This paper addresses the problem of multiple multicast in WDM networks. It presents three efficient algorithms to construct an optimal/sub-optimal multicast tree for each multicast and minimise the network congestion on wavelengths. The first two algorithm achieve an optimal network congestion for a specific class of networks whose all wavelengths are globally accessible and convertible at a unit cost. The third algorithm produces an approximation solution for the general case of WDM networks.

To meet the highly competitive and dynamic needs in the market, an e-Business company needs to flexibly integrate its heterogeneous database systems together, e.g., the integration of makers and retailers in a Supply Chain Management System (SCM). The customers demand one-click response and also their access requirements change too frequently. Moreover, different retailers and makers in a SCM, being the autonomous entities, have their own specific requirements for stock-cost and opportunity-loss, depending on their local situation that is also changing with time. Under this background, the integrated DBs of the SCM are required to provide real-time response, heterogeneity satisfaction and flexibility to adapt to changing requirements. The conventional approach of strict consistency leads to low response and less flexibility due to the strong interdependence of the systems. In this paper, Autonomous Decentralized Database System has been proposed as an application-oriented database technology based on the concept of autonomy and loose-consistency among the distributed DB systems thus providing real-time, flexibility and high availability. The autonomy in the system has been achieved by defining a data attribute, Allowable Volume, within which each component DB has autonomy to update the data in real-time. Moreover, the system adapts to the dynamically changing heterogeneous access requirements at each DB by managing the distribution of AV among different DBs through an active coordination mechanism. Due to the dynamic and unpredictable environment, the component DBs are provided with complete autonomy for their local and coordination decisions, thus diminishing the interdependency and improving the response time. As the system consists of loosely-connected subsystems, it also has high availability. Therefore, the proposed system provides highly decentralized architecture with flexibility and high availability. The performance of the system has been shown significantly effective by simulating the internet based SCM system, from the communication-cost and response time point of view.

In this paper, we propose a high-speed full-duplex optical wireless communication system using a single channel imaging receiver for personal area network applications. This receiver is composed of an imaging lens, a small sensitive-area photodiode, and a 2-aixs actuator and it can reject most of the background light. Compared with the previously proposed system with single wide field-of-view (FOV) non-imaging receiver, the coverage area at 12.5 Gb/s is extended by > 20%. Furthermore, since the rough location information of the user is available in our proposed system, instead of searching for the focused light spot over a large area on the focal plane of the lens, only a small possible area needs to be scanned. In addition, by pre-setting a proper comparison threshold when searching for the focused light spot, the time needed for searching can be further reduced. Proof-of-concept experiments have been carried out and the results show that with this partial searching algorithm and pre-set threshold, better performance is achieved.

Recently with the advent of the IT and the wide spread use of the Internet, new user oriented production and logistic systems, such as the Supply Chain Management System, have been required in order to cope with the drastic and continuous changes on the markets and users' preferences. Therefore, heterogeneous database systems need to be integrated in a common environment which can cope with the heterogeneous requirements of each company under an ever-evolving changing environment. That is assurance. Autonomous Decentralized Database System (ADDS) is proposed as a system architecture in order to realize assurance in distributed database systems. In this system architecture, a loosely-consistency management technology is proposed in order to maintain the consistency of the system, each database can update autonomously, and confer the real time property. A background coordination technology, performed by an autonomous mobile agent, is devised to adapt the system to evolving situations. The system can achieve real time by allocating the information in advance among the sites that has different time constraints for updating. Moreover, an assurance information allocation technology is proposed when considering that a failure in the background coordination mechanism may lead to loss of data and unavailability of the system. This mechanism, in which the mobile agent autonomously regulate its own capacity for allocating the information, is proposed based on the real-time property and system's availability considerations. The effectiveness of the proposed architecture and technologies are evaluated by simulation.

This letter studies the physical layer security of an unmanned aerial vehicle (UAV)-enabled multicasting system, where a UAV serves as a mobile transmitter to send a common confidential message to a group of legitimate users under the existence of multiple eavesdroppers. The worst situation in which each eavesdropper can wiretap all legitimate users is considered. We seek to maximize the average secrecy rate by jointly optimizing the UAV's transmit power and trajectory over a given flight period. The resulting optimization problem is nonconvex and intractable to solve. To circumvent the nonconvexity, we propose an iterative algorithm to approximate the solution based on the alternating optimization and successive convex approximation methods. Simulation results validate the convergence and effectiveness of our proposed algorithm.

We investigate the utilization of vector registers (VRs) on reducing memory references for single instruction multiple data fast Fourier transform calculation. We propose to group the butterfly computations in several consecutive stages to maximize utilization of the available VRs and take the advantage of the symmetries in twiddle factors. All the butterflies sharing identical twiddle factors are clustered and computed together to further improve performance. The relationship between the number of fused stages and the number of available VRs is then examined. Experimental results on different platforms show that the proposed method is effective.

In this paper, the artificial noise (AN)-aided multiple-input single-output (MISO) cognitive radio network with simultaneous wireless information and power transfer (SWIPT) is considered, in which the cognitive user adopts the power-splitting (PS) receiver architecture to simultaneously decode information and harvest energy. To support secure communication and facilitate energy harvesting, AN is transmitted with information signal at cognitive base station (CBS). The secrecy energy efficiency (SEE) maximization problem is formulated with the constraints of secrecy rate and harvested energy requirements as well as primary user's interference requirements. However, this challenging problem is non-convex due to the fractional objective function and the coupling between the optimization variables. For tackling the challenging problem, a double-layer iterative optimization algorithm is developed. Specifically, the outer layer invokes a one-dimension search algorithm for the newly introduced tight relaxation variable, while the inner one leverages the Dinkelbach method to make the fractional optimization problem more tractable. Furthermore, closed-form expressions for the power of information signal and AN are obtained. Numerical simulations are conducted to demonstrate the efficiency of our proposed algorithm and the advantages of AN in enhancing the SEE performance.

Cognitive radio network (CRN) provides an effective way of improving efficiency and flexibility in spectrum usage. Due to the coexistence of secondary user (SU) and primary user (PU), managing interference is a critical issue to be addressed if we are to reap the full benefits. In this paper, we consider the problem of joint interference management and resource allocation in a multi-channel ad hoc CRN. We formulate the problem as an overlapping coalition formation game to maximize the sum rate of SU links while guaranteeing the quality of service (QoS) of PU links. In the game, each SU link can make an autonomous decision and is allowed to participate in one or more cooperative coalitions simultaneously to maximize its payoff. To obtain the solution of the formulated game, a distributed, self-organizing algorithm is proposed for performing coalition formation. We analyze the properties of the algorithm and show that SU links can cooperate to reach a final stable coalition structure. Compared with existing approaches, the proposed scheme achieves appreciable performance improvement in terms of the sum rate of SU links, which is demonstrated by simulation results.

Syndrome is a crucial principle of Traditional Chinese Medicine. Formula classification is an effective approach to discover herb combinations for the clinical treatment of syndromes. In this study, a local search based firefly algorithm (LSFA) for parameter optimization and feature selection of support vector machines (SVMs) for formula classification is proposed. Parameters C and γ of SVMs are optimized by LSFA. Meanwhile, the effectiveness of herbs in formula classification is adopted as a feature. LSFA searches for well-performing subsets of features to maximize classification accuracy. In LSFA, a local search of fireflies is developed to improve FA. Simulations demonstrate that the proposed LSFA-SVM algorithm outperforms other classification algorithms on different datasets. Parameters C and γ and the features are optimized by LSFA to obtain better classification performance. The performance of FA is enhanced by the proposed local search mechanism.

Introducing inter-satellite ranging and communication links in a Global Navigation Satellite System (GNSS) can improve its performance. In view of the highly dynamic characteristics and the rapid but reliable acquisition requirement of inter-satellite link (ISL) signal of navigation constellation, we utilize navigation data, which is the special resource of navigation satellites, to assist signal acquisition. In this paper, we introduce a method that uses the navigation data for signal acquisition from three aspects: search space, search algorithm, and detector structure. First, an iteration method to calculate the search space is presented. Then the most efficient algorithm is selected by comparing the computation complexity of different search algorithms. Finally, with the navigation data, we also propose a method to guarantee the detecting probability constant by adjusting the non-coherent times. An analysis shows that with the assistance of navigation data, we can reduce the computing cost of ISL signal acquisition significantly, as well effectively enhancing acquisition speed and stabling the detection probability.

Motif searching, i.e., identifying meaningful patterns from biological data, has been studied extensively due to its importance in the biomedical sciences. In this work, we seek to improve the performance of Weeder, a widely-used tool for automatic de novo motif searching. Weeder consists of several functions, among which we find that the function oligo_scan, which handles the pattern matching, is the bottleneck, especially when dealing with large datasets. Motivated by this observation, we adopt the Micron Automata Processor (AP) to accelerate the pattern-matching stage of Weeder. The AP is a massively-parallel, non-von-Neumann semiconductor architecture that is purpose-built for symbolic pattern matching. Relying on the fact that AP is capable of performing matching for thousands of patterns in parallel, we develop an AP-accelerated Weeder implementation in this work. In particular, we describe how to map Weeder's pattern matching to the AP chip and use the high-end FPGA on the AP board to postprocess the output from AP. Our experiment shows that the AP-accelerated Weeder achieves 751x speedup on pattern matching, compared to a single-threaded CPU implementation.

A new fuzzy level set method (FLSM) based on the global search capability of quantum particle swarm optimization (QPSO) is proposed to improve the stability and precision of image segmentation, and reduce the sensitivity of initialization. The new combination of QPSO-FLSM algorithm iteratively optimizes initial contours using the QPSO method and fuzzy c-means clustering, and then utilizes level set method (LSM) to segment images. The new algorithm exploits the global search capability of QPSO to obtain a stable cluster center and a pre-segmentation contour closer to the region of interest during the iteration. In the implementation of the new method in segmenting liver tumors, brain tissues, and lightning images, the fitness function of the objective function of QPSO-FLSM algorithm is optimized by 10% in comparison to the original FLSM algorithm. The achieved initial contours from the QPSO-FLSM algorithm are also more stable than that from the FLSM. The QPSO-FLSM resulted in improved final image segmentation.

Crosstalk between lines plays an important role in the transmission of signal. Hence it is of great significance to establish the transmission lines model accurately to evaluate factors affecting crosstalk coupling between lines and to improve the anti-interference capability of the system. As twisted-pair line is widely used for its unique twist structure which improves the anti-interference performance of cables, this paper presents a method of constructing transmission lines model of the shielded twisted-pair line (STP) with two twisted pairs based on S-parameters. Firstly, the transmission lines model of STP with one twisted pair is established. The establishment of distributed capacitance matrix of this model depends on the dielectric constant of insulation layer that surrounds a conductor, but the dielectric constant is often unknown. In this respect, a method to obtain the distributed capacitance matrix based on the S-parameters of this model is proposed. Due to twisting, there is a great deal of variability between the distribution parameters along the length of the STP. As the spatial distribution of conductors in the cross-section of twisted-pair line vary along with the cable length, the distribution parameters matrices also change as they move. The cable is divided into several segments, and the transmission lines model of STP is obtained with the cascade of each segment model. For the STP with two twisted pairs, the crosstalk between pairs is analyzed based on the mixed mode S-parameters. Combined with the transmission lines model of STP with one twisted pair, that of STP with two twisted pairs is obtained. The terminal response voltage can be calculated from the transmission lines model and cable terminal conditions. The validity of the transmission lines model is verified by the consistency between the terminal responses calculated by the model and by the simulated. As the theoretical and simulation results are compatible, the modeling method for the STP with two twisted pairs can be used for the STP with more twisted pairs. In practical engineering application, S-parameters and mixed mode S-parameters can be obtained by testing. That means the transmission lines model of STP can be established based on the test results.

Network Functional Virtualization (NFV) is a high-performance network interconnection technology that allows access to traditional network transport devices through virtual network links. It is widely used in cloud computing and other high-concurrent access environments. However, there is a long delay in the introduction of software NFV solutions. Other hardware I/O virtualization solutions don't scale very well. Therefore, this paper proposes a virtualization implementation method on 100Gbps high-speed Field Programmable Gate Array (FPGA) network accelerator card, which uses FPGA accelerator to improve the performance of virtual network devices. This method uses the single root I/O virtualization (SR-IOV) technology to allow 256 virtual links to be created for a single Peripheral Component Interconnect express (PCIe) device. And it supports data transfer with virtual machine (VM) in the way of Peripheral Component Interconnect (PCI) passthrough. In addition, the design also adopts the shared extensible queue management mechanism, which supports the flexible allocation of more than 10,000 queues on virtual machines, and ensures the good isolation performance in the data path and control path. The design provides high-bandwidth transmission performance of more than 90Gbps for the entire network system, meeting the performance requirements of hyperscale cloud computing clusters.