Recently in an SDN/NFV-enabled network, a consolidated middlebox is proposed in which middlebox functions required by a network flow are provided at a single machine in a virtualized manner. With the promising advantages such as simplifying network traffic routing and saving resources of switches and machines, consolidated middleboxes are going to replace traditional middleboxes in the near future. However, the location of consolidated middleboxes may affect the performance of an SDN/NFV network significantly. Accordingly, the consolidated middlebox positioning problem in an SDN/NFV-enabled network must be addressed adequately with service chain constraints (a flow must visit a specific type of consolidated middlebox), resource constraints (switch memory and processing power of the machine), and performance requirements (end-to-end delay and bandwidth consumption). In this paper, we propose a novel solution of the consolidated middlebox positioning problem in an SDN/NFV-enabled network based on flow clustering to improve the performance of service chain flows and utilization of a consolidated middlebox. Via extensive simulations, we show that our solution significantly reduces the number of routing rules per switch, the end-to-end delay and bandwidth consumption of service flows while meeting service chain and resource constraints.

A novel computational method based on a combination of the method of moments in the complex frequency domain and the fast inverse Laplace transform is proposed for solving time-domain electromagnetic problems. Using our proposed method, it is easy to estimate and control the computational error, and the observation time can be selected independently. We investigate canonical scattering problems and verify these advantages.

Recently, due to the development of design and manufacturing technologies for VLSI systems, an embedded system becomes more and more complex. Consequently, not only the performance of chips, but also the flexibility and dynamic adaptation of the implemented systems are required. To achieve these requirements, a partially reconfigurable device is promising. In this paper, we propose an efficient data structure to manage the reconfigurable units. And then, on the assumption that each task utilizes the rectangle shaped resources, a very simple MER enumeration algorithm based on this data structure is proposed. By utilizing the result of MER enumeration, the free space on the reconfigurable device can be used sufficiently. We analyze the complexity of the proposed algorithm and confirm its efficiency by experiments.

A fully synthesizable all-digital phase-locked loop (AD-PLL) with a stochastic time-to-digital converter (STDC) is proposed in this paper. The whole AD-PLL circuit design is based on only standard cells from digital library, thus the layout of this AD-PLL can be automatically synthesized by a commercial place-and-route (P&R) tool with a foundry-provided standard-cell library. No manual layout and process modification is required in the whole AD-PLL design. In order to solve the delay mismatch issue in the delay-line-based time-to-digital converter (TDC), an STDC employing only standard D flip-flop (DFF) is presented to mitigate the sensitivity to layout mismatch resulted from automatic P&R. For the stochastic TDC, the key idea is to utilize the layout uncertainty due to automatic P&R which follows Gaussian distribution according to statistics theory. Moreover, the fully synthesized STDC can achieve a finer resolution compared to the conventional TDC. Implemented in a 28nm fully depleted silicon on insulator (FDSOI) technology, the fully synthesized PLL consumes only 480µW under 1.0V power supply while operating at 0.9GHz. It achieves a figure of merit (FoM) of -231.1dB with 4.0ps RMS jitter while occupying 0.0055mm2 chip area only.

Workflow nets (WF-nets for short) are a mathematical model of real world workflows. A WF-net is often updated in accordance with the change of real world. This may cause places that are redundant from the viewpoint of the behavior. Such places are called implicit. We first proposed a necessary and sufficient condition to find implicit places. Then we proved that removing of implicit places is a reduction operation which forms branching bisimilarity. We also constructed an algorithm for the reduction. Next, we applied the proposed reduction operation to WF-net refactoring. Then we showed the usefulness of the proposed refactoring with two examples.

In this paper, we propose a novel Autonomous Decentralized Control (ADC) scheme for indirectly controlling a system performance variable of large-scale and wide-area networks. In a large-scale and wide-area network, since it is impractical for any one node to gather full information of the entire network, network control must be realized by inter-node collaboration using information local to each node. Several critical network problems (e.g., resource allocation) are often formulated by a system performance variable that is an amount to quantify system state. We solve such problems by designing an autonomous node action that indirectly controls, via the Markov Chain Monte Carlo method, the probability distribution of a system performance variable by using only local information. Analyses based on statistical mechanics confirm the effectiveness of the proposed node action. Moreover, the proposal is used to implement traffic-aware virtual machine placement control with load balancing in a data center network. Simulations confirm that it can control the system performance variable and is robust against system fluctuations. A comparison against a centralized control scheme verifies the superiority of the proposal.

The main purpose of this paper is to propose overtime replacement policies for the system which has a finite life cycle. The newly proposed overtime technique, where the system is replaced preventively at the first completion of some working cycle over a planned time T, is employed into modelings to avoid operational interruptions for successive jobs. We consider two overtime replacement model with finite operating interval which S is given as (i) constant interval, and (ii) random interval. The expected replacement costs per unit of time are obtained and their optimal solutions are discussed analytically. Further, numerical examples are given when the failure time has a Weibull distribution and working cycles are exponentially distributed.

The emerging three-dimensional (3D) technology is considered as a promising solution for achieving better performance and easier heterogeneous integration. However, the thermal issue becomes exacerbated primarily due to larger power density and longer heat dissipation paths. The thermal issue would also be critical once FPGAs step into the 3D arena. In this article, we first construct a fine-grained thermal resistive model for 3D FPGAs. We show that merely reducing the total power consumption and/or minimizing the power density in vertical direction is not enough for a thermal-aware 3D FPGA backend (placement and routing) flow. Then, we propose our thermal-aware backend flow named TherWare considering location-based heat balance. In the placement stage, TherWare not only considers power distribution of logic tiles in both lateral and vertical directions but also minimizes the interconnect power. In the routing stage, TherWare concentrates on overall power minimization and evenness of power distribution at the same time. Experimental results show that TherWare can significantly reduce the maximum temperature, the maximum temperature gradient, and the temperature deviation only at the cost of a minor increase in delay and runtime as compared with present arts.

Power-aware distributed file systems for efficient Big Data processing are increasingly moving towards power-proportional designs. However, current data placement methods for such systems have not given careful consideration to the effect of gear-shifting during operations. If the system wants to shift to a higher gear, it must reallocate the updated datasets that were modified in a lower gear when a subset of the nodes was inactive, but without disrupting the servicing of requests from clients. Inefficient gear-shifting that requires a large amount of data reallocation greatly degrades the system performance. To address this challenge, this paper proposes a data placement method known as Accordion, which uses data replication to arrange the data layout comprehensively and provide efficient gear-shifting. Compared with current methods, Accordion reduces the amount of data transferred, which significantly shortens the period required to reallocate the updated data during gear-shifting then able to improve the performance of the systems. The effect of this reduction is larger with higher gears, so Accordion is suitable for smooth gear-shifting in multigear systems. Moreover, the times when the active nodes serve the requests are well distributed, so Accordion is capable of higher scalability than existing methods based on the I/O throughput performance. Accordion does not require any strict constraint on the number of nodes in the system therefore our proposed method is expected to work well in practical environments. Extensive empirical experiments using actual machines with an Accordion prototype based on the Hadoop Distributed File System demonstrated that our proposed method significantly reduced the period required to transfer updated data, i.e., by 66% compared with an existing method.

Displacement mapping has been widely used for adding geometric surface details to 3D mesh models. However, it requires sufficient tessellation of the mesh if fine details are to be represented. In this paper, we propose a method for applying the displacement mapping even on coarse models by using an augmented patch mesh. The patch mesh is a regularly tessellated flat square mesh, which is mapped onto the target area. Our method applies displacement mapping to the patch mesh for fitting it to the original mesh as well as for adding surface details. We generate a patch map, which stores three-dimensional displacements from the patch mesh to the original mesh. A displacement map is also provided for defining the new surface feature. The target area in the original mesh is then replaced with the patch mesh, and the patch mesh reconstructs the original shape using the patch map and the new surface detail is added using the displacement map. Our results show that our method conveniently adds surface features to various models. The proposed method is particularly useful if the surface features change dynamically since the original mesh is preserved and the separate patch mesh overwrites the target area at runtime.

In this paper, a novel high-performance heuristic algorithm, named relay-race algorithm (RRA), which was proposed to approach a global optimal solution by exploring similar local optimal solutions more efficiently within shorter runtime for NP-hard problem is investigated. RRA includes three basic parts: rough search, focusing search and relay. The rough search is designed to get over small hills on the solution space and to approach a local optimal solution as fast as possible. The focusing search is designed to reach the local optimal solution as close as possible. The relay is to escape from the local optimal solution in only one step and to maintain search continuity simultaneously. As one of typical applications, multi-objective placement problem in physical design optimization is solved by the proposed RRA. In experiments, it is confirmed that the computational performance is considerably improved. RRA achieves overall Pareto improvement of two conflicting objectives: power consumption and maximal delay. RRA has its potential applications to improve the existing search methods for more hard problems.

Information-centric networking (ICN) is a promising architecture and has attracted much attention in the area of future Internet architectures. As one of the key technologies in ICN, in-network caching can enhance content retrieval at a global scale without requiring any special infrastructure. In this paper, we propose a workload-aware caching policy, LRU-GT, which allows cache nodes to protect newly cached contents for a period of time (guard time) during which contents are protected from being replaced. LRU-GT can utilize the temporal locality and distinguish contents of different popularity, which are both the characteristics of the workload. Cache replacement is modeled as a semi-Markov process under the Independent Reference Model (IRM) assumption and a theoretical analysis proves that popular contents have longer sojourn time in the cache compared with unpopular ones in LRU-GT and the value of guard time can affect the cache hit ratio. We also propose a dynamic guard time adjustment algorithm to optimize the performance. Simulation results show that LRU-GT can reduce the average hops to get contents and improve cache hit ratio.

NAND flash storage devices, such as eMMCs and microSD cards, are now widely used in mobile devices. In this paper, we propose a novel buffer replacement scheme for mobile NAND flash storages. It efficiently improves write performance by evicting pages flash-friendly and maintains high cache hit ratios by managing pages in order of recency. Our experimental results show that the proposed scheme outperforms the best performing scheme in the recent literature, Sp.Clock, by 48%.

Mobile IPv6 is an IETF (Internet Engineering Task Force) standard which permits node mobility in IPv6. To manage mobility, it establishes a centralized mediator, Home Agent (HA), which inevitably introduces several penalties like triangular routing, single point of failure and limited scalability. Some later extensions such as Global HAHA, which employed multiple HAs, made to alleviate above shortcomings by introducing Distributed Mobility Management (DMM) approach. However, Multiple HA model will not be beneficial, unless the HAs are located finely. But, no major research paper has focused on locating HAs. This paper examines impact of single and multiple HA placements in data plane, by using an Autonomous System (AS) level topology consisting of 30,000 nodes with several evaluation criteria. All possible placements of HA(s) are analysed on a fair, random set of 30,000 node pairs of Mobile Nodes (MN) and Correspondent Nodes (CN). Ultimate result provides a concise account of different HA placements: i.e. cost centrality interprets performance variation better than degree centrality or betweenness. 30,000 ASs are classified into three groups in terms of Freeman's closeness index and betweenness centrality: 1) high range group, 2) mid range group, and 3) low range group. Considering dual HA placement, if one HA is placed in an AS in the high range group, then any subsequent HA placement gives worse results, thus single HA placement is adequate. With the mid range group, similar results are demonstrated by the upper portion of the group, but the rest yields better results when combined with another HA. Finally, from the perspective of low range group, if the subsequent HA is placed in the high range group, it gives better result. On the other hand, betweenness based grouping yields varying results. Consequently, this study reveals that the Freeman's closeness index is most appropriate in determining impacts of HA placements among considered indices.

Travel recommendation and travel diary generation applications can benefit significantly from methods that infer the durations and locations of visits from travelers' GPS data. However, conventional inference methods, which cluster GPS points on the basis of their spatial distance, are not suited to inferring visit durations. This paper presents a pace-based clustering method to infer visit locations and durations. The method contributes two novel techniques: (1) It clusters GPS points logged during visits by considering the speed and applying a probabilistic density function for each trip. Consequently, it avoids clustering GPS points that are near but unrelated to visits. (2) It also includes additional GPS points in the clusters by considering their temporal sequence. As a result, it is able to complete the clusters with GPS points that are far from the visits but are logged during the visits, caused, for example, by GPS noise indoors. The results of an experimental evaluation comparing our proposed method with three published inference methods indicate that our proposed method infers the duration of a visit with an average error rate of 8.7%, notably outperforming the other methods.

To improve immunity against process gradients, a common centroid constraint, in which every pair of capacitors should be placed symmetrically with respect to a common center point, is widely used. The pair of capacitors are derived by dividing some original capacitors into two halves. Xiao et al. proposed a method to obtain a placement which satisfies the common centroid constraints, but this method has a defect. In this paper, we propose a decoding algorithm to obtain a placement which satisfies common centroid constraints.

In this paper, we propose a novel voice activity detection (VAD) algorithm based on the generalized normal-Laplace (GNL) distribution to provide enhanced performance in adverse noise environments. Specifically, the probability density function (PDF) of a noisy speech signal is represented by the GNL distribution; the variance of the speech and noise of the GNL distribution are estimated using higher-order moments. After in-depth analysis of estimated variances, a feature that is useful for discrimination between speech and noise at low SNRs is derived and compared to a threshold to detect speech activity. To consider the inter-frame correlation of speech activity, the result from the previous frame is employed in the decision rule of the proposed VAD algorithm. The performance of our proposed VAD algorithm is evaluated in terms of receiver operating characteristics (ROC) and detection accuracy. Results show that the proposed method yields better results than conventional VAD algorithms.

Sparse representation has been studied within the field of signal processing as a means of providing a compact form of signal representation. This paper introduces a sparse representation based framework named Sparse Probabilistic Linear Discriminant Analysis in speaker recognition. In this latent variable model, probabilistic linear discriminant analysis is modified to obtain an algorithm for learning overcomplete sparse representations by replacing the Gaussian prior on the factors with Laplace prior that encourages sparseness. For a given speaker signal, the dictionary obtained from this model has good representational power while supporting optimal discrimination of the classes. An expectation-maximization algorithm is derived to train the model with a variational approximation to a range of heavy-tailed distributions whose limit is the Laplace. The variational approximation is also used to compute the likelihood ratio score of all trials of speakers. This approach performed well on the core-extended conditions of the NIST 2010 Speaker Recognition Evaluation, and is competitive compared to the Gaussian Probabilistic Linear Discriminant Analysis, in terms of normalized Decision Cost Function and Equal Error Rate.

It is believed that the wavelength switched optical network (WSON) technology is moving towards being adopted by large-scale networks. Wavelength conversion and signal regeneration through reamplifying, reshaping, and retiming (3R) are beneficial to support the expansion of WSON. In many cases, these two functions can be technically integrated into a single shared physical component, namely the wavelength convertible 3R regenerator (WC3R). However, fully deploying such devices is infeasible due to their excessive cost. Thus, this topic serves as a motivation behind the investigation of the sparse placement issue of WC3Rs presented in this paper. A series of strategies are proposed based on knowledge of the network. Moreover, a novel adaptive routing and joint resource assignment algorithm is presented to provision the lightpaths in WSON with sparsely placed WC3Rs. Extensive simulation trials are conducted under even and uneven distribution of WC3R resource. Each strategic feature is examined for its efficiency in lowering the blocking probability. The results reveal that carefully designed sparse placement of WC3Rs can achieve performance comparable to that of full WC3R placement scenario. Furthermore, the expenditure of WC3R deployment also depends on the type of used WC3Rs characterized by the wavelength convertibility, i.e., fixed WC3R or tunable WC3R. This paper also investigates WSON from the perspective of cost and benefit by employing different types of WC3Rs in order to find the possibility of more efficient WC3R investment.

In the recent LSI design, it is difficult to obtain a placement which satisfies both design constraints and specifications due to the increase of the circuit size, the progress of the manufacturing technology, and the speed-up of the circuit performance. Analytical placement methods are promising to obtain the placement which satisfies both design constraints and specifications. Although existing analytical placement methods obtain the placement with the short wire length, the obtained placement has overlap. In this paper, we propose Overlap Removable Area as an overlap evaluation method for an analytical placement method. Experiments show that the proposed evaluation method is effective for removing overlap in the analytical placement method.