Multi-pattern matching is a key technique for implementing network security applications such as Network Intrusion Detection/Protection Systems (NIDS/NIPSes) where every packet is inspected against tens of thousands of predefined attack signatures written in regular expressions (regexes). To this end, Deterministic Finite Automaton (DFA) is widely used for multi-regex matching, but existing DFA-based researches have claimed high throughput at an expense of extremely high memory cost, so fail to be employed in devices such as high-speed routers and embedded systems where the available memory is quite limited. In this paper, we propose a parallel architecture of DFA called Parallel DFA (PDFA) taking advantage of the large amount of concurrent flows to increase the throughput with nearly no extra memory cost. The basic idea is to selectively store the underlying DFA in memory modules that can be accessed in parallel. To explore its potential parallelism we intensively study DFA-split schemes from both state and transition points in this paper. The performance of our approach in both the average cases and the worst cases is analyzed, optimized and evaluated by numerical results. The evaluation shows that we obtain an average speedup of 100 times compared with traditional DFA-based matching approach.

TCP's performance significantly degrades in multi-hop wireless networks because TCP's retransmission timeouts (RTOs) are frequently triggered regardless of congestion due to sudden delay and wireless transmission errors. Such RTOs non-related to congestions lead to TCP's unnecessary behaviors such as retransmitting all the outstanding packets which might be located in the bottleneck queue or reducing sharply its sending rate and increasing exponentially its back-off value even when the network is not congested. Since traditional TCP has no ability to identify if a RTO is triggered by congestion or not, it is unavoidable for TCP to underutilize available bandwidth by blindly reducing its sending rate for all the RTOs. In this paper, we propose an algorithm to detect the RTOs non-related to congestion in order to let TCP respond to the RTOs differently according to the cause. When a RTO is triggered, our algorithm estimates the queue usage in the network path during the go-back-N retransmissions, and decides if the RTO is triggered by congestion or not when the retransmissions end. If any RTO non-related to congestion is detected, our algorithm prevents TCP from increasing unnecessarily its back-off value as well as reducing needlessly its sending rate. Throughout the extensive simulation scenarios, we observed how frequently RTOs are triggered regardless of congestion, and evaluated our algorithm in terms of accuracy and goodput. The experiment results show that our algorithm has the highest accuracy among the previous works and the performance enhancement reaches up to 70% when our algorithm is applied to TCP.

This paper proposes a concept for a new technical field called wireless distributed network (WDN) as a strategic technical field to enable flexible networking and radio resource management (RRM) to cope with dynamic variation of spatially distributed traffic demands. As the core technical subject areas for the WDN, this paper identifies distributed networking for flexible network creation, cooperative transmission and reception for flexible link creation, and dynamic spectrum access for flexible radio resource management, and explains their technical features and challenges for constructing the WDN. This paper also discusses some already being studied application fields as well as potential future directions of the WDN applications.

Reliable data transmission is desirable in wireless sensor networks due to the high packet loss rate during multi-hop transmissions. To reliably transmit data for event-driven applications, packet loss recovery mechanism is needed. For loss recovery, sensor nodes need to keep packets in their buffers until transmissions successfully complete. However, since sensor nodes have limited memory, packets cannot be buffered for a long period of time. This letter proposes an efficient buffer management technique that caches data packets for appropriate amount of time to minimize the resource requirements and at the same time provide reliable data transmission among sensor nodes.

This paper proposes a prioritized aggregation method that supports compressed video transmission on millimeter wave wireless personal area network (mmWave WPAN) systems. Frame aggregation is an effective means to improve system efficiency and throughput for wide band systems such as mmWave WPAN. It is required by the applications that the mmWave WPAN systems should provide Gbps or multiGbps transmission capability. The proposed scheme targets not only transmission efficiency but also support of compressed video transmission which currently is very popular. The proposal combines MAC layer aggregation with PHY layer skew modulation to facilitate the video transmission in a way that more important data is better protected. Simulation results show that the average peak signal to noise ratio (PSNR) performance is improved by 5 dB compared to conventional method, while the Gbps transmission requirement is fulfilled.

The biggest challenge in multi-cell MIMO multiplexing systems is how to effectively suppress the other-cell interference (OCI) since the OCI severely decrease the system performance. Cooperation among cells is one of the most promising solutions to OCI problems. However, this solution suffers greatly from delay and overhead issues, which make it impractical. A coordinated MIMO system with a simplified cooperation between the base stations is a compromise between the theory and practice. We aim to devise an effective resource allocation algorithm based on a coordinated MIMO system that largely alleviates the OCI. In this paper, we propose a joint resource allocation algorithm incorporating intra-cell beamforming multiplexing and inter-cell interference suppression, which adaptively allocates the transmitting power and schedules users while achieving close to an optimal system throughput under proportional fairness consideration. We formulate this problem as a nonlinear combinational optimization problem, which is hard to solve. Then, we decouple the variables and transform it into a problem with convex sub-problems that can be solve but still need heavy computational complexity. In order to implement the algorithm in real-time scenarios, we reduce the computational complexity by assuming an equal power allocation utility to do user scheduling before the power allocation. Extensive simulation results show that the joint resource allocation algorithm can achieve a higher throughput and better fairness than the traditional method while maintains the proportional fairness. Moreover, the low-complexity algorithm obtains a better fairness and less computational complexity with only a slight loss in throughput.

Distributed networks employing collaborative transmission (CT) from remote antennas can provide improved system capacity and cell-edge performance, by using appropriate transmission strategies. When compared to conventional non-collaborative transmission (NCT) from one base station (BS), we show that CT from two adjacent BSs can be beneficial in terms of the capacity, even when the transmission rate is normalized by the number of collaborating BSs. We further demonstrate that performing adaptive transmission (AT) between NCT and CT based on the instantaneous channel conditions provide an additional gain in capacity. The exact amount of achievable gain is quantified by the closed-form formula for the capacity distribution, which is derived using the Jacobian transformation. The presented distribution is immediately applicable to 6-sectored distributed cellular network, for which we present numerical verification of the results.

The safety applications for cooperative driving in VANETs, typically require the dissemination of safety-related information to all vehicles with high reliability and a strict timeline. However, due to the high vehicle mobility, dynamic traffic density, and a self-organized network, Safety message dissemination has a special challenge to efficiently use the limited network resources to satisfy its requirements. With this motivation, we propose a novel broadcasting protocol referred to as congestion awareness multi-hop broadcasting (CAMB) based loosely on a TDMA-like transmission scheduling scheme. The proposed protocol was evaluated using different traffic scenarios within both a realistic channel model and an 802.11p PHY/MAC model in our simulation. The simulation results showed that the performance of our CAMB protocol was better than those of the existing broadcasting protocols in terms of channel access delay, packet delivery ratio, end-to-end delay, and network overhead.

In an embedded control system, control performances of each job depend on its latency and a control algorithm implemented in it. In order to adapt a job set to optimize control performances subject to schedulability, we design several types of control software for each job, which will be called versions, and select one version from them when the job is released. A real-time system where each job has several versions is called a multiversion real-time system. A benefit and a CPU utilization of a job depend on the versions. So, it is an important problem to select a version of each job so as to maximize the total benefit of the system subject to a schedulability condition. Such a problem will be called an optimal configuration problem. In this paper, we assume that each version is specified by the relative deadline, the execution time, and the benefit. We show that the optimal configuration problem is transformed to a maximum path length problem. We propose an optimal algorithm based on the forward dynamic programming. Moreover, we propose sub-optimal algorithms to reduce computation times. The efficiencies of the proposed algorithms are illustrated by simulations.

An antidictionary is particularly useful for data compression, and on-line electrocardiogram (ECG) lossless compression algorithms using antidictionaries have been proposed. They work in real-time with constant memory and give better compression ratios than traditional lossless data compression algorithms, while they only deal with ECG data on a binary alphabet. This paper proposes on-line ECG lossless compression for a given data on a finite alphabet. The proposed algorithm gives not only better compression ratios than those algorithms but also uses less computational space than they do. Moreover, the proposed algorithm work in real-time. Its effectiveness is demonstrated by simulation results.

The letter proposes a novel binary vulnerability analyzer for executable programs that is based on the Hidden Markov Model. A vulnerability instruction library (VIL) is primarily constructed by collecting binary frames located by double precision analysis. Executable programs are then converted into structurized code sequences with the VIL. The code sequences are essentially context-sensitive, which can be modeled by Hidden Markov Model (HMM). Finally, the HMM based vulnerability analyzer is built to recognize potential vulnerabilities of executable programs. Experimental results show the proposed approach achieves lower false positive/negative rate than latest static analyzers.

Spectrum sensing is a fundamental function for cognitive radio network to protect transmission of primary system. Cooperative spectrum sensing, which can help increasing sensing performance, is regarded as one of the most promising methods in realizing a reliable cognitive network. In such cooperation system, however the communication resources such as sensing time delay, control channel bandwidth and consumption energy for reporting the cognitive radio node's sensing results to the fusion center may become extremely huge when the number of cognitive users is large. In this paper, we propose an ordered sequential cooperative spectrum sensing scheme in which the local sensing data will be sent according to its reliability order to the fusion center. In proposed scheme, the sequential fusion process is sequentially conducted based on Dempster Shafer theory of evidence's combination of the reported sensing results. Above all, the proposed scheme is highly feasible due to the proposed two ordered sequential reporting methods. From simulation results, it is shown that the proposed technique not only keeps the same sensing performance of non-sequential fusion scheme but also extremely reduces the reporting resource requirements.

In this paper, a scheme for constructing the flat frequency spectrum of interleaved frequency division multiple access (IFDMA) is proposed. Since IFDMA is one of the single carrier modulation schemes, the frequency spectrum components are fluctuated and depend on the information data sequence. Even if IFDMA modulation scheme makes frequency spectrum dispersive for obtaining frequency diversity gain, frequency diversity gain is reduced by the fluctuation of frequency spectrum. In addition, in decision directed channel estimation (DDCE), which achieves good channel estimation accuracy in fast fading environment, the accuracy of channel transfer function estimated at the significant attenuated frequency component is much degraded. In the proposed technique, a random phase sequence is multiplied to the information data sequence for constructing the flat frequency spectrum. As a result, the frequency diversity gain is enlarged and the accuracy of channel estimation by DDCE is improved. Furthermore, we consider the blind estimation technique for the random phase sequence selected by transmitter. We show the effects of the proposed scheme by computer simulation.

We present an orthogonal frequency division multiple access (OFDMA) based multichannel slotted ALOHA for cognitive radio networks (OMSA-CR). The performance of an infinite population based OMSA-CR system is analyzed in terms of channel capacity, throughput, delay, and packet capture effect. We investigate the channel capacity for OMSA-CR with perfect or imperfect spectrum sensing. We introduce the proposed CR MAC based on two channel selection schemes: non-agile channel selection (NCS) and agile channel selection (ACS). Comparing them, we show the tradeoff between complexity and system performance. We verify the proposed CR system model using numerical analysis. In particular, using simulation with a finite populated linear feedback model, we observe the OMSA-CR MAC tradeoff between throughput and minimum delay whose results matched those of the analytical framework. Numerical results for the proposed system throughput are also compared to conventional MACs, including pure ALOHA based CR MAC.

We propose Turbo-coded two-dimensional (2-D) free-space optical (FSO) CDMA systems for broadband access networks. The performance bound for the proposed system over atmospheric turbulence channels is obtained considering multiple-access interference (MAI) and receiver noise. The results show that the proposed system offers a better performance than that of previously proposed ones. Also, it has a better tolerance to the atmospheric turbulence and the increase in the number of users.

Base Station (BS) cooperation has been considered as a promising technology to mitigate co-channel interference (CCI), yielding great capacity improvement in cellular systems. In this paper, by combining frequency domain cooperation and space domain cooperation together, we design a new CCI mitigation scheme to maximize the total utility for a multi-cell OFDMA network. The scheme formulates the CCI mitigation problem as a mixture integer programming problem, which involves a joint user-set-oriented subcarrier assignment and power allocation. A computationally feasible algorithm based on Lagrange dual decomposition is derived to evaluate the optimal value of the problem. Moreover, a low-complexity suboptimal algorithm is also presented. Simulation results show that our scheme outperforms the counterparts incorporating BS cooperation in a single domain considerably, and the proposed low-complexity algorithm achieves near optimal performance.

It is known that traditional water-filling provides a closed form solution for capacity maximization in frequency-selective channels or fading channels with adaptive modulation. However, the solution is derived from a maximum mutual information argument with a single total power constraint. Motivated by the new technology of coordinated multiple point transmission (CoMP), this paper considers a novel power allocation scheme for a frequency-selective fading channel with multiple coordinated transmission points (CTP) transmission, in which each CTP has a power constraint and an individual channel state information (CSI). In order to maximize the channel's throughput, closed form solutions are obtained by solving a non-convex constrained optimization problem. The solution turns out to take the form of traditional WF and also combined with some regular cooperative feature. Based on the derived solution, we firstly investigate a joint water-filling (Jo-WF) power allocation scheme and a new iterative Jo-WF algorithm. Numerical results are presented to verify the optimality of the derived scheme and to show throughput gains over traditional non-coordinated water-filling (WF) and equal power allocation (EPA). Considering the flexibility of CTP's category, e.g., base station or relay station, it is known that the derived Jo-WF power allocation scheme can be valid for any coordinated networks such as next-generation cellular networks or ad-hoc networks.

Multimedia applications such as video and audio have recently come into much wider use. Because this heterogeneous traffic consumes most of the network's resources, call admission control (CAC) is required to maintain high-quality services. User satisfaction depends on CAC's success in accommodating application flows. Conventional CACs do not take into consideration user satisfaction because their main purpose is to improve the utilization of resources. Moreover, if we assume a service where an ISP provides a "flat-based charging," each user may receive same user satisfaction as a result of users being accommodated in a network, even if each has a different bandwidth. Therefore, we propose a novel CAC to maximize total user satisfaction based on a new philosophy where heterog eneous traffic is treated equally in networks. Theoretical analysis is used to derive optimal thresholds for various traffic configurations with a full search system. We also carried out theoretical numerical analysis to demonstrate the effectiveness of our new CAC. Moreover, we propose a sub-optimal threshold configuration obtained by using an approximation formula to develop practical CAC from these observations. We tested and confirmed that performance could be improved by using sub-optimal parameters.

In this letter, an eigenspace of network topology is introduced to increase a spatial capacity. The network topology is represented as an adjacency matrix. By an eigenvector of adjacency matrix, efficient two way transmission can be realized in wireless distributed networks. It is confirmed by numerical analysis that the scheme with an eigenvector of adjacency matrix supplies higher spatial capacity and reliability than that of conventional scheme.

This paper presents a voltage reference that utilizes the virtually diode-connected MOS transistors, biased in the weak-inversion region. The proposed architecture increases the gain of the feedback loop that consequently reduces the system sensitivity, and hence improves the PSRR. The circuit is designed and simulated in a standard 0.18 µm CMOS technology. The simulation results in HSPICE indicate the successful operation of the circuit as follows: the PSRR at DC frequency is 86 dB and for the temperature range from -55C to 125C, the variation of the output reference voltage is less than 66 ppm/C.