This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.

Intrusion detection system (IDS) has played an important role as a device to defend our networks from cyber attacks. However, since it is unable to detect unknown attacks, i.e., 0-day attacks, the ultimate challenge in intrusion detection field is how we can exactly identify such an attack by an automated manner. Over the past few years, several studies on solving these problems have been made on anomaly detection using unsupervised learning techniques such as clustering, one-class support vector machine (SVM), etc. Although they enable one to construct intrusion detection models at low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we propose a new anomaly detection method based on clustering and multiple one-class SVM in order to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that our approach outperforms the existing algorithms reported in the literature; especially in detection of unknown attacks.

Recently, the result of TinyECCK (Tiny Elliptic Curve Cryptosystem with Koblitz curve) shows that both field multiplication and reduction over GF(2m) are related to a heavy amount of duplicated memory accesses and that reducing the number of these duplications noticeably improves the performance of elliptic curve operations such as scalar multiplications, signing and verification. However, in case that the underlying word size is extended from 8-bit to 16-bit or 32-bit, the efficiency of the techniques proposed in TinyECCK is decreased because the number of memory accesses to load or store an element in GF(2m) is significantly reduced. Therefore, in this paper, we propose a technique which makes left-to-right (ltr) comb method which is widely used as an efficient multiplication algorithm over GF(2m) suitable for extended word sizes and present TinyECCK16 (Tiny Elliptic Curve Cryptosystem with Koblitz curve on 16-bit word) which is implemented with the proposed multiplication algorithm on 16-bit Tmote Sky mote. The proposed algorithm is faster than typical ltr comb method by 15.06% and the 16-bit version of the algorithm proposed in TinyECCK by 5.12% over GF(2163).

Given a sparse linear system, A x = b, we can solve the equivalent system P A PT y = P b, x = PT y, where P is a permutation matrix. It has been known that, for example, when P is the RCMK (Reverse Cuthill-Mckee) ordering permutation, the convergence rate of the Krylov subspace method combined with the ILU-type preconditioner is often enhanced, especially if the matrix A is highly nonsymmetric. In this paper we offer a reordering heuristic for accelerating the solution of large sparse linear systems by the Krylov subspace methods with the ILUT preconditioner. It is the LRB (Line Red/Black) ordering based on the well-known 2-point Red-Black ordering. We show that for some model-like PDE (partial differential equation)s the LRB ordered FDM (Finite Difference Method)/FEM (Finite Element Method) discretization matrices require much less fill-ins in the ILUT factorizations than those of the Natural ordering and the RCMK ordering and hence, produces a more accurate preconditioner, if a high level of fill-in is used. It implies that the LRB ordering could outperform the other two orderings combined with the ILUT preconditioned Krylov subspace method if the level of fill-in is high enough. We compare the performance of our heuristic with that of the RCMK (Reverse Cuthill-McKee) ordering. Our test matrices are obtained from various standard discretizations of two-dimensional and three-dimensional model-like PDEs on structured grids by the FDM or the FEM. We claim that for the resulting matrices the performance of our reordering strategy for the Krylov subspace method combined with the ILUT preconditioner is superior to that of RCMK ordering, when the proper number of fill-in was used for the ILUT. Also, while the RCMK ordering is known to have little advantage over the Natural ordering in the case of symmetric matrices, the LRB ordering still can improve the convergence rate, even if the matrices are symmetric.

In recent years huge potential benefits from novel applications in mobile ad hoc networks (MANET) have been discussed extensively. However, without robust security mechanisms and systems to provide safety shell through the MANET infrastructure, MANET applications can be vulnerable and hammered by malicious attackers easily. In order to detect misbehaved message routing and identify malicious attackers in MANET, schemes based on reputation concept have shown their advantages in this area in terms of good scalability and simple threshold-based detection strategy. We observed that previous reputation schemes generally use predefined thresholds which do not take into account the effect of behavior dynamics between nodes in a period of time. In this paper, we propose a Threshold-Adaptive Reputation System (TARS) to overcome the shortcomings of static threshold strategy and improve the overall MANET performance under misbehaved routing attack. A fuzzy-based inference engine is introduced to evaluate the trustiness of a node's one-hop neighbors. Malicious nodes whose trust values are lower than the adaptive threshold, will be detected and filtered out by their honest neighbors during trustiness evaluation process. The results of network simulation show that the TARS outperforms other compared schemes under security attacks in most cases and at the same time reduces the decrease of total packet delivery ratio by 67% in comparison with MANET without reputation system.

This paper proposes a novel RBF training algorithm based on immune operations for dynamic problem solving. The algorithm takes inspiration from the dynamic nature of natural immune system and locally-tuned structure of RBF neural network. Through immune operations of vaccination and immune response, the RBF network can dynamically adapt to environments according to changes in the training set. Simulation results demonstrate that RBF equalizer based on the proposed algorithm obtains good performance in nonlinear time-varying channels.

Single-carrier (SC) multiple access is a promising uplink multiple access technique because of its low peak-to-average power ratio (PAPR) property and high frequency diversity gain that is achievable through simple one-tap frequency-domain equalization (FDE) in a strong frequency-selective channel. The multiple access capability can be obtained by combining either frequency division multiple access (FDMA) or code division multiple access (CDMA) with SC transmission. In this article, we review the recent research on the SC multiple access techniques with one-tap FDE. After introducing the principle of joint FDE/antenna diversity combining, we review various SC multiple access techniques with one-tap FDE, i.e., SC-FDMA, SC-CDMA, block spread CDMA, and delay-time/CDMA.

This paper proposes a point-to-multipoint (P2MP) Multi-Protocol Label Switching (MPLS) based hierarchical service management system. Traditionally, general management systems deployed in some service providers control MPLS Label Switched Paths (LSPs) (e.g., RSVP-TE and LDP) and services (e.g., L2VPN, L3VPN and IP) separately. In order for dedicated management systems for MPLS LSPs and services to cooperate with each other automatically, a hierarchical service management system has been proposed with the main focus on point-to-point (P2P) TE LSPs in MPLS path management. In the case where P2MP TE LSPs and services are deployed in MPLS networks, the dedicated management systems for P2MP TE LSPs and services must work together automatically. Therefore, this paper proposes a new algorithm that uses a correlation between P2MP TE LSPs and multicast VPN services based on a P2MP MPLS-based hierarchical service management architecture. Also, the capacity and performance of the proposed algorithm are evaluated by simulations, which are actually based on certain real MPLS production networks, and are compared to that of the algorithm for P2P TE LSPs. Results show this system is very scalable within real MPLS production networks. This system, with the automatic correlation, appears to be deployable in real MPLS production networks.

A time synchronization protocol for WSN is required to compensate time discrepancy. Time discrepancy among sensor nodes inevitably happens in WSN due to several internal and external factors. In order to make WSN's own job done effectively, a time synchronization protocol should be designed to achieve low execution time and low network traffic as well as accurate synchronization. Several synchronization protocols have been proposed to provide accurate time synchronization but do not consider execution time and network traffic for time synchronization. This paper proposes MNTP; it provides rapid and accurate time synchronization in multi-hop communication range. It presents a new broadcast scheme and time stamping mechanism to achieve low execution time and low network traffic along with accurate synchronization. Evaluation results show that MNTP improves synchronization accuracy up to 22% in single-hop and 51% in multi-hop respectively. MNTP also has 67 times and 58 times lower execution time and network traffic when 300 nodes are deployed in 2020 m2 sensor field.

With proliferation of smart handsets capable of mobile Internet, the severity of malware attacks targeting such handsets is rapidly increasing, thereby requiring effective countermeasure for them. However, existing signature-based solutions are not suitable for resource-poor handsets due to the excessive run-time overhead of matching against ever-increasing malware pattern database as well as the limitation of detecting well-known malware only. To overcome these drawbacks, we present a bio-inspired approach to discriminate malware (non-self) from normal programs (self) by replicating the processes of biological immune system. Our proposed approach achieves superior performance in terms of detecting 83.7% of new malware or their variants and scalable storage requirement that grows very slowly with inclusion of new malware, making it attractive for use with mobile handsets.

A state-discretization approach [11], which was introduced for stability of constant delayed systems, will be extended to time-varying delayed systems. The states not only in constructing the Lyapunov-Krasovskii functional but also in designing the integral inequality technique [12] will be discretized. Based on the discretized-state, [9],[17] 's piecewise analysis method will be applied to confirm the system stability in whole delay bound. Numerical examples show that the results obtained by this criterion improve the allowable delay bounds over the existing results in the literature.

Utilizing a heterogeneous multiprocessor system has become a popular design paradigm to build an embedded system at a cheap cost within short development time. A reliability issue for embedded systems, which is vulnerability to single event upsets (SEUs), has become a matter of concern as technology proceeds. This paper discusses reliability inherent in heterogeneous multiprocessors and proposes task scheduling for minimizing SEU vulnerability of them. This paper experimentally shows that increasing performance of a CPU core deteriorates its reliability. Based on the experimental observation, we propose task scheduling for reducing SEU vulnerability of a heterogeneous multiprocessor system. The experimental results demonstrate that our task scheduling technique can reduce much of SEU vulnerability under real-time constraints.

The proposed quasi-resonant (QR) zero current switching (ZCS) switched-capacitor (SC) converter is a new type of bidirectional power flow control conversion scheme. The proposed converter is able to provide voltage conversion ratios from -3/- (triple-mode/ trisection-mode) to -n/- (-n-mode/--mode) by adding a different number of switched-capacitors and power MOSFET switches with a small series connected resonant inductor for forward and reverse power flow control schemes. It possesses the advantages of low switching losses and current stress in this QR ZCS SC converter. The principle of operation, theoretical analysis of the proposed triple-mode/ trisection-mode bidirectional power conversion scheme is described in detail with circuit model analysis. Simulation and experimental studies are carried out to verify the performance of the proposed inverting type ZCS SC QR bidirectional converter. The proposed converters can be applied to battery equalization for battery management system (BMS).

We propose an MRAM macro architecture for SoCs to reduce their area size. The shared write-selection transistor (SWST) architecture is based on 2T1MTJ MRAM cell technology, which enables the same fast access time with a smaller cell area than that of 6T SRAMs. We designed a 4-Mb macro using the SWST architecture with a 0.15-µm CMOS process and a 0.24-µm MRAM process. The macro cell array consists of 81T64MTJ cell array elements, each storing 64 bits of data. The area size is reduced by more than 30%. By introducing a leakage-replication (LR) read scheme, a wide read margin on a test chip is accomplished and 50-ns access time is achieved with SPICE simulation. The 2T1MTJ macro and 81T64MTJ macro can be integrated into a single SoC.

A signal detection system using noise statistical processing is proposed. By approaching the problems of low voltage and high noise from miniaturization of a device from a stochastic point of view, a faint-signal receiving system that can effectively detect subthreshold and noise level signals has been developed. In addition, an alternative to statistical processing is proposed, and would be successfully implemented on a circuit. For the proposed signal detection method, the detection sensitivity was investigated using numerical simulation, and the detection sensitivity was sufficiently high to detect even a signal with a signal-to-inherent-noise ratio of -14 dB. Thus, it is anticipated that the application of this system to an integrated circuit will have a significant impact on signal processing.

This paper presents a deadbeat control scheme for linear systems with state constraints. The proposed controller increases the number of steps on-line for the deadbeat tracking performance, satisfying given admissible state constraints. LMI conditions are given to minimize the unavoidable step delay. The proposed schemes can be easily developed by using LMI approach, and are validated by numerical simulation.

In this article, we introduce a new concept for the future information environment, called an "ambient information environment (AmIE)." We first explain it, especially emphasizing the difference from the existing ubiquitous information environment (UbIE), which is an interaction between users and environments. Then, we focus on an ambient networking environment (AmNE) which supports the AmIE as a networking infrastructure. Our approach of a biologically inspired framework is next described in order to demonstrate why such an approach is necessary in the AmIE. Finally, we show some example for building the AmNE.

This paper proposes a software-controllable variable line-size (SC-VLS) cache architecture for low power embedded systems. High bandwidth between logic and a DRAM is realized by means of advanced integrated technology. System-in-Silicon is one of the architectural frameworks to realize the high bandwidth. An ASIC and a specific SRAM are mounted onto a silicon interposer. Each chip is connected to the silicon interposer by eutectic solder bumps. In the framework, it is important to reduce the DRAM energy consumption. The specific DRAM needs a small cache memory to improve the performance. We exploit the cache to reduce the DRAM energy consumption. During application program executions, an adequate cache line size which produces the lowest cache miss ratio is varied because the amount of spatial locality of memory references changes. If we employ a large cache line size, we can expect the effect of prefetching. However, the DRAM energy consumption is larger than a small line size because of the huge number of banks are accessed. The SC-VLS cache is able to change a line size to an adequate one at runtime with a small area and power overheads. We analyze the adequate line size and insert line size change instructions at the beginning of each function of a target program before executing the program. In our evaluation, it is observed that the SC-VLS cache reduces the DRAM energy consumption up to 88%, compared to a conventional cache with fixed 256 B lines.

This paper studies a simple spiking oscillator having piecewise constant vector field. Repeating vibrate-and-fire dynamics, the system exhibits various spike-trains and we pay special attention to chaotic spike-trains having line-like spectrum in distribution of inter-spike intervals. In the parameter space, existence regions of such phenomena can construct infinite window-like structures. The system has piecewise linear trajectory and we can give theoretical evidence for the phenomena. Presenting a simple test circuit, typical phenomena are confirmed experimentally.

Tracking a large quantity of moving target tags simultaneously is essential for the localization and guidance of people in welfare facilities like hospitals and sanatoriums for the aged. The locating system using active RFID technology consists of a number of fixed RFID readers and tags carried by the target objects, or senior people. We compare the performances of several determination algorithms which use the power measurement of received signals emitted by the moving active RFID tags. This letter presents a study on the effect of collision in tracking large quantities of objects based on active RFID real time location system (RTLS). Traditional trilateration, fingerprinting, and well-known LANDMARC algorithm are evaluated and compared with varying number of moving tags through the SystemC-based computer simulation. From the simulation, we show the tradeoff relationship between the number of moving tags and estimation accuracy.