Besides the complexity in time or in number of messages, a common approach for analyzing distributed algorithms is to look at the assumptions they make on the underlying network. We investigate this question from the perspective of network dynamics. In particular, we ask how a given property on the evolution of the network can be rigorously proven as necessary or sufficient for a given algorithm. The main contribution of this paper is to propose the combination of two existing tools in this direction: local computations by means of graph relabelings, and evolving graphs. Such a combination makes it possible to express fine-grained properties on the network dynamics, then examine what impact those properties have on the execution at a precise, intertwined, level. We illustrate the use of this framework through the analysis of three simple algorithms, then discuss general implications of this work, which include (i) the possibility to compare distributed algorithms on the basis of their topological requirements, (ii) a formal hierarchy of dynamic networks based on these requirements, and (iii) the potential for mechanization induced by our framework, which we believe opens a door towards automated analysis and decision support in dynamic networks.
Let us repeat that an algorithm does not specify how the nodes synchronize, how they select each other to perform a common computation step. From the abstraction level of local computations, this underlying synchronization is seen as an implementation choice (dedicated procedures were designed to fit the various models, e.g. local elections @cite_14 and local rendezvous @cite_6 for starwise and pairwise interactions, respectively). A direct consequence is that the execution of an algorithm at this level may not be deterministic. Another consequence is that the characterization of conditions on the dynamics will additionally require assumptions on the synchronization -- we suggest later a generic progression hypothesis that serves this purpose. Note that the three algorithms provided in this paper rely on pairwise interactions, but the concepts and methodology involved apply to local computations in general.
@cite_14 @cite_6
2118991742 2088310932
Given a set of sensor nodes V where each node wants to broadcast a message to all its neighbors that are within a certain broadcasting range, the local broadcasting problem is to schedule all these requests in as few timeslots as possible. In this paper, assuming the more realistic physical interference model and no knowledge of the topology, we present three distributed local broadcasting algorithms where the first one is for the asynchronized model and the other two are for the synchronized model. Under the asynchronized model, nodes may join the execution of the protocol at any time and do not have access to a global clock, for which we give a distributed randomized algorithm with approximation ratio O(log2 n). This improves the state-of-the-art result given in [14] by a logarithmic factor. For the synchronized model where communications among nodes are synchronous and nodes can perform physical carrier sensing, we propose two distributed deterministic local broadcasting algorithms for synchronous and asynchronous node wakeups, respectively. Both algorithms have approximation ratio O(log n). Mobile agent computing is being used in fields as diverse as artificial intelligence, computational economics and robotics. Agents' ability to adapt dynamically and execute asynchronously and autonomously brings potential advantages in terms of fault-tolerance, flexibility and simplicity. This monograph focuses on studying mobile agents as modelled in distributed systems research and in particular within the framework of research performed in the distributed algorithms community. It studies the fundamental question of how to achieve rendezvous , the gathering of two or more agents at the same node of a network. Like leader election, such an operation is a useful subroutine in more general computations that may require the agents to synchronize, share information, divide up chores, etc. The work provides an introduction to the algorithmic issues raised by the rendezvous problem in the distributed computing setting. For the most part our investigation concentrates on the simplest case of two agents attempting to rendezvous on a ring network. Other situations including multiple agents, faulty nodes and other topologies are also examined. An extensive bibliography provides many pointers to related work not covered in the text. The presentation has a distinctly algorithmic, rigorous, distributed computing flavor and most results should be easily accessible to advanced undergraduate and graduate students in computer science and mathematics departments. Table of Contents: Models for Mobile Agent Computing Deterministic Rendezvous in a Ring Multiple Agent Rendezvous in a Ring Randomized Rendezvous in a Ring Other Models Other Topologies We present a methodology for modeling heterogeneous real-time components. Components are obtained as the superposition of three layers : Behavior, specified as a set of transitions; Interactions between transitions of the behavior; Priorities, used to choose amongst possible interactions. A parameterized binary composition operator is used to compose components layer by layer. We present the BIP language for the description and composition of layered components as well as associated tools for executing and analyzing components on a dedicated platform. The language provides a powerful mechanism for structuring interactions involving rendezvous and broadcast. We show that synchronous and timed systems are particular classes of components. Finally, we provide examples showing the utility of the BIP framework in heterogeneous component modeling. We present an improved algorithm to wake up a multi-hop ad-hoc radio network. The goal is to have all the nodes activated, when some of them may wake up spontaneously at arbitrary times and the remaining nodes need to be awoken by the already active ones. The best previously known wake-up algorithm was given by Chrobak, Gasieniec and Kowalski [11], and operated in time O(n5 3 log n), where n is the number of nodes. We give an algorithm with the running time O(n3 2 log n). This also yields better algorithms for other synchronization-type primitives, like leader election and local-clocks synchronization, each with a time performance that differs from that of wake-up by an extra factor of O(log n) only, and improves the best previously known method for the problem by a factor of n1 6. A wake-up algorithm is a schedule of transmissions for each node. It can be represented as a collection of binary sequences. Useful properties of such collections have been abstracted to define a (radio) synchronizer. It has been known that good radio synchronizers exist and previous algorithms [17,11] relied on this. We show how to construct such synchronizers in polynomial time, from suitable constructible expanders. As an application, we obtain a wake-up protocol for a multiple-access channel that activates the network in time O(k2 polylog n), where k is the number of stations that wake up spontaneously, and which can be found in time polynomial in n. We extend the notion of synchronizers to universal synchronizers. We show that there exist universal synchronizers with parameters that guarantee time O(n3 2 log n) of wake-up. We present a methodology for modeling heterogeneous real-time components. Components are obtained as the superposition of three layers : Behavior, specified as a set of transitions; Interactions between transitions of the behavior; Priorities, used to choose amongst possible interactions. A parameterized binary composition operator is used to compose components layer by layer. We present the BIP language for the description and composition of layered components as well as associated tools for executing and analyzing components on a dedicated platform. The language provides a powerful mechanism for structuring interactions involving rendezvous and broadcast. We show that synchronous and timed systems are particular classes of components. Finally, we provide examples and compare the BIP framework to existing ones for heterogeneous component-based modeling. In many applications, nodes in a network desire not only a consensus, but an optimal one. To date, a family of subgradient algorithms have been proposed to solve this problem under general convexity assumptions. This technical note shows that, for the scalar case and by assuming a bit more, novel non-gradient-based algorithms with appealing features can be constructed. Specifically, we develop Pairwise Equalizing (PE) and Pairwise Bisectioning (PB), two gossip algorithms that solve unconstrained, separable, convex consensus optimization problems over undirected networks with time-varying topologies, where each local function is strictly convex, continuously differentiable, and has a minimizer. We show that PE and PB are easy to implement, bypass limitations of the subgradient algorithms, and produce switched, nonlinear, networked dynamical systems that admit a common Lyapunov function and asymptotically converge. Moreover, PE generalizes the well-known Pairwise Averaging and Randomized Gossip Algorithm, while PB relaxes a requirement of PE, allowing nodes to never share their local functions. This paper studies the differences between two levels of synchronization in a distributed broadcast system (or a multiple-access channel). In the globally synchronous model, all processors have access to a global clock. In the locally synchronous model, processors have local clocks ticking at the same rate, but each clock starts individually when the processor wakes up. We consider the fundamental problem of waking up all n processors of a completely connected broadcast system. Some processors wake up spontaneously, while others have to be woken up. Only awake processors can send messages; a sleeping processor is woken up upon hearing a message. The processors hear a message in a given round if and only if exactly one processor sends a message in that round. Our goal is to wake up all processors as fast as possible in the worst case, assuming an adversary controls which processors wake up and when. We analyze the problem in both the globally synchronous and locally synchronous models with or without the assumption that n is known to the processors. We propose randomized and deterministic algorithms for the problem, as well as lower bounds in some of the cases. These bounds establish a gap between the globally synchronous and locally synchronous models. Mobile computing represents a major point of departure from the traditional distributed computing paradigm. The potentially very large number of independent computing units, a decoupled computing style, frequent disconnections, continuous position changes, and the location-dependent nature of the behavior and communication patterns of the individual components present designers with unprecedented challenges in the areas of modularity and dependability. The paper describes two ideas regarding a modular approach to specifying and reasoning about mobile computing. The novelty of our approach rests with the notion of allowing transient interactions among programs which move in space. We restrict our concern to pairwise interactions involving variable sharing and action synchronization. The motivation behind the transient nature of the interactions comes from the fact that components can communicate with each other only when they are within a certain range. The notation we propose is meant to simplify the writing of mobile applications and is a direct extension of that used in UNITY. Reasoning about mobile computations relies on the UNITY proof logic. We present Disco, an asynchronous neighbor discovery and rendezvous protocol that allows two or more nodes to operate their radios at low duty cycles (e.g. 1 ) and yet still discover and communicate with one another during infrequent, opportunistic encounters without requiring any prior synchronization information. The key challenge is to operate the radio at a low duty cycle but still ensure that discovery is fast, reliable, and predictable over a range of operating conditions. Disco nodes pick a pair of prime numbers such that the sum of their reciprocals is equal to the desired radio duty cycle. Each node increments a local counter with a globallyfixed period. If a node's local counter value is divisible by either of its primes, then the node turns on its radio for one period. This protocol ensures that two nodes will have some overlapping radio on-time within a bounded number of periods, even if nodes independently set their own duty cycle. Once a neighbor is discovered, and its wakeup schedule known, rendezvous is just a matter of being awake during the neighbor's next wakeup period,for synchronous rendezvous, or during an overlapping wake period, for asynchronous rendezvous. We study the problem of stochastic optimization for deep learning in the parallel computing environment under communication constraints. A new algorithm is proposed in this setting where the communication and coordination of work among concurrent processes (local workers), is based on an elastic force which links the parameters they compute with a center variable stored by the parameter server (master). The algorithm enables the local workers to perform more exploration, i.e. the algorithm allows the local variables to fluctuate further from the center variable by reducing the amount of communication between local workers and the master. We empirically demonstrate that in the deep learning setting, due to the existence of many local optima, allowing more exploration can lead to the improved performance. We propose synchronous and asynchronous variants of the new algorithm. We provide the stability analysis of the asynchronous variant in the round-robin scheme and compare it with the more common parallelized method ADMM. We show that the stability of EASGD is guaranteed when a simple stability condition is satisfied, which is not the case for ADMM. We additionally propose the momentum-based version of our algorithm that can be applied in both synchronous and asynchronous settings. Asynchronous variant of the algorithm is applied to train convolutional neural networks for image classification on the CIFAR and ImageNet datasets. Experiments demonstrate that the new algorithm accelerates the training of deep architectures compared to DOWNPOUR and other common baseline approaches and furthermore is very communication efficient. Graph matching has a wide spectrum of computer vision applications such as finding feature point correspondences across images. The problem of graph matching is generally NP-hard, so most existing work pursues suboptimal solutions between two graphs. This paper investigates a more general problem of matching N attributed graphs to each other, i.e. labeling their common node correspondences such that a certain compatibility affinity objective is optimized. This multi-graph matching problem involves two key ingredients affecting the overall accuracy: a) the pairwise affinity matching score between two local graphs, and b) global matching consistency that measures the uniqueness and consistency of the pairwise matching results by different sequential matching orders. Previous work typically either enforces the matching consistency constraints in the beginning of iterative optimization, which may propagate matching error both over iterations and across different graph pairs; or separates score optimizing and consistency synchronization in two steps. This paper is motivated by the observation that affinity score and consistency are mutually affected and shall be tackled jointly to capture their correlation behavior. As such, we propose a novel multi-graph matching algorithm to incorporate the two aspects by iteratively approximating the global-optimal affinity score, meanwhile gradually infusing the consistency as a regularizer, which improves the performance of the initial solutions obtained by existing pairwise graph matching solvers. The proposed algorithm with a theoretically proven convergence shows notable efficacy on both synthetic and public image datasets. Abstract The hybrid χ (Chi) formalism integrates concepts from dynamics and control theory with concepts from computer science, in particular from process algebra and hybrid automata. It integrates ease of modeling with a straightforward, structured operational semantics. Its ‘consistent equation semantics’ enforces state changes to be consistent with delay predicates, that combine the invariant and flow clauses of hybrid automata. Ease of modeling is ensured by means of the following concepts: (1) different classes of variables: discrete and continuous, of subclass jumping or non-jumping, and algebraic; (2) strong time determinism of alternative composition in combination with delayable guards; (3) integration of urgent and non-urgent actions; (4) differential algebraic equations as a process term as in mathematics; (5) steady-state initialization; and 6) several user-friendly syntactic extensions. Furthermore, the χ formalism incorporates several concepts for complex system specification: (1) process terms for scoping that integrate abstraction, local variables, local channels and local recursion definitions; (2) process definition and instantiation that enable process re-use, encapsulation, hierarchical and or modular composition of processes; and (3) different interaction mechanisms: handshake synchronization and synchronous communication that allow interaction between processes without sharing variables, and shared variables that enable modular composition of continuous-time or hybrid processes. The syntax and semantics are illustrated using several examples. Anonymous mobile robots are often classified into synchronous, semi-synchronous, and asynchronous robots when discussing the pattern formation problem. For semi-synchronous robots, all patterns formable with memory are also formable without memory, with the single exception of forming a point (i.e., the gathering) by two robots. (All patterns formable with memory are formable without memory for synchronous robots, and little is known for asynchronous robots.) However, the gathering problem for two semi-synchronous robots without memory (called oblivious robots in this paper) is trivially solvable when their local coordinate systems are consistent, and the impossibility proof essentially uses the inconsistencies in their coordinate systems. Motivated by this, this paper investigates the magnitude of consistency between the local coordinate systems necessary and sufficient to solve the gathering problem for two oblivious robots under semi-synchronous and asynchronous models. To discuss the magnitude of consistency, we assume that each robot is equipped with an unreliable compass, the bearings of which may deviate from an absolute reference direction, and that the local coordinate system of each robot is determined by its compass. We consider two families of unreliable compasses, namely, static compasses with (possibly incorrect) constant bearings and dynamic compasses the bearings of which can change arbitrarily (immediately before a new look-compute-move cycle starts and after the last cycle ends). For each of the combinations of robot and compass models, we establish the condition on deviation @math that allows an algorithm to solve the gathering problem, where the deviation is measured by the largest angle formed between the @math -axis of a compass and the reference direction of the global coordinate system: @math for semi-synchronous and asynchronous robots with static compasses, @math for semi-synchronous robots with dynamic compasses, and @math for asynchronous robots with dynamic compasses. Except for asynchronous robots with dynamic compasses, these sufficient conditions are also necessary. Synchronization and localization are critical challenges for the coherent functioning of a wireless network, which are conventionally solved independently. Recently, various estimators have been proposed for pairwise synchronization between immobile nodes, based on time stamp exchanges via two-way communication. In this paper, we consider a network of mobile nodes for which a novel joint time-range model is presented, treating both unsynchronized clocks and the pairwise distances as a polynomial functions of true time. For a pair of nodes, a least squares solution is proposed for estimating the pairwise range parameters between the nodes, in addition to estimating the clock offsets and clock skews. Extending these pairwise solutions to network-wide ranging and clock synchronization, we present a central data fusion based global least squares algorithm. A unique solution is nonexistent without a constraint on the cost function e.g., a clock reference node. Ergo, a constrained framework is proposed and a new Constrained Cramer–Rao Bound (CCRB) is derived for the joint time-range model. In addition, to alleviate the need for a single clock reference, various clock constraints are presented and their benefits are investigated using the proposed solutions. Simulations are conducted and the algorithms are shown to approach the theoretical limits. Abstract Documents in computer-readable form can be used to provide information about other documents, i.e. those they cite. To do this efficiently requires procedures for computer recognition of citing statements. This is not easy, especially for multi-sentence citing statements. Computer recognition procedures have been developed which are accurate to the following extent: 73 of the words in statements selected by computer procedures as being citing statements are words which are correctly attributable to the corresponding documents. The retrieval effectiveness of computer-recognized citing statements was tested in the following way. First, for eight retrieval requests in inorganiic chemistry, average recall by search of Chemical Abstracts Service indexing and Chemical Abstracts abstract text words was found to be 50 . Words from citing statements referring to the papers to be retrieved were then added to the index terms and abstract words as additional access points, and searching was repeated. Average recall increased to 70 . Only words from citing statements published within a year of the cited papers were used. The retrieval effect of citing statement words alone (published within a year) without index or abstract terms was the following: average recall was 40 . When just the words of the titles of the cited papers were added to those citing statement words, average recall increased to 50 . When computing descriptors of image data, the type of information that can be extracted may be strongly dependent on the scales at which the image operators are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of scale levels when detecting one-dimensional image features, such as edges and ridges. A novel concept of a scale-space edge is introduced, defined as a connected set of points in scale-space at which: (i) the gradient magnitude assumes a local maximum in the gradient direction, and (ii) a normalized measure of the strength of the edge response is locally maximal over scales. An important consequence of this definition is that it allows the scale levels to vary along the edge. Two specific measures of edge strength are analyzed in detail, the gradient magnitude and a differential expression derived from the third-order derivative in the gradient direction. For a certain way of normalizing these differential descriptors, by expressing them in terms of so-called γ-normalized derivatives, an immediate consequence of this definition is that the edge detector will adapt its scale levels to the local image structure. Specifically, sharp edges will be detected at fine scales so as to reduce the shape distortions due to scale-space smoothing, whereas sufficiently coarse scales will be selected at diffuse edges, such that an edge model is a valid abstraction of the intensity profile across the edge. Since the scale-space edge is defined from the intersection of two zero-crossing surfaces in scale-space, the edges will by definition form closed curves. This simplifies selection of salient edges, and a novel significance measure is proposed, by integrating the edge strength along the edge. Moreover, the scale information associated with each edge provides useful clues to the physical nature of the edge. With just slight modifications, similar ideas can be used for formulating ridge detectors with automatic selection, having the characteristic property that the selected scales on a scale-space ridge instead reflect the width of the ridge. It is shown how the methodology can be implemented in terms of straightforward visual front-end operations, and the validity of the approach is supported by theoretical analysis as well as experiments on real-world and synthetic data. We analyze the convergence of gradient-based optimization algorithms that base their updates on delayed stochastic gradient information. The main application of our results is to the development of gradient-based distributed optimization algorithms where a master node performs parameter updates while worker nodes compute stochastic gradients based on local information in parallel, which may give rise to delays due to asynchrony. We take motivation from statistical problems where the size of the data is so large that it cannot fit on one computer; with the advent of huge datasets in biology, astronomy, and the internet, such problems are now common. Our main contribution is to show that for smooth stochastic problems, the delays are asymptotically negligible and we can achieve order-optimal convergence results. In application to distributed optimization, we develop procedures that overcome communication bottlenecks and synchronization requirements. We show @math -node architectures whose optimization error in stochastic problems---in spite of asynchronous delays---scales asymptotically as @math after @math iterations. This rate is known to be optimal for a distributed system with @math nodes even in the absence of delays. We additionally complement our theoretical results with numerical experiments on a statistical machine learning task. Abstract : Persistent controversies about human multiple task performance suggest that research on it will benefit from increased use of precise computational models. Toward this objective, the present report outlines a comprehensive theoretical framework for understanding and predicting the performance of concurrent perceptual motor and cognitive tasks. The framework involves an Executive Process Interactive Control (EPIC) architecture, which has component modules that process information at perceptual, cognitive, and motor levels. On the basis of EPIC, computational models that use a production system formalism may be constructed to simulate multiple task performance under a variety of conditions. These models account well for reaction time data from representative paradigms such as the psychological refractory period (PRP) procedure. With modest numbers of parameters, good fits between empirical and simulated reaction times support several key conclusions: (1) at a cognitive level, people can apply distinct sets of production rules simultaneously for executing the procedures of multiple tasks; (2) there is no immutable central response selection or decision bottleneck; (3) people's capacity to process information and take action at peripheral perceptual motor levels is limited; (4) to cope with such limits and to satisfy task priorities, flexible scheduling strategies are used; (5) these strategies are mediated by executive cognitive processes that coordinate concurrent tasks adaptively. The initial success of EPIC and models based on it suggest that they may help characterize multiple task performance across many domains, including ones that have substantial practical relevance. A local algorithm with local horizon r is a distributed algorithm that runs in r synchronous communication rounds; here r is a constant that does not depend on the size of the network. As a consequence, the output of a node in a local algorithm only depends on the input within r hops from the node. We give tight bounds on the local horizon for a class of local algorithms for combinatorial problems on unit-disk graphs (UDGs). Most of our bounds are due to a refined analysis of existing approaches, while others are obtained by suggesting new algorithms. The algorithms we consider are based on network decompositions guided by a rectangular tiling of the plane. The algorithms are applied to matching, independent set, graph colouring, vertex cover, and dominating set. We also study local algorithms on quasi-UDGs, which are a popular generalisation of UDGs, aimed at more realistic modelling of communication between the network nodes. Analysing the local algorithms on quasi-UDGs allows one to assume that the nodes know their coordinates only approximately, up to an additive error. Despite the localisation error, the quality of the solution to problems on quasi-UDGs remains the same as for the case of UDGs with perfect location awareness. We analyse the increase in the local horizon that comes along with moving from UDGs to quasi-UDGs. Abstract We describe a new fault-tolerant algorithm for solving a variant of Lamport's clock synchronization problem. The algorithm is designed for a system of distributed processes that communicate by sending messages. Each process has its own read-only physical clock whose drift rate from real time is very small. By adding a value to its physical clock time, the process obtaines its local time. The algorithm solves the problem of maintaining closely synchronized local times, assuming that processes' local times are closely synchronized initially. The algorithm is able to tolerate the failure of just under one-third of the participating processes. It maintains synchronization to within a small constant, whose magnitude depends upon the rate of clock drift, the message delivery time and its uncertainty, and the initial closeness of synchronization. We also give a characterization of how far the clocks drift from real time. Reintegration of a repaired process can be accomplished using a slight modification of the basic alborithm. A similar style algorithm can also be used to achieve synchronization initially.