcast process. To guarantee the accuracy of forward decisions, based on historical location information nodes will predict neighbors' positions at future actual transmission time and then construct predicted and synchronized local views rather than simply collect received "Hello" messages. Several enhancement technologies are also proposed to compensate the inaccuracy of prediction and forward decisions. To verify the effectiveness of our framework we apply existing efficient broadcast algorithms to it. Simulation results show that new algorithms, which are derived from the generic framework, can greatly increase the broadcast coverage ratio.

Wireless sensor networks can be used in various fields, e.g., military and civil applications. The technique of saving energy to prolong the life of sensor nodes is one of main challenges to resource-constrained sensor networks. Therefore, in-network aggregation of data has been proposed in resource-constrained environments for energy efficiency. Most previous works on in-network aggregation only support a one-dimensional data (e.g., MIN and MAX). To support a multi-dimensional data, the skyline query is used. The skyline query returns a set of points that are not dominated by any other point on all dimensions. The majority of previous skyline query processing methods (e.g., BNL and BBS) work on centralized storage. Centralized query processing methods do not have merits in terms of energy efficiency in high event rate environments. In this paper, we propose new algorithm of in-network processing for the skyline queries. The proposed algorithm reduces the communication cost and evenly distributes load. The experimental results show the advantages of our algorithm over in-network aggregation in terms of improving energy efficiency.

In this paper, we propose a sequential type-based detection scheme for wireless sensor networks in the case of spatially and temporally identically and independently distributed observations. First, we investigate the optimal sequential detection rule of the proposed scheme, and then with the motivation of reducing the computational complexity of the optimal detection rule, we consider an approximation scheme and derive a suboptimal detection rule. We also compare the performances of the type-based sequential detection scheme with those of the non-sequential type-based detection scheme in terms of both average number of observations and total energy consumption, and determine the region of individual node power where the proposed scheme outperforms the non-sequential scheme. In addition, we show that the approximated detection rule provides the similar results as the optimal detection rule with a significant reduction of the computational complexity, which makes the approximated detection rule useful for real-time applications.

We have been investigating a new class of ubiquitous services, called Activity Logging, which takes advantage for private and public sensors and the RFID tags on real-world objects. The purpose of Activity Logging is to digitally record users' interests with real-world objects and users' context to describe the users' activity. Such digital information acquired from a range of sensors and tags, if being accumulated, forms a great data source for users to recall their activities later or to share the activities with others. This paper explores the design space to realize Activity Logging, and proposes a simple mobile device called Activity Recorder that marries public and private sensors to provide a powerful Activity Logging service. An Activity Recorder contains a range of private sensors, and has communication capability to work with public sensors around the user.

Many devices are expected to be networked with wireless appliances such as radio frequency identification (RFID) tags and wireless sensors, and the number of such appliances will greatly exceed the number of PCs and mobile telephones. This may lead to an essential change in the network architecture. This paper proposes a new network architecture called the appliance defined ubiquitous network (ADUN), in which wireless appliances will be networked without network protocol standards. Radio space information rather than individual appliance signals is carried over the ADUN in the form of a stream with strong privacy/security control. It should be noted that this is different from the architectural principles of the Internet. We discuss a network-appliance interface that is sustainable over a long period, and show that the ADUN overhead will be within the scope of the broadband network in the near future.

Recently there has been a great deal of research on using mobility in sensor networks to assist their sensing tasks. In this paper, we propose a policy-based session control protocol for Multi-Robot Sensor Networks (MRSNs) called Billiards. In a MRSN, all messages are transported by the physical motion of participants (mobile nodes) in the network. When a large volume of data or continuous data is required to be transferred, there exists a problem determining how the data is fragmented and how the mobile nodes are formed for carrying the data to the destination. To overcome the issues, we propose a suitable method of session control which is determined based on a state of surrounding mobile nodes such as number, maximum-velocity and buffer-size. Billiards also takes a system policy of delay minimization into consideration. In this paper, we describe the protocol and model of Billiards and analyze the model. We evaluated the performance of Billiards utilizing mobile robots which are equipped with MICA2 mote and comparing with non optimized method. The experimental results demonstrate that Billiards achieves less delay than non optimized method at every velocity and buffer-size of each robot.

In this paper, we propose a multipath en-route filtering method to deal with the problems caused by black hole attacks and selective forwarding attacks. Our result shows that the method is more resilient to these problems up to a certain number of compromised nodes than the statistical en-route filtering scheme.

The recent progress in sensor and wireless communication technologies has enabled the design and implementation of new applications such as sensor telemetry which is the use of wireless sensors to gather fine-grained information from products, people and places. In this work, we consider a realistic telemetry application in which an area is periodically monitored by a sensor network which gathers data from equally spaced sample points. The objective is to maximize the lifetime of the network by jointly selecting the sensing nodes, the node transmission powers and the route to the base station from each sensing node. We develop an optimization-based algorithm OPT-RE and a low complexity algorithm SP-RE for this purpose and analyze their dynamics through extensive numerical studies. Our results indicate that SP-RE is a promising algorithm which has comparable performance to that of the more computationally intensive OPT-RE algorithm. The energy consumption is significantly affected by the channel access method, and in this paper, we also compare the effects of the collision free TDMA and contention based CSMA/CA methods. We propose practical enhancements to CSMA/CA so that the energy consumption due to collisions is reduced. Our simulation results indicate that with the proposed enhancements contention based channel access can provide comparable performance to that of the collision free methods.

In a wireless sensor network (WSN), a large number of sensor nodes are deployed over a wide area and multi-hop communications are required between the nodes. Managing numerous sensor nodes is a very complicated task, especially when the energy issue is involved. Even though a number of ad-hoc management and network structuring approaches for WSNs have been proposed, a management framework covering the entire network management infrastructure from the messaging protocol to the network structuring algorithm has not yet been proposed. In this paper we introduce a management framework for WSNs called SNOWMAN (SeNsOr netWork MANagement) framework. It employs the policy-based management approach for letting the sensor nodes autonomously organize and manage themselves. Moreover, a new light-weight policy distribution protocol called TinyCOPS-PR and policy information base (PIB) are also developed. To facilitate scalable and localized management of sensor networks, the proposed SNOWMAN constructs a 3-tier hierarchy of regions, clusters, and sensor nodes. The effectiveness of the proposed framework is validated through actual implementation and simulation using ns-2. The simulation results reveal that the proposed framework allows smaller energy consumption for network management and longer network lifetime than the existing schemes such as LEACH and LEACH-C for practical size networks.

In this paper, we describe a new ultrasonic oscillosensor and its application in a biological information measurement system. This ultrasonic sensor has a cylindrical tank of 26 mm (diameter)20 mm (height) filled with water and an ultrasonic probe. It detects the vibration of the target object by obtaining echo signals reflected from the water surface. This sensor can noninvasively detect the vibration of a patient by placing it under a bed frame. We propose a recognition system for humans in bed. Using this sensor, we could determine whether or not a patient is in the bed. Moreover, we propose a heart rate monitoring system using this sensor. When our system was tested on four volunteers, we successfully detected a heart rate comparable to that in the case of using an electrocardiograph. Fuzzy logic plays a primary role in the recognition. Consequently, this system can noninvasively determine whether a patient is in the bed as well as their heart rate using a constraint-free and compact device.

We have investigated real-time object tracking using a wide view imaging system. For the system, we have designed and fabricated new smart image sensor with four functions effective in wide view imaging, such as a random access function. In this system, eight smart sensors and an octagonal mirror are used and each image obtained by the sensors is equivalent to a partial image of the wide view. In addition, by using an FPGA for processing, the circuits in this system can be scaled down and a panoramic image can be obtained in real time. For object tracking using this system, the object-detection method based on background subtraction is used. When moving objects are detected in the panoramic image, the objects are constantly displayed on the monitor at higher resolution in real time. In this paper, we describe the random access image sensor and show some results obtained using this sensor. In addition, we describe the wide view imaging system using eight sensors. Furthermore, we explain the method of object tracking in this system and show the results of real-time multipl-object tracking.

This paper describes logic and analog test schemes that improve the testability of a pixel-parallel fingerprint identification circuit. The pixel contains a processing circuit and a capacitive fingerprint sensor circuit. For the logic test, we propose a test method using a pseudo scan circuit to check the processing circuits of all pixels simultaneously. In the analog test, the sensor circuit employs dummy capacitance to mimic the state of a finger touching the chip. This enables an evaluation of the sensitivity of all sensor circuits on logical LSI tester without touching the chip with a finger. To check the effectiveness of the schemes, we applied them to a pixel array in a fingerprint identification LSI. The pseudo scan circuit achieved a 100% failure-detection rate for the processing circuit. The analog test determines that the sensitivities of the sensor circuit in all pixels are in the proper range. The results of the tests confirmed that the proposed schemes can completely detect defects in the circuits. Thus, the schemes will pave the way to logic and analog tests of chips integrating highly functional devices stacked on a LSI.