System implementation for e-Government initiatives should be reliable. Unreliable system implementation could, on the one hand, be insufficient to fulfill basic system requirements, and more seriously on the other hand, break the trust of citizens on governments. The objective of this paper is to advocate the use of formal methods in general, the OTS/CafeOBJ method in particular in this paper, to help develop reliable system implementation for e-Government initiatives. An experiment with the OTS/CafeOBJ method on an e-Government messaging framework proposed for providing citizens with seamless public services is described to back up our advocation. Two previously not well-clarified problems of the framework and their potential harm realized in this experiment are reported, and possible ways of revisions to the framework are suggested as well. The revisions are proved to be sufficient for making the framework satisfy certain desired properties.

We propose a high-speed protection scheme for multiple-priority-class traffic transmission in WDM ring networks. This scheme achieves high-speed protection by quickly suspending transmission of low-priority traffic when a failure is detected. Each node suspends transmission of the low-priority traffic being sent over the backup path corresponding to the impaired primary path after receiving a failure notification and checking a table that includes the primary paths passing through the node, the backup paths corresponding to the primary paths, and low-priority traffic transmitted by the node. If a node detects a failure, it sends a single failure notification for each ring to the source node of the primary path, and the nodes on the route sequentially suspend low-priority traffic. Simulation shows that the proposed scheme reduces the failure-recovery time by up to 60% compared with the conventional scheme.

The establishment of inter-domain traffic engineered paths is a requisite to accomplishing an end-to-end bandwidth guarantee and end-to-end resource optimization. Though the inter-domain paths must be reliable, it is difficult to compute suitable backup inter-domain paths in advance when the traffic engineering information is not disclosed outside of each domain. This means that the inter-domain path computation must satisfy the severe requirement of path establishment delay, since all inter-domain paths traversing the links in failure need to be computed after the failure occurs. Though several inter-domain path computation schemes have been proposed, their relative characteristics remain unknown. First, this paper classifies the conventional inter-domain path computation schemes into two types, i.e. end-to-end and per-domain schemes, and compares their performances under various traffic loads. Based on results of the comparisons, this paper proposes an adaptive inter-domain path computation scheme that can satisfy the severe requirement of the path establishment delay. In this scheme, the domain sequence from the source node to the destination node is divided into multiple sub-domain sequences according to the traffic load in each domain. The end-to-end path computation scheme is applied to the sub-domain sequences under heavy traffic loads, while the per-domain path computation scheme is applied to those under normal traffic loads. The simulation results show that the proposed scheme can adaptively satisfy the requirement for the path establishment delay while it maintains the optimality of path computation, even if the traffic load applied to each domain changes.

In this letter, we propose a distributed channel assignment where each basestation selects a set of channels shared by multiple users through time domain scheduling for best effort services. The proposed scheme distributedly assigns the channels considering a cochannel interference from neighboring basestations and its own traffic load condition. The computer simulation demonstrates that the proposed scheme appropriately assigns the channels to the basestations taking into account these requirements.

In this letter, we propose a novel antenna selection algorithm for amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay systems with Zero-Forcing (ZF) processing applied both at the source node and at the destination node. We obtain the optimum antenna selection criterion by deriving an iterative closed-form expression for capacity maximization.

The safety and availability policies are very important in an access control system for ensuring security and success when performing a certain task. However, conflicts may arise between safety and availability policies due to their opposite focuses. In this paper, we address the problem of consistency checking for safety and availability policies, especially for the co-existence of static separation-of-duty (SSoD) policies with availability policies, which determines whether there exists an access control state that satisfies all of these policies. We present criteria for determining consistency with a number of special cases, and show that the general case and partial subcases of the problem are intractable (NP-hard) and in the Polynomial Hierarchy NPNP. We design an algorithm to efficiently solve the nontrivial size instances for the intractable cases of the problem. The running example shows the validity of the proposed algorithm. The investigation will help the security officer to specify reasonable access control policies when both safety and availability policies coexist.

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

Since traffic in IP access networks is less aggregated than in backbone networks, its variance could be significant and its distribution may be long-tailed rather than Gaussian in nature. Such characteristics make it difficult to forecast traffic volume in IP access networks for appropriate capacity planning. This paper proposes a traffic forecasting method that includes a function to control residual error distribution in IP access networks. The objective of the proposed method is to grasp the statistical characteristics of peak traffic variations, while conventional methods focus on average rather than peak values. In the proposed method, a neural network model is built recursively while weighting residual errors around the peaks. This enables network operators to control the trade-off between underestimation and overestimation errors according to their planning policy. Evaluation with a total of 136 daily traffic volume data sequences measured in actual IP access networks demonstrates the performance of the proposed method.

This letter proposes a new multicast traffic control policy in TDM-PON, which differentially classifies multicast flows which have relatively many associated receivers as high-class, and multicast flows which have relatively few associated receivers as low-class. Simulation results confirm that the proposed policy can effectively enhance multicast performance regarding delay and loss, specifically important to multimedia services, compared to the legacy policy.

Recent research on overlay networks has revealed that user-perceived network performance could be improved by an overlay routing mechanism. The effectiveness of overlay routing is mainly a result of the policy mismatch between the overlay routing and the underlay IP routing operated by ISPs. However, this policy mismatch causes a "free-riding" traffic problem, which may become harmful to the cost structure of Internet Service Providers. In the present paper, we define the free-riding problem in the overlay routing and evaluate the degree of free-riding traffic to reveal the effect of the problem on ISPs. We introduce a numerical metric to evaluate the degree of the free-riding problem and confirm that most multihop overlay paths that have better performance than the direct path brings the free-riding problem. We also discuss the guidelines for selecting paths that are more effective than the direct path and that mitigate the free-riding problem.

In Malay language, there are no conjugations and declensions and affixes have important grammatical functions. In Malay, the same word may function as a noun, an adjective, an adverb, or, a verb, depending on its position in the sentence. Although extensively simple root words are used in informal conversations, it is essential to use the precise words in formal speech or written texts. In Malay, to make sentences clear, derivative words are used. Derivation is achieved mainly by the use of affixes. There are approximately a hundred possible derivative forms of a root word in written language of the educated Malay. Therefore, the composition of Malay words may be complicated. Although there are several types of stemming algorithms available for text processing in English and some other languages, they cannot be used to overcome the difficulties in Malay word stemming. Stemming is the process of reducing various words to their root forms in order to improve the effectiveness of text processing in information systems. It is essential to avoid both over-stemming and under-stemming errors. We have developed a new Malay stemmer (stemming algorithm) for removing inflectional and derivational affixes. Our stemmer uses a set of affix rules and two types of dictionaries: a root-word dictionary and a derivative-word dictionary. The use of set of rules is aimed at reducing the occurrence of under-stemming errors, while that of the dictionaries is believed to reduce the occurrence of over-stemming errors. We performed an experiment to evaluate the application of our stemmer in text mining software. For the experiment, text data used were actual web pages collected from the World Wide Web to demonstrate the effectiveness of our Malay stemming algorithm. The experimental results showed that our stemmer can effectively increase the precision of the extracted Boolean expressions for text categorization.

The performance of two-way amplify-and-forward (AF) relay networks is presented. In particular, we derive exact closed-form expressions for symbol error rate (SER), average sum-rate, and outage probability of two-way AF relay systems in independent but not identically distributed (i.n.i.d.) Rayleigh fading channels. Our analysis is validated by a comparison against the results of Monte-Carlo simulations.

Mining correlated patterns in large transaction databases is one of the essential tasks in data mining since a huge number of patterns are usually mined, but it is hard to find patterns with the correlation. The needed data analysis should be made according to the requirements of the particular real application. In previous mining approaches, patterns with the weak affinity are found even with a high minimum support. In this paper, we suggest weighted support affinity pattern mining in which a new measure, weighted support confidence (ws-confidence) is developed to identify correlated patterns with the weighted support affinity. To efficiently prune the weak affinity patterns, we prove that the ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate patterns with dissimilar weighted support levels. Based on the two properties, we develop a weighted support affinity pattern mining algorithm (WSP). The weighted support affinity patterns can be useful to answer the comparative analysis queries such as finding itemsets containing items which give similar total selling expense levels with an acceptable error range α% and detecting item lists with similar levels of total profits. In addition, our performance study shows that WSP is efficient and scalable for mining weighted support affinity patterns.

This paper presents the analysis and design of a reflection-cancelling transverse slot-pair array antenna with baffles by using the Spectrum of Two-Dimensional Solutions (S2DS) method. For the transverse slot array, the slot spacings with more than one free-space wavelength cause the grating-lobes. The baffles suppress the grating-lobes effectively. A one-dimensional slot array is extracted from the 2D array with in-phase excitation by assuming periodicity in the transversal direction. The uniform excitation over the finite array is synthesized iteratively to demonstrate the fast and accurate results by S2DS. A unit design model with the baffles is introduced to determine the initial parameters of the slot-pairs, which greatly accelerate the iterations process. Experiments at 25.3 GHz demonstrate the suppression of the grating lobes to the level less than -20.0 dB and also the good uniformity of the aperture field distribution.

In this paper, the performance of the Wireless Sensor Network (WSN) using fixed relay nodes and Multiple-Input Multiple-Output (MIMO) technology was evaluated based on the correlated channel capacity of MIMO system and the number of sensor node served by the system. Moreover, the performance evaluation of the proposed algorithm, which is used to find the optimum distance to place the relay nodes from sink node, is done not only with AF relaying and spatial correlation effect, but also with Decode-and-Forward (DF) relaying scheme. The results show that the relay gain (a ratio between the maximum number of sensors satisfying the required channel capacity in 7-cell topology to the number of sensor nodes in sink cell) is affected strongly by the spatial correlation at high required channel capacity but little at low required channel capacity. The results also show that the relay gain can be improved remarkably by using the DF relaying scheme, and that the validity of the proposed algorithm holds for any relaying scheme, spatial correlation effect and different antenna size.

This paper proposes a novel image inpainting method based on bandelet transform. This technique is based on a multi-resolution layer to perform image restoration, and mainly utilizes the geometrical flow of the neighboring texture of the damaged regions as the basis of restoration. By performing the warp transform with geometrical flows, it transforms the textural variation into the nearing domain axis utilizing the bandelet decomposition method to decompose the non-relative textures into different bands, and then combines them with the affine search method to perform image restoration. The experimental results show that the proposed method can simplify the complexity of the repair decision method and improve the quality of HVS, and thus, repaired results to contain the image of contour of high change, and in addition, offer a texture image of high-frequency variation. These repair results can lead to state-of-the-art results.

In this letter, we present a closed-form bound of the average bit error rate (BER) performance for the multi-hop amplify-and-forward (AF) relaying systems with fixed gain in Rayleigh fading channel. The proposed bound is derived from the probability density function (PDF) of the overall multi-hop relay channel under the assumption of asymptotic high signal-to-noise ratio (SNR) at every intermediate relays. When intermediate relays actually operate at finite SNR, the proposed BER bound becomes looser as the SNR of the last hop increases. In order to reflect the effect of all the noise variances of relay links to the BER evaluation, a hop-indexed recursive BER approximation is proposed, in which the proposed bound of BER under asymptotic high SNR is used. The simulation results manifest that the proposed hop-indexed recursive BER approximation can not only guarantee accuracy regardless of the SNR of the last hop but also provide higher accuracy than the previous works.

The predictability of network traffic is an important and widely studied topic because it can lead to the solutions to get more efficient dynamic bandwidth allocation, admission control, congestion control and better performance wireless networks. Support vector machine (SVM) is a novel type of learning machine based on statistical learning theory, can solve small-sample learning problems. The work presented in this paper aims to examine the feasibility of applying SVM to predict actual WLAN traffic. We study one-step-ahead prediction and multi-step-ahead prediction without any assumption on the statistical property of actual WLAN traffic. We also evaluate the performance of different prediction models such as ARIMA, FARIMA, artificial neural network, and wavelet-based model using three actual WLAN traffic. The results show that the SVM-based model for predicting WLAN traffic is reasonable and feasible and has the best performance among the above mentioned prediction models.

Most P2P systems divide a file into many pieces and fetch different pieces from many peers simultaneously. If one of the last few pieces is requested from an extremely slow peer, the overall download time may become excessive. The end-game mode was proposed to solve this problem. This method requests the last piece from all the connected peers at the same time. Unfortunately, the duplicated requests generate redundant traffic. This paper proposes a requesting method that does not increase overall download time as well as avoiding the redundant traffic. We also propose a combination of our requesting method and the end-game mode. The proposed methods are compared to the existing method with the end-game mode in simulations that use BitTorrent as a typical instance of the parallel retrieving P2P system. The results confirm that our requesting method can match the download times of the end-game mode while suppressing the redundant traffic. Our method enhances network performance by absorbing the difference in peer performance and providing steady download times without wasting traffic resources. Moreover, it is also confirmed that our combination method can distribute a file more quickly than other methods.

To attain good performance in an acoustic echo cancellation system, it is important to have a variable step size (VSS) algorithm as part of an adaptive filter. In this paper, we are concerned with the development of a VSS algorithm for a recently proposed subband affine projection (SAP) adaptive filter. Two popular VSS algorithms in the literature are the methods of delayed coefficients (DC) and variable regularization (VR). However, the merits and demerits of them are mutually exclusive. We propose a VSS algorithm that is a hybrid of both methods and combines their advantages. An extensive study of the new algorithm in different scenarios like the presence double-talk (DT) during the transient phase of the adaptive filter, DT during steady state, and varying DT power is conducted and reasoning is given to support the observed behavior. The importance of the method of VR as part of a VSS algorithm is emphasized.