Abstract: This paper presents a survey of vehicle routing problems with multiple synchronization constraints. These problems exhibit, in addition to the usual task covering constraints, further synchronization requirements between the vehicles, concerning spatial, temporal, and load aspects. They constitute an emerging field in vehicle routing research and are becoming a “hot” topic. The contribution of the paper is threefold: (i) It presents a classification of different types of synchronization. (ii) It discusses the central issues related to the exact and heuristic solution of such problems. (iii) It comprehensively reviews pertinent literature with respect to applications as well as successful solution approaches, and it identifies promising algorithmic avenues.

Abstract: Synchronization, the emergence of spontaneous order in coupled systems, is of fundamental importance in both physical and biological systems. We demonstrate the synchronization of two dissimilar silicon nitride micromechanical oscillators, that are spaced apart by a few hundred nanometers and are coupled through an optical cavity radiation field. The tunability of the optical coupling between the oscillators enables one to externally control the dynamics and switch between coupled and individual oscillation states. These results pave a path toward reconfigurable synchronized oscillator networks.

Abstract: This technical note studies distributed adaptive control of synchronization in complex networks An effective distributed adaptive strategy to tune the coupling weights of a network is designed based on local information of node dynamics The analysis is then extended to the case where only a small fraction of coupling weights can be adjusted A general criterion is derived and it is found that synchronization can be reached if the subgraph consisting of the edges and nodes corresponding to the updated coupling weights is connected Finally, simulation examples are given to illustrate the theoretical analysis

Abstract: Introduction to Data Communications. Theoretical Foundations of Digital Communications. Error Correcting and Detecting Codes. Baseband Pulse Transmission. Passband Data Transmission. Synchronization. Optimum Data Transmission. Automatic and Adaptive Equalization. Echo Cancellation. Topics in Digital Communications. Index.

Abstract: Author's version of an article published in the journal: Journal of the Franklin Institute Also available from the publisher at: http://dxdoiorg/101016/jjfranklin201109015

Abstract: In this paper, we characterize and analyze an increasingly popular style of programming for the GPU called Persistent Threads (PT). We present a concise formal definition for this programming style, and discuss the difference between the traditional GPU programming style (nonPT) and PT, why PT is attractive for some high-performance usage scenarios, and when using PT may or may not be appropriate. We identify limitations of the nonPT style and identify four primary use cases it could be useful in addressing—CPU-GPU synchronization, load balancing/irregular parallelism, producer-consumer locality, and global synchronization. Through micro-kernel benchmarks we show the PT approach can achieve up to an order-of-magnitude speedup over nonPT kernels, but can also result in performance loss in many cases. We conclude by discussing the hardware and software fundamentals that will influence the development of Persistent Threads as a programming style in future systems.

Abstract: Synchronization of neural activity is considered essential for information processing in the nervous system. Both local and inter-regional synchronization are omnipresent in different frequency regimes and relate to a variety of behavioral and cognitive functions. Over the years, many studies have sought to elucidate the question how alpha/mu, beta, and gamma synchronization contribute to motor control. Here, we review these studies with the purpose to delineate what they have added to our understanding of the neural control of movement. We highlight important findings regarding oscillations in primary motor cortex, synchronization between cortex and spinal cord, synchronization between cortical regions, as well as abnormal synchronization patterns in a selection of motor dysfunctions. The interpretation of synchronization patterns benefits from combining results of invasive and non-invasive recordings, different data analysis tools, and modeling work. Importantly, although synchronization is deemed to play a vital role, it is not the only mechanism for neural communication. Spike timing and rate coding act together during motor control and should therefore both be accounted for when interpreting movement-related activity.

Abstract: We investigate the stability of synchronized states in delay-coupled networks where synchronization takes place in groups of different local dynamics or in cluster states in networks with identical local dynamics. Using a master stability approach, we find that the master stability function shows a discrete rotational symmetry depending on the number of groups. The coupling matrices that permit solutions on group or cluster synchronization manifolds show a very similar symmetry in their eigenvalue spectrum, which helps to simplify the evaluation of the master stability function. Our theory allows for the characterization of stability of different patterns of synchronized dynamics in networks with multiple delay times, multiple coupling functions, but also with multiple kinds of local dynamics in the networks' nodes. We illustrate our results by calculating stability in the example of delay-coupled semiconductor lasers and in a model for neuronal spiking dynamics.

Abstract: Critical phenomena in complex networks, and the emergence of dynamical abrupt transitions in the macroscopic state of the system are currently a subject of the outmost interest We report evidence of an explosive phase synchronization in networks of chaotic units Namely, by means of both extensive simulations of networks made up of chaotic units, and validation with an experiment of electronic circuits in a star configuration, we demonstrate the existence of a first-order transition towards synchronization of the phases of the networked units Our findings constitute the first prove of this kind of synchronization in practice, thus opening the path to its use in real-world applications

Abstract: Several different embodiments of a massively scalable object storage system are described. The object storage system is particularly useful for storage in a cloud computing installation whereby shared servers provide resources, software, and data to computers and other devices on demand. In several embodiments, the object storage system includes a ring implementation used to associate object storage commands with particular physical servers such that certain guarantees of consistency, availability, and performance can be met. In other embodiments, the object storage system includes a synchronization protocol used to order operations across a distributed system. In a third set of embodiments, the object storage system includes a metadata management system. In a fourth set of embodiments, the object storage system uses a structured information synchronization system. Features from each set of embodiments can be used to improve the performance and scalability of a cloud computing object storage system.

Abstract: Systems and methods for folder synchronization and offline synchronization via a mobile platform in a web-based collaboration environment are disclosed. One embodiment includes synchronizing user selected folders and/or sub-folders via the mobile platform, using portable devices including smart phones and tablets using any mobile operating system to allow offline access. Child or sub-folders of the selected folders and/or sub-folders are automatically detected and synchronized for offline access. Any change or new content detected on the client side or on the server side is also synchronized such that the selected folders and/or sub-folders on the client and server sides are up to date.

Abstract: In this technical note, we study output synchronization of networked multiagent systems. The agents, modeled as nonlinear systems with relative degree one, exchange information over a network described by an interagent communication graph. Inspired by the results of Igarashi , we extend our earlier results on output synchronization to include the case of strongly connected graphs. We first demonstrate output synchronization for input-output passive systems communicating over strongly connected graphs and include the practical case of constant time delays in communication. It is well known (Byrnes ) that weakly minimum phase systems with relative degree one are feedback equivalent to a passive system with a positive definite storage function. We exploit this feedback equivalence to develop control laws for output synchronization of such systems, exchanging outputs on strongly connected graphs, and in the presence of communication delays. A numerical example is also presented to illustrate the proposed results.

Abstract: Fine-grain thread synchronization has been proved, in several cases, to be outperformed by efficient implementations of the combining technique where a single thread, called the combiner, holding a coarse-grain lock, serves, in addition to its own synchronization request, active requests announced by other threads while they are waiting by performing some form of spinning. Efficient implementations of this technique significantly reduce the cost of synchronization, so in many cases they exhibit much better performance than the most efficient finely synchronized algorithms.In this paper, we revisit the combining technique with the goal to discover where its real performance power resides and whether or how ensuring some desired properties (e.g., fairness in serving requests) would impact performance. We do so by presenting two new implementations of this technique; the first (CC-Synch) addresses systems that support coherent caches, whereas the second (DSM-Synch) works better in cacheless NUMA machines. In comparison to previous such implementations, the new implementations (1) provide bounds on the number of remote memory references (RMRs) that they perform, (2) support a stronger notion of fairness, and (3) use simpler and less basic primitives than previous approaches. In all our experiments, the new implementations outperform by far all previous state-of-the-art combining-based and fine-grain synchronization algorithms. Our experimental analysis sheds light to the questions we aimed to answer.Several modern multi-core systems organize the cores into clusters and provide fast communication within the same cluster and much slower communication across clusters. We present an hierarchical version of CC-Synch, called H-Synch which exploits the hierarchical communication nature of such systems to achieve better performance. Experiments show that H-Synch significantly outper forms previous state-of-the-art hierarchical approaches.We provide new implementations of common shared data structures (like stacks and queues) based on CC-Synch, DSM-Synch and H-Synch. Our experiments show that these implementations outperform by far all previous (fine-grain or combined-based) implementations of shared stacks and queues.

Abstract: SUMMARY In this paper, we propose a general framework for distributed model predictive control of discrete-time nonlinear systems with decoupled dynamics but subject to coupled constraints and a common cooperative task. To ensure recursive feasibility and convergence to the desired cooperative goal, the systems optimize a local cost function in a sequential order, whereas only neighbor-to-neighbor communication is allowed. In contrast to most of the existing distributed model predictive control schemes in the literature, we do not necessarily consider the stabilization of an a priori known set point. Instead, also other cooperative control tasks such as consensus and synchronization problems can be handled within the proposed framework. In particular, one of our main contributions is to show how for the latter case the terminal cost functions and the terminal region can be suitably defined and computed. Furthermore, we illustrate our results with simulation examples. Copyright © 2012 John Wiley & Sons, Ltd.

Abstract: Much of the complexity and overhead (directory, state bits, invalidations) of a typical directory coherence implementation stems from the effort to make it “invisible” even to the strongest memory consistency model. In this paper, we show that a much simpler, directory-less/broadcast-less, multicore coherence can outperform a directory protocol but without its complexity and overhead. Motivated by recent efforts to simplify coherence, we propose a hardware approach that does not require any application guidance. The cornerstone of our approach is a dynamic, application-transparent, write-policy (write-back for private data, write-through for shared data), simplifying the protocol to just two stable states. Self-invalidation of the shared data at synchronization points allows us to remove the directory (and invalidations) completely, with just a data-race-free guarantee from software. This leads to our main result: a virtually costless coherence that outperforms a MESI directory protocol (by 4.8%) while at the same time reducing shared cache and network energy consumption (by 14.2%) for 15 parallel benchmarks, on 16 cores.

Abstract: We consider the synchronization of coupled dynamical systems when different types of interactions are simultaneously present. We assume that a set of dynamical systems is coupled through the connections of two or more distinct networks (each of which corresponds to a distinct type of interaction), and we refer to such a system as a dynamical hypernetwork. Applications include neural networks made up of both electrical gap junctions and chemical synapses, the coordinated motion of shoals of fish communicating through both vision and flow sensing, and hypernetworks of coupled chaotic oscillators. We first analyze the case of a hypernetwork made up of m = 2 networks. We look for the necessary and sufficient conditions for synchronization. We attempt to reduce the linear stability problem to a master stability function (MSF) form, i.e. decoupling the effects of the coupling functions from the structure of the networks. Unfortunately, we are unable to obtain a reduction in an MSF form for the general case. However, we show that such a reduction is possible in three cases of interest: (i) the Laplacian matrices associated with the two networks commute; (ii) one of the two networks is unweighted and fully connected; and (iii) one of the two networks is such that the coupling strength from node i to node j is a function of j but not of i. Furthermore, we define a class of networks such that if either one of the two coupling networks belongs to this class, the reduction can be obtained independently of the other network. As an example of interest, we study synchronization of a neural hypernetwork for which the connections can be either chemical synapses or electrical gap junctions. We propose a generalization of our stability results to the case of hypernetworks formed of m ≥ 2 networks.

Abstract: Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. Asynchronous SN P systems are non-synchronized systems, where the use of spiking rules (even if they are enabled by the contents of neurons) is not obligatory. It remains open whether asynchronous SN P systems with standard spiking rules are equivalent with Turing machines. In this paper, with a biological inspiration (in order to achieve some specific biological functioning, neurons from the same functioning motif or community work synchronously to cooperate with each other), we introduce the notion of local synchronization into asynchronous SN P systems. The computation power of asynchronous SN P systems with local synchronization is investigated. Such systems consisting of general neurons (respectively, unbounded neurons) and using standard spiking rules are proved to be universal. Asynchronous SN P systems with local synchronization consisting of bounded neurons and using standard spiking rules characterize the semilinear sets of natural numbers. These results show that the local synchronization is useful, it provides some ''programming capacity'' useful for achieving a desired computation power.

Abstract: The invention relates to a method comprising classifying user equipment (UE) cells, to which carrier aggregation is applied, into a plurality of time advance groups. Uplink-time synchronization is managed using the time synchronization of a primary cell (Pcell) in the time synchronization group to which the primary cell belongs. For other time synchronization groups, the uplink time synchronization is managed using the time synchronization of a secondary cell (SCell) that is particularly set in the relevant time synchronization group. Thus, the plurality of time synchronizations can be effectively managed for the UE and a base station (BS).

Abstract: Several different embodiments of a massively scalable object storage system are described. The object storage system is particularly useful for storage in a cloud computing installation whereby shared servers provide resources, software, and data to computers and other devices on demand. In several embodiments, the object storage system includes a ring implementation used to associate object storage commands with particular physical servers such that certain guarantees of consistency, availability, and performance can be met. In other embodiments, the object storage system includes a synchronization protocol used to order operations across a distributed system. In a third set of embodiments, the object storage system includes a metadata management system. In a fourth set of embodiments, the object storage system uses a structured information synchronization system. Features from each set of embodiments can be used to improve the performance and scalability of a cloud computing object storage system.

Abstract: The latest techniques for designing robust, high performance integrated circuits in nanoscale technologies Focusing on a new technological paradigm, this practical guide describes the interconnect-centric design methodologies that are now the major focus of nanoscale integrated circuits (ICs). High Performance IntegratedCircuit Design begins by discussing the dominant role of on-chip interconnects and provides an overview of technology scaling. The book goes on to cover data signaling, power management, synchronization, andsubstrate-aware design. Specific design constraints and methodologies unique to each type of interconnect are addressed. This comprehensive volume also explains the design of specialized circuits such as tapered buffers and repeaters for data signaling, voltage regulators for power management, and phase-locked loops for synchronization. This is an invaluable resource for students, researchers, and engineers working in the area of high performance ICs. Coverage includes: Technology scaling Interconnect modeling and extraction Signal propagation and delay analysis Interconnect coupling noise Global signaling Power generation Power distribution networks CAD of power networks Techniques to reduce power supply noise Power dissipation Synchronization theory and tradeoffs Synchronous system characteristics On-chip clock generation and distribution Substrate noise in mixed-signal ICs Techniques to reduce substrate noise

Abstract: This brief presents a new method for master-slave synchronization of chaotic Lur'e systems with sampled-data control. The new method is based on a novel construction of piecewise differentiable Lyapunov functionals in the framework of the input delay approach. The new Lyapunov functional is continuous at sampling times but not necessarily positive definite inside the sampling intervals. Compared with the existing works, the proposed method makes full use of the information on the piecewise constant input and the actual sampling pattern. Two illustrative examples are given which substantiate the usefulness of the proposed method.

Abstract: In this brief, the analysis problem of the mode and delay-dependent adaptive exponential synchronization in th moment is considered for stochastic delayed neural networks with Markovian switching. By utilizing a new nonnegative function and the -matrix approach, several sufficient conditions to ensure the mode and delay-dependent adaptive exponential synchronization in th moment for stochastic delayed neural networks are derived. Via the adaptive feedback control techniques, some suitable parameters update laws are found. To illustrate the effectiveness of the -matrix-based synchronization conditions derived in this brief, a numerical example is provided finally.

Abstract: Synchronization in large laser networks with both homogeneous and heterogeneous coupling delay times is examined The number of synchronized clusters of lasers is established to equal the greatest common divisor of network loops We experimentally demonstrate up to 16 multicluster phase synchronization scenarios within unidirectional coupled laser networks, whereby synchronization in heterogeneous networks is deduced by mapping to an equivalent homogeneous network The synchronization in large laser networks is controlled by means of tunable coupling and self-coupling