Distributed denial-of-service attacks on public servers have recently become more serious. The most effective way to prevent this type of traffic is to identify the attack nodes and detach (or block) attack nodes at their egress routers. However, existing traceback mechanisms are currently not widely used for several reasons, such as the necessity of replacement of many routers to support traceback capability, or difficulties in distinguishing between attacks and legitimate traffic. In this paper, we propose a new scheme that enables a traceback from a victim to the attack nodes. More specifically, we identify the egress routers that attack nodes are connecting to by estimating the traffic matrix between arbitral source-destination edge pairs. By monitoring the traffic variations obtained by the traffic matrix, we identify the edge routers that are forwarding the attack traffic, which have a sharp traffic increase to the victim. We also evaluate the effectiveness of our proposed scheme through simulation, and show that our method can identify attack sources accurately.

Content delivery network improves end-user performance by replicating Web contents on a group of geographically distributed sites interconnected over the Internet. However, with the development whereby content distribution systems can manage dynamically changing files, an important issue to be resolved is consistency management, which means the cached replicas on different sites must be updated if the originals change. In this paper, based on the analytical formulation of object freshness, web access distribution and network topology, we derive a novel algorithm as follows: (1) For a given content which has been changed on its original server, only a limited number of its replicas instead of all replicas are updated. (2) After a replica has been selected for update, the latest version will be sent from an algorithm-decided site instead of from its original server. Simulation results verify that the proposed algorithm provides better consistency management than conventional methods with the reduced the old hit ratio and network traffic.

The Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. In the immune response, according to Burnet's clonal selection principle, the antigen imposes a selective pressure on the antibody population by allowing only those cells which specifically recognize the antigen to be selected for proliferation and differentiation. However ongoing investigations indicate that receptor editing, which refers to the process whereby antigen receptor engagement leads to a secondary somatic gene rearrangement event and alteration of the receptor specificity, is occasionally found in affinity maturation process. In this paper, we extend the traditional CSA approach by incorporating the receptor editing method, named RECSA, and applying it to the Traveling Salesman Problem. Thus, both somatic hypermutation (HM) of clonal selection theory and receptor editing (RE) are utilized to improve antibody affinity. Simulation results and comparisons with other general algorithms show that the RECSA algorithm can effectively enhance the searching efficiency and greatly improve the searching quality within reasonable number of generations.

Correctness of Java programs is important because they are executed in distributed computing environments. The object initialization scheme in the Java programming language is complicated, and this complexity may lead to undesirable semantic bugs. Various tools have been developed for detecting program patterns that might cause errors during program execution. However, current tools cannot identify code patterns in which an uninitialized field is accessed when an object is initialized. We refer to such erroneous patterns as uninitialized field references. In this paper, we propose a static pattern detection algorithm for identifying uninitialized field references. We design a sound analysis for this problem and implement an analyzer using the Soot framework. In addition, we apply our algorithm to some real Java applications. From the experiments, we identify 12 suspicious field references in the applications, and among those we find two suspected errors by manual inspection.

In this paper, a novel decentralized adaptive neural network controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, nonaffine subsystems and unknown nonlinear interconnections. The stability of the closed loop system is guaranteed by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed method, we performed some simulation studies. The results of simulation become very promising.

A new type of sound source segregation method using robot-mounted microphones, which are free from strict head related transfer function (HRTF) estimation, has been proposed and successfully applied to three simultaneous speech recognition systems. The proposed segregation method is executed with sound intensity differences that are due to the particular arrangement of the four directivity microphones and the existence of a robot head acting as a sound barrier. The proposed method consists of three-layered signal processing: two-line SAFIA (binary masking based on the narrow band sound intensity comparison), two-line spectral subtraction and their integration. We performed 20 K vocabulary continuous speech recognition test in the presence of three speakers' simultaneous talk, and achieved more than 70% word error reduction compared with the case without any segregation processing.

We present MobileOBJ, a formal framework for specifying and verifying mobile systems. Based on hidden algebra, the components of a mobile system are specified as behavioral objects or Observational Transition Systems, a kind of transition system, enriched with special action and observation operators related to the distinct characteristics of mobile computing systems. The whole system comes up as the concurrent composition of these components. The implementation of the abstract model is achieved using CafeOBJ, an executable, industrial strength algebraic specification language. The visualization of the specification can be done using CafeOBJ graphical notation. In addition, invariant and behavioral properties of mobile systems can be proved through theorem proving techniques, such as structural induction and coinduction that are fully supported by the CafeOBJ system. The application of the proposed framework is presented through the modeling of a mobile computing environment and the services that need to be supported by the former.

We point out the unstable operation of reverse traffic management in the cdma2000 1xEV-DO system, and propose a new rate control scheme that controls the reverse traffic load more precisely. The proposed scheme is modeled as a multidimensional Markov process and compared with the conventional scheme. The analysis results show that the proposed rate control scheme has a lower overload probability and higher reverse link throughput than the conventional one.

We present a novel training method for recognizing traffic sign symbols. The symbol images captured by a car-mounted camera suffer from various forms of image degradation. To cope with degradations, similarly degraded images should be used as training data. Our method artificially generates such training data from original templates of traffic sign symbols. Degradation models and a GA-based algorithm that simulates actual captured images are established. The proposed method enables us to obtain training data of all categories without exhaustively collecting them. Experimental results show the effectiveness of the proposed method for traffic sign symbol recognition.

We survey traffic matrix models, whose elements represent the traffic demand between source-destination pair nodes. Modeling the traffic matrix is useful for multilayer Traffic Engineering (TE) in IP optical networks. Multilayer TE techniques make the network so designed flexible and reliable. This is because it allows reconfiguration of the virtual network topology (VNT), which consists of a set of several lower-layer (optical) paths and is provided to the higher layer, in response to fluctuations (diurnal) in traffic demand. It is, therefore, important to synthetically generate traffic matrices as close to the real ones as possible to maximize the performance of multilayer TE. We compare several models and clarify their applicability to VNT design and control. We find that it is difficult in practice to make an accurate traffic matrix with conventional schemes because of the high cost for data measurement and the complicated calculations involved. To overcome these problems, we newly introduce a simplified traffic matrix model that is practical; it well mirrors real networks. Next, this paper presents our developed server, the IP Optical TE server. It performs multilayer TE in IP optical networks. We evaluate the effectiveness of multilayer TE using our developed IP Optical server and the simplified traffic matrix. We confirm that multilayer TE offers significant CAPEX savings. Similarly, we demonstrate basic traffic control in IP optical networks, and confirm the dynamic control of the network and the feasibility of the IP Optical TE server.

This paper investigates the use of the affine transformation matrix when employing principal component analysis (PCA) to compress the data of 3D animation models. Satisfactory results were achieved for the common 3D models by using PCA because it can simplify several related variables to a few independent main factors, in addition to making the animation identical to the original by using linear combinations. The selection of the principal component factor (also known as the base) is still a subject for further research. Selecting a large number of bases could improve the precision of the animation and reduce distortion for a large data volume. Hence, a formula is required for base selection. This study develops an automatic PCA selection method, which includes the selection of suitable bases and a PCA separately on the three axes to select the number of suitable bases for each axis. PCA is more suitable for animation models for apparent stationary movement. If the original animation model is integrated with transformation movements such as translation, rotation, and scaling (RTS), the resulting animation model will have a greater distortion in the case of the same base vector with regard to apparent stationary movement. This paper is the first to extract the model movement characteristics using the affine transformation matrix and then to compress 3D animation using PCA. The affine transformation matrix can record the changes in the geometric transformation by using 44 matrices. The transformed model can eliminate the influences of geometric transformations with the animation model normalized to a limited space. Subsequently, by using PCA, the most suitable base vector (variance) can be selected more precisely.

The traffic with asymmetry between uplink and downlink has recently been getting remarkable on mobile communication systems providing multimedia communication services. In the future mobile communications, the accommodation of asymmetric traffic is essential to realize efficient multimedia mobile communication systems. This paper discusses asymmetric traffic accommodation in CDMA/FDD cellular packet communication systems and proposes its efficient scheme using an adaptive cell sizing technique. In the proposed scheme, each base station autonomously controls its coverage area so that almost the same communication quality can be achieved across the service area under the asymmetric traffic conditions. We present some numerical examples to demonstrate the effectiveness of the proposed scheme by using computer simulation. The simulation results show that, under asymmetric traffic conditions, the proposed scheme can provide fair communication quality across the service area in both links and can improve total transmission capacity in the uplink.

Burst assembly at edge nodes is an important issue for the Optical Burst Switching (OBS) networks because it has a great impact on the traffic characteristics. We analyze the assembled traffic of the Science Information Network (SINET) by using the Fractional Brownian Motion (FBM) model. The analytical and simulation results show that existing assembly schemes cannot avoid increasing the burstiness, which will deteriorate the network performance. Here, burstiness is defined as the variance of the bitrate in small timescales. Therefore, we address the issue of how to reduce the burstiness of the assembled network traffic. Firstly, a sliding window-based assembly algorithm is introduced to reduce the burstiness of assembled traffic by transmitting bursts at an average rate in a small timescale. Next, an advanced timer-based assembly algorithm is introduced, by which the traffic rate is smoothed out by restricting the burst length to a threshold. The simulation results show that both the sliding window-based and advanced timer-based assembly algorithms perform better than existing assembly algorithms do in terms of the burst loss ratio. The simulation also indicates that the advanced timer-based assembly algorithm performs better in terms of the edge buffering delay than the sliding window-based assembly algorithm does.

Internet access traffic follows hourly patterns that depend on various factors, such as the periods users stay on-line at the access point (e.g. at home or in the office) or their preferences for applications. The clustering of Internet users may provide important information for traffic engineering and billing. For example, it can be used to set up service differentiation according to hourly behavior, resource optimization based on multi-hour routing and definition of tariffs that promote Internet access in low busy hours. In this work, we propose a methodology for clustering Internet users with similar patterns of Internet utilization, according to their hourly traffic utilization. The methodology resorts to three statistical multivariate analysis techniques: cluster analysis, principal component analysis and discriminant analysis. The methodology is illustrated through measured data from two distinct ISPs, one using a CATV access network and the other an ADSL one, offering distinct traffic contracts. Principal component analysis is used as an exploratory tool. Cluster analysis is used to identify the relevant Internet usage profiles, with the partitioning around medoids and Ward's method being the preferred clustering methods. For the two data sets, these methods lead to the choice of 3 clusters with different hourly traffic utilization profiles. The cluster structure is validated through discriminant analysis. It is also evaluated in terms of several characteristics of the user traffic not used in the cluster analysis, such as the type of applications, the amount of downloaded traffic, the activity duration and the transfer rate, resulting in coherent outcomes.

Traffic markers differentiate among packets from senders based on their service profile in the differentiated service networks. Researchers have previously revealed that the existing marking mechanism causes the unfairness in aggregates. This study presents a new marking algorithm. Simulation results demonstrate that the fairness of the proposed scheme exceeds that of SRTCM, TRTCM, TSWTCM and ITSWTCM for medium to high network provision levels.

In order to reconstruct 3-D Euclidean shape by the Tomasi-Kanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and paraperspective. We present a new method that does not require any such specific models. We show that a minimal requirement for an affine camera to mimic perspective projection leads to a unique camera model, called symmetric affine camera, which has two free functions. We determine their values from input images by linear computation and demonstrate by experiments that an appropriate camera model is automatically selected.

One approach to accommodating IP traffic on a wavelength division multiplexing (WDM) network is to construct a logical topology, establishing a set of lightpaths between nodes. The lightpaths carry IP traffic but do not require any electronic packet processing at intermediate nodes, thereby reducing the load on those nodes. When the IP and WDM networks have independent routing functions, however, the lightpaths in the WDM network may not be fully utilized by the IP router. It is therefore necessary to integrate the two routing mechanisms in order to utilize resources efficiently and adapt to changes in traffic. In this paper, we propose an integrated routing mechanism for IP over WDM networks. The key idea is to first prepare a set of virtual-links representing the lightpaths that can be established by the WDM network, then calculate the minimum cost route on an IP network including those links. Our simulation results show that when traffic patterns do not change, the throughput of our method is almost the same as that of a logical topology optimally designed for a given traffic demand. When traffic patterns change, the throughput of our method is about 50% higher than that of the logical topology.

This paper addresses the issue of deafness in MAC (Medium Access Control) protocols for wireless ad hoc networks using directional antennas. Directional antennas are expected to provide significant improvements over omni-directional antennas in ad hoc networks, such as high spatial reuse and range extension. Recently, several MAC protocols using directional antennas, typically referred to as directional MAC protocols, have been proposed for ad hoc networks. However, directional MAC protocols inherently introduce new kinds of problems arising from directivity. One major problem is deafness, caused by a lack of state information of neighbor nodes, whether idle or busy. This paper proposes DMAC/DA (Directional MAC with Deafness Avoidance) to overcome the deafness problem. DMAC/DA modifies the previously proposed MAC protocol, MDA (MAC protocol for Directional Antennas), to reduce the number of control messages and also maintain the ability to handle deafness. In DMAC/DA, WTS (Wait To Send) frames are simultaneously transmitted by the transmitter and the receiver after the successful exchange of directional RTS (Request To Send) and CTS (Clear To Send) to notify the on-going communication to potential transmitters that may experience deafness. The experimental results show that DMAC/DA outperforms existing directional MAC protocols, such as DMAC (Directional MAC) and MDA, in terms of throughput, control overhead and packet drop ratio under the different values of parameters such as the number of flows and the number of beams. In addition, qualitative evaluation of 9 MAC protocols is presented to highlight the difference between DMAC/DA and existing MAC protocols.

Multipath routing employs multiple parallel paths between the source and destination for a connection request to improve resource utilization of a network. In this paper, we present an integrated design of multipath routing with delay constraints and failure survivability in MPLS networks. By combining the failure survivability schemes into the multipath routing algorithms, path protection or restoration policies will enable the network to accommodate link failures and at the same time achieve significant improvement on network resource utilization. We propose a number of multipath routing algorithms, working-backup path selection and bandwidth allocation schemes. We evaluate the performance of the proposed schemes in terms of call blocking probability, network resource utilization and load balancing factor. Extensive simulation results validate the effectiveness of the proposed schemes. In particular, we compare these multipath schemes to the existing failure recovery schemes that mostly focus on single path routing. The results demonstrate that the proposed integrated design framework can provide effective network failure survivability, and also achieve better load balancing and/or higher network resource utilization.

From the introduction of CodeRed and Slammer worms, it has been learned that the early detection of worm epidemics is important in order to reduce the damage resulting from outbreaks. A prominent characteristic of Internet worms is the random selection of subsequent targets. In this paper, we propose a new worm detection mechanism by checking the random distribution of destination addresses in network traffic. The proposed mechanism constructs a matrix from network traffic and checks the rank of the matrix in order to detect the spreading of Internet worms. From the fact that a random binary matrix holds a high rank value, ADUR (Anomaly Detection Using Randomness check) is proposed for detecting unknown worms based on the rank of the matrix. From experiments on various environments, it is demonstrated that the ADUR mechanism effectively detects the spread of new worms in the early stages, even when there is only a single host infected in a monitoring network. Also, we show that ADUR is highly sensitive so that the worm epidemic can be detectable quickly, e.g., three times earlier than the infection of 90% vulnerable hosts.