In this letter, we propose a revised geographic routing protocol and a scheduling algorithm to support real-time applications, which are often observed in wireless sensor networks. In order to meet real-time requirement, a specific application is modeled as an (m,k)-firm stream that has a property of weakly hard real-time system. In addition, both a priority-based scheduling and a geographic forwarding scheme based on delay, distance, and remaining slack time are newly proposed. Simulations and their analysis are followed to validate the suitability of reduced dynamic failure probability and extended network lifetime.

In this letter, we first study the impact of the basic reference frame jitter on the digital image stabilization. Next, a method for stabilizing the digital image sequence based on the correction for basic reference frame jitter is proposed. The experimental results show that our proposed method can effectively decrease the excessive undefined areas in the stable image sequence resulting from the basic reference frame jitter.

The exact time complexity of Hsu and Huan's self-stabilizing maximal matching algorithm is provided. It is n2 + n - 2 if the number of nodes n is even and n2 + n - if n is odd.

Recently, privacy preservation has become one of the key issues in data mining. In many data mining applications, computing frequencies of values or tuples of values in a data set is a fundamental operation repeatedly used. Within the context of privacy preserving data mining, several privacy preserving frequency mining solutions have been proposed. These solutions are crucial steps in many privacy preserving data mining tasks. Each solution was provided for a particular distributed data scenario. In this paper, we consider privacy preserving frequency mining in a so-called 2-part fully distributed setting. In this scenario, the dataset is distributed across a large number of users in which each record is owned by two different users, one user only knows the values for a subset of attributes, while the other knows the values for the remaining attributes. A miner aims to compute the frequencies of values or tuples of values while preserving each user's privacy. Some solutions based on randomization techniques can address this problem, but suffer from the tradeoff between privacy and accuracy. We develop a cryptographic protocol for privacy preserving frequency mining, which ensures each user's privacy without loss of accuracy. The experimental results show that our protocol is efficient as well.

The current interdomain routing protocol, BGP, is not resilient to a path failure due to its single-path and slowly-converging route calculation. This paper proposes a novel approach to improve the resilience of the interdomain communication by enabling a set of ASes to form an alliance for themselves. The alliance members cooperatively discover a set of disjoint paths using not only the best routes advertised via BGP but also the ones unadvertised. Since such a set of disjoint paths are unlikely to share a link failure, a member AS can provide a pair of the other members with a transit to circumvent the failure. We evaluate how many disjoint paths we could discover from both advertised and hidden (unadvertised) routes by analyzing publicly available BGP route data. Our feasibility study indicates that an alliance of ASes can establish a set of disjoint paths between arbitrary pair of its alliance members with high probability to improve the resilience of interdomain routing among the members.

Threshold testing, which is an LSI testing method based on the acceptability of faults, is effective in yield enhancement of LSIs and selective hardening for LSI systems. In this paper, we propose test generation models for threshold test generation. Using the proposed models, we can efficiently identify acceptable faults and generate test patterns for unacceptable faults with a general test generation algorithm, i.e., without a test generation algorithm specialized for threshold testing. Experimental results show that our approach is, in practice, effective.

This manuscript introduces a pointing interface for a tabletop display with a reflex in eye-hand coordination. The reflex is a natural response to inconsistency between kinetic information of a mouse and visual feedback of the mouse cursor. The reflex yields information on which side the user sees the screen from, so that the screen coordinates are aligned with the user's position.

We propose a scheme of MultiCast Routing and Wavelength Assignment (MC-RWA) to establish light-tree for dynamic multicast session for the Wavelength Division Multiplex (WDM) network by choosing the wavelength that leads to a reduction in blocking probabilities by using a parameter Δ. Δ is defined as the overall reduction of connectivity of the nodes in the network caused by a wavelength assignment process when using a particular wavelength, and we assign wavelength resources to the multicast session by choosing the Δ which leads to smallest reduction in connectivity. Through computer simulation, we show that the proposed scheme has lower blocking probabilities when compared with minimum cost scheme under the condition that wavelength conversion is not allowed.

In a ZigBee network, a finite address space is allocated to every potential parent device and a device may disallow a join request once this address space is exhausted. When a new node (child) requests to a coordinator (parent) to join a ZigBee network, the coordinator checks its address space. If it has sufficient address space, the coordinator accepts the new node as its child in the ZigBee network. If the new node has router capability (JoinAsRouter), it becomes a router in the ZigBee network. However, this association procedure makes ZigBee networks inefficient for routing, because the coordinator checks only the maximum and current numbers of child nodes. In the worst case, the network will be arranged so that the router nodes are crowded in the network. Therefore, we propose the KMCD-IME (Keeping the Maximum Communication Distance and Initial Mutual Exclusion among router nodes) algorithm with two additional conditions when a new node joins the ZigBee network. The first condition maintains the maximum communication distance between the new node and the would-be parent node. The second condition is the Initial Mutual Exclusion among router nodes. The router nodes are evenly spread across the network by KMCD-IME and an effective routing topology is formed. Therefore, the KMCD-IME algorithm extends the lifetime of the ZigBee network.

Delay Tolerant Networks (DTNs) are a class of emerging networks that experience frequent and long-duration partitions. Delay is inevitable in DTNs, so ensuring the validity and reliability of the message transmission and making better use of buffer space are more important than concentrating on how to decrease the delay. In this paper, we present a novel routing protocol named Location and Direction Aware Priority Routing (LDPR) for DTNs, which utilizes the location and moving direction of nodes to deliver a message from source to destination. A node can get its location and moving direction information by receiving beacon packets periodically from anchor nodes and referring to received signal strength indicator (RSSI) for the beacon. LDPR contains two schemes named transmission scheme and drop scheme, which take advantage of the nodes' information of the location and moving direction to transmit the message and store the message into buffer space, respectively. Each message, in addition, is branded a certain priority according to the message's attributes (e.g. importance, validity, security and so on). The message priority decides the transmission order when delivering the message and the dropping sequence when the buffer is full. Simulation results show that the proposed LDPR protocol outperforms epidemic routing (EPI) protocol, prioritized epidemic routing (PREP) protocol, and DTN hierarchical routing (DHR) protocol in terms of packet delivery ratio, normalized routing overhead and average end-to-end delay. It is worth noting that LDPR doesn't need infinite buffer size to ensure the packet delivery ratio as in EPI. In particular, even though the buffer size is only 50, the packet delivery ratio of LDPR can still reach 93.9%, which can satisfy general communication demand. We expect LDPR to be of greater value than other existing solutions in highly disconnected and mobile networks.

Internet computing is proposed to exploit personal computing resources across the Internet in order to build large-scale Web applications at lower cost. In this paper, a DHT-based distributed Web crawling model based on the concept of Internet computing is proposed. Also, we propose two optimizations to reduce the download time and waiting time of the Web crawling tasks in order to increase the system's throughput and update rate. Based on our contributor-friendly download scheme, the improvement on the download time is achieved by shortening the crawler-crawlee RTTs. In order to accurately estimate the RTTs, a network coordinate system is combined with the underlying DHT. The improvement on the waiting time is achieved by redirecting the incoming crawling tasks to light-loaded crawlers in order to keep the queue on each crawler equally sized. We also propose a simple Web site partition method to split a large Web site into smaller pieces in order to reduce the task granularity. All the methods proposed are evaluated through real Internet tests and simulations showing satisfactory results.

We present an alternative approach to what we call the "standard optimization", which minimizes a cost function by searching a parameter space. Instead, our approach "projects" in the joint observation space onto the manifold defined by the "consistency constraint", which demands that any minimal subset of observations produce the same result. This approach avoids many difficulties encountered in the standard optimization. As typical examples, we apply it to line fitting and multiview triangulation. The latter produces a new algorithm far more efficient than existing methods. We also discuss the optimality of our approach.

Interrupt service routines are a key technology for embedded systems. In this paper, we introduce the standard approach for using Generalized Stochastic Petri Nets (GSPNs) as a high-level model for generating CTMC Continuous-Time Markov Chains (CTMCs) and then use Markov Reward Models (MRMs) to compute the performance for embedded systems. This framework is employed to analyze two embedded controllers with low cost and high performance, ARM7 and Cortex-M3. Cortex-M3 is designed with a tail-chaining mechanism to improve the performance of ARM7 when a nested interrupt occurs on an embedded controller. The Platform Independent Petri net Editor 2 (PIPE2) tool is used to model and evaluate the controllers in terms of power consumption and interrupt overhead performance. Using numerical results, in spite of the power consumption or interrupt overhead, Cortex-M3 performs better than ARM7.

We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multi-objective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, and offspring generation, to improve population diversity as well as convergence rate. Experimental results indicate that the proposed MOGP-based FEP construction system outperforms the two conventional MOEAs (i.e., NSGA-II and SPEA2) for a test problem. Moreover, we compared the programs constructed by the proposed MOGP with four human-designed object recognition programs. The results show that the constructed programs are better than two human-designed methods and are comparable with the other two human-designed methods for the test problem.

In this report, Focused Ion Beam (FIB) -- SEM technique was applied to observe the tin plated fretting contacts. Spatial distributions of tin, tin oxide and so on have been confirmed quantitatively in two plating thickness of 1 and 5 µm.

This paper proposes an adaptive resource allocation for multi-tier computing systems to guarantee a fair QoS level under resource constraints of tiers. We introduce a multi-tier computing architecture which consists of a group of resource managers and an arbiter. Resource allocation of each client is managed by a dedicated resource manager. Each resource manager updates resources allocated to subtasks of its client by locally exchanging QoS levels with other resource managers. An arbiter compensates the updated resources to avoid overload conditions in tiers. Based on the compensation by the arbiter, the subtasks of each client are executed in corresponding tiers. We derive sufficient conditions for the proposed resource allocation to achieve a fair QoS level avoiding overload conditions in all tiers with some assumptions on a QoS function and a resource consumption function of each client. We conduct a simulation to demonstrate that the proposed resource allocation can adaptively achieve a fair QoS level without causing any overload condition.

In this letter, we propose a novel approach to estimate three different kinds of phone mismatch penalty matrices for two-stage keyword spotting. When the output of a phone recognizer is given, detection of a specific keyword is carried out through text matching with the phone sequences provided by the specified keyword using the proposed phone mismatch penalty matrices. The penalty matrices associated with substitution, insertion and deletion errors are estimated from the training data through deliberate error generation. The proposed approach has shown a significant improvement in a Korean continuous speech recognition task.

In this letter, we present a real-time orientation estimation and motion tracking scheme using interacting multiple model (IMM) based Kalman filtering method. Two nonlinear filters, quaternion-based extended Kalman filter (QBEKF) and gyroscope-based extended Kalman filter (GBEKF) are utilized in the proposed IMM-based orientation estimator for sensor motion state estimation. In the QBEKF, measurements from gyroscope, accelerometer and magnetometer are processed; while in the GBEKF, sole measurements from gyroscope are processed. The interacting multiple model algorithm is used for fusing the estimated states via adaptive model weighting. Simulation results validate the proposed design concept, and the scheme is capable of reducing overall estimation errors in sensor motion tracking.

This paper presents a paraunitary filter bank (PUFB) based on a direct lifting structure of a building block and its inverse transform for lossless-to-lossy image coding. Although the conventional lifting-based filter banks (LBFBs), which are constructed by lifting structures with integer coefficients and rounding operations, suffer from degradation of coding performance due to much rounding error generated by cascading lifting structures, our proposals can be applied to any PUFB without losing many ones because building blocks can be applied to every lifting block as it is. It is constructed with very simple structures and many rounding operations are eliminated. Additionally, the number of rounding operations is reduced more by using two-dimensional block transform (2DBT) of separated transform to each building block. As result, even though the proposed PUFBs require a little side information block (SIB), they show better coding performance in lossless-to-lossy image coding than the conventional ones.

A method has been developed for deriving the approximate global optimum of a nonlinear objective function. First, the objective function is expanded into a linear equation for a moment vector, and the optimization problem is reduced to an eigen analysis problem in the wave coefficient space. Next, the process of the optimization is expressed using a Schrodinger-type equation, so global optimization is equivalent to eigen analysis of the Hamiltonian of a Schrodinger-type equation. Computer simulation of this method demonstrated that it produces a good approximation of the global optimum. An example optimization problem was solved using a Hamiltonian constructed by combining Hamiltonians for other optimization problems, demonstrating that various types of applications can be solved by combining simple Hamiltonians.