As the demand for spectrum for future wireless communication services increases, cognitive radio technology has been developed for dynamic and opportunistic spectrum access, which enables the secondary users to use the underutilized licensed spectrum of the primary users. In particular, the recent studies on the MAC protocol for dynamic and opportunistic access have focused on sensing and using the vacant spectrum efficiently. Under the ad-hoc network environment, how the secondary users use the unused channels by the primary users affects the efficient utilization of channels and a cognitive radio system is required to follow the rapid and frequent changes in channel status. In this paper, we propose a self-scheduling multi-channel cognitive MAC (SMC-MAC) protocol, which allows multiple secondary users to transmit data though the sensed idle channels by two cooperative channel sensing algorithms, i.e., fixed channel sensing (FCS) and adaptive channel sensing (ACS), and by slotted contention mechanism to exchange channel request information for self-scheduling. The performance of the proposed SMC-MAC protocol is investigated via analysis and simulations. According to the results, the proposed SMC-MAC protocol is effective in allowing multiple secondary users to transmit data frames effectively on multi-channels and adaptively in response to the primary users' traffic dynamics.

In this letter, we propose a Partially Observable Markov Decision Process (POMDP) based Distributed Adaptive Opportunistic Spectrum Access (DA-OSA) Strategy for Cognitive Ad Hoc Networks (CAHNs). In each slot, the source and destination choose a set of channels to sense and then decide the transmission channels based on the sensing results. In order to maximize the throughput for each link, we use the theories of sequential decision and optimal stopping to determine the optimal sensing channel set. Moreover, we also establish the myopic policy and exploit the monotonicity of the reward function that we use, which can be used to reduce the complexity of the sequential decision.

The performance of spectrum sensing in cognitive radio can be improved by employing multiple antennas. In this letter, the effect of antenna correlation on the performance improvement by deploying multiple antennas in the sensing node of the secondary system is investigated. It is proved mathematically that in the regime of low SNR, with antenna correlation, the secondary sensing node can achieve almost the same performance improvement as that without correlation. Simulation results verify the conclusions.

Transmission coordination mechanism (TCM) aids opportunistic routing (OR) to reduce the total number of packet transmissions and improve end-to-end throughput. Existing paradigms based on batch map partitions packets of communication session into segments, and transmit packet segments in batch mode sequentially. However, the rate of successful transmission coordination oscillates due to the oscillation of the number of packets batch transmitted. In this paper, we propose batch sliding window-based TCM to improve the performance of OR. By transmitting packets in continuous batch mode, batch sliding window-based TCM can hold the rate of successful transmission coordination steady. Simulation results show the average end-to-end throughput gain of the proposed TCM is 15.4% over existing batch map-based TCM.

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.

Several papers have presented measured function to handle multi-criteria fuzzy decision-making problems based on interval-valued intuitionistic fuzzy sets. However, in some cases, the proposed function cannot give sufficient information about alternatives. Consequently, in this paper, we will overcome previous insufficient problem and provide a novel accuracy function to measure the degree of the interval-valued intuitionistic fuzzy information. And a practical example has been provided to demonstrate our proposed approach. In addition, to make computing and ranking results easier and to increase the recruiting productivity, a computer-based interface system has been developed for decision makers to make decisions more efficiently.

In this letter, we present a flow-aware opportunistic routing protocol over wireless mesh networks. Firstly, a forwarder set selection mechanism is proposed to avoid potential flow contention, thus alleviating possible congestion from the increased number of flows. Secondly, a Round-Robin packet sending fashion combined with batch-by-batch acknowledgement is introduced to provide reliability and improve throughput. Evaluations show that our protocol significantly outperforms a seminal opportunistic routing protocol, MORE, under both single and multiple flow scenarios.

We propose an opportunistic spectrum access scheme for unslotted secondary users exploiting spectrum opportunities in unslotted primary networks. An analytical model is developed to investigate the performance of the proposed scheme, and numerical results are presented to evaluate the performance in unslotted primary networks.

In this paper, the outage probability and diversity order of opportunistic decode-and-forward (DF) cooperation are analyzed under Rayleigh fading channels, where the impacts of channel estimation error, relay selection feedback delay and the availability of the direct link between the source and the destination are considered comprehensively. The closed-form expressions of outage probability in the high signal-to-noise ratio (SNR) region are derived as well as the diversity order. The theoretical results demonstrate that the achievable diversity order is zero when channel estimation error exists, and this conclusion holds no matter whether the direct link is available, even if the relay selection feedback is delay-free. For the perfect channel estimation scenario, the achievable diversity order is related to the potential relay number K, the channel delay correlation coefficient ρd and the availability of the direct link. If relay selection feedback is not delayed, i.e., ρd = 1, the diversity order is K when the direct link is blocked, and it becomes K+1 when the direct link is available. For delayed relay selection feedback, i.e., ρd < 1, the diversity order achievable is only related to the availability of the direct link. In this case, if the direct link does not exist, the diversity order is 1, otherwise the diversity order of 2 can be obtained. Simulation results verify the analytical results of outage probability and diversity order.

In this letter, a dual-hop wireless communication network with opportunistic amplify and forward (O-AF) relay is investigated over independent and non-identically distributed Nakagami-m fading channels. Employing Maclaurin series expansion around zero to derive the approximate probability density function of the normalized instantaneous signal-to-noise ratio (SNR), the asymptotic symbol error rate (SER) and outage probability expressions are presented. Simulation results indicate that the derived expressions well match the results of Monte-Carlo simulations at medium and high SNR regions. By comparing the O-AF with all AF relaying analyzed previously, it can be concluded that the former has significantly better performance than the latter in many cases.

In this paper, we study an opportunistic scheduling scheme for the TDMA wireless network with relay stations. We model the time-varying channel condition of a wireless link as a stochastic process. Based on this model, we formulate an optimization problem for the opportunistic scheduling scheme that maximizes the expected system throughput while satisfying the QoS constraint of each user. In the opportunistic scheduling scheme for the system without relay stations, each user has only one communication path between the base station and itself, and thus only user selection is considered. However, in our opportunistic scheduling scheme for the system with relay stations, since there may exist multiple paths between the base station and a user, not only user selection but also path selection for the scheduled user is considered. In addition, we also propose an opportunistic time-sharing method for time-slot sharing between base station and relay stations. With the opportunistic time-sharing method, our opportunistic scheduling provides opportunistic resource sharing in three places in the system: user selection in a time-slot, path selection for the selected user, and time-slot sharing between base station and relay stations. Simulation results show that as the number of places that opportunistic resource sharing is applied to increases, the performance improvement also increases.

Cooperative relaying (CR) is a promising technique to provide spatial diversity by combining multiple signals from source and relay stations. In the present paper, the impact and use of the asymmetric property in bi-directional CR under asymmetric traffic conditions are discussed assuming that CR involves one communication pair and one relay station in a time division duplex (TDD) system. The asymmetric property means that the average communication quality differs for each transmission direction because of the difference in signal power between the combined signals for each direction. First, numerical results show the asymmetric property of bi-directional CR. Next, in order to evaluate the impact of the asymmetric property, the optimal relay position and resource allocation are compared to those in simple multi-hop relaying, which does not have the asymmetric property. Numerical results show that, in order to maximize the overall quality of bi-directional communication, the optimal relay position in CR depends on the offered traffic ratio, which is defined as the traffic ratio of each transmission direction, while the offered traffic ratio does not affect the optimal relay position in multi-hop relaying. Finally, the asymmetric property is used to enhance the overall quality. Specifically, a high overall quality can be achieved by, for example, opportunistically switching to the transmission direction with higher quality. Under asymmetric traffic conditions, weighted proportionally fair scheduling (WPFS), which is proposed in the context of downlink scheduling in a cellular network, is applied to transmission direction switching. Numerical results reveal that WPFS provides a high overall quality and that the quality ratio is similar to the offered traffic ratio.

We propose a randomness test based on the T-complexity of a sequence, which can be calculated using a parsing algorithm called T-decomposition. Recently, the Lempel-Ziv (LZ) randomness test based on LZ-complexity using the LZ78 incremental parsing was officially excluded from the NIST test suite in NIST SP 800-22. This is caused from the problem that the distribution of P-values for random sequences of length 106 is strictly discrete for the LZ-complexity. Our proposed test can overcome this problem because T-complexity has almost ideal continuous distribution of P-values for random sequences of length 106. We also devise a new sequential T-decomposition algorithm using forward parsing, while the original T-decomposition is an off-line algorithm using backward parsing. Our proposed test can become a supplement to NIST SP 800-22 because it can detect several undesirable pseudo-random numbers that the NIST test suite almost fails to detect.

This paper investigates the closure properties of 1-inkdot nondeterministic Turing machines and 1-inkdot alternating Turing machines with only universal states which have sublogarithmic space. We show for example that the classes of sets accepted by these Turing machines are not closed under length-preserving homomorphism, concatenation with regular set, Kleene closure, and complementation.

This letter suggests an opportunistic resource scheduling scheme for supporting users with variety of services in wireless network. This scheme is designed to increase resource utilization while meeting diverse quality of service (QoS) requirements. It can be achieved by considering the channel status and the urgency for QoS support synthetically.

In this letter, the performance improvement by the deployment of multiple antennas in cognitive radio systems is studied from a system-level view. The term opportunistic spectrum efficiency (OSE) is defined as the performance metric to evaluate the spectrum opportunities that can actually be exploited by the secondary user (SU). By applying a simple energy combining detector, we show that deploying multiple antennas at the SU transceiver can improve the maximum achievable OSE significantly. Numerical results also reveal that the improvement comes from the reduction of both the detection overhead and the false alarm probability.

A simple distributed Medium Access Control (MAC) protocol for cognitive wireless networks is proposed. It is assumed that the network is slotted, the spectrum is divided into a number of channels, and the primary network statistical aggregate traffic model on each channel is given by independent Bernoulli random variables. The objective of the cognitive MAC is to maximize the exploitation of the channels idle time slots. The cognitive users can achieve this aim by appropriate hopping between the channels at each decision stage. The proposed protocol is based on the rule of least failures that is deployed by each user independently. Using this rule, at each decision stage, a channel with the least number of recorded collisions with the primary and other cognitive users is selected for exploitation. The performance of the proposed protocol for multiple cognitive users is investigated analytically and verified by simulation. It is shown that as the number of users increases the user decision under this protocol comes close to the optimum decision to maximize its own utilization. In addition, to improve opportunity utilization in the case of a large number of cognitive users, an extension to the proposed MAC protocol is presented and evaluated by simulation.

Applications usually have their own phases in heap memory usage. The traditional garbage collector fails to match various application phases because the same heuristic on the object behavior is used throughout the entire execution. This paper introduces a phase-adaptive garbage collector which reorganizes the heap layout and adjusts the invocation time of the garbage collection according to the phases. The proposed collector identifies phases by detecting the application methods strongly related to the phase boundaries. The experimental results show that the proposed phase-adaptive collector successfully recognizes application phases and improves the garbage collection time by as much as 41%.

In this paper, we study an opportunistic scheduling and adaptive modulation scheme for a wireless network with an XOR network coding scheme, which results in a cross-layer problem for MAC and physical layers. A similar problem was studied in [2] which considered an idealized system with the Shannon capacity. They showed that it may not be optimal for a relay node to encode all possible native packets and there exists the optimal subset of native packets that depends on the channel condition at the receiver node of each native packet. In this paper, we consider a more realistic model than that of [2] with a practical modulation scheme such as M-PSK. We show that the optimal policy is to encode native as many native packets as possible in the network coding group into a coded packet regardless of the channel condition at the receiver node for each native packet, which is a different conclusion from that of [2]. However, we show that adaptive modulation, in which the constellation size of a coded packet is adjusted based on the channel condition of each receiver node, provides a higher throughput than fixed modulation, in which its constellation size is always fixed regardless of the channel condition at each receiver node.

This article explains how to apply the deterministic annealing (DA) and simulated annealing (SA) methods to fuzzy entropy based fuzzy c-means clustering. By regularizing the fuzzy c-means method with fuzzy entropy, a membership function similar to the Fermi-Dirac distribution function, well known in statistical mechanics, is obtained, and, while optimizing its parameters by SA, the minimum of the Helmholtz free energy for fuzzy c-means clustering is searched by DA. Numerical experiments are performed and the obtained results indicate that this combinatorial algorithm of SA and DA can represent various cluster shapes and divide data more properly and stably than the standard single DA algorithm.