This work focuses on understanding the quantum message complexity of two central problems in distributedcomputing, namely, leader election and agreement in synchronous message-passing communication networks. We show ...
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ISBN:
(纸本)9798400718854
This work focuses on understanding the quantum message complexity of two central problems in distributedcomputing, namely, leader election and agreement in synchronous message-passing communication networks. We show that quantum communication gives an advantage for both problems by presenting quantum distributed algorithms that significantly outperform their respective classical counterparts under various network *** prior works have studied and analyzed quantum distributed algorithms in the context of (improving) round complexity, a key conceptual contribution of our work is positing a framework to design and analyze the message complexity of quantum distributed algorithms. We present and demonstrate how quantum algorithmic techniques, such as Grover search, quantum counting, and quantum walks, can significantly enhance the message efficiency of distributed *** particular, our leader election protocol for diameter-2 networks uses quantum walks to achieve the improved message complexity. To the best of our knowledge, this is the first such application of quantum walks in distributedcomputing.
We present poly log log n-round randomized distributed algorithms to compute vertex splittings, a partition of the vertices of a graph into k parts such that a node of degree d(u) has ≈ d(u)/k neighbors in each part....
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Real-time data processing applications with low latency requirements have led to the increasing popularity of stream processing systems. While such systems offer convenient APIs that can be used to achieve data parall...
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ISBN:
(纸本)9781450392044
Real-time data processing applications with low latency requirements have led to the increasing popularity of stream processing systems. While such systems offer convenient APIs that can be used to achieve data parallelism automatically, they offer limited support for computations that require synchronization between parallel nodes. In this paper, we propose dependency-guided synchronization (DGS), an alternative programming model for stateful streaming computations with complex synchronization requirements. In the proposed model, the input is viewed as partially ordered, and the program consists of a set of parallelization constructs which are applied to decompose the partial order and process events independently. Our programming model maps to an execution model called synchronization plans which supports synchronization between parallel nodes. Our evaluation shows that APIs offered by two widely used systems-Flink and Timely Dataflow-cannot suitably expose parallelism in some representative applications. In contrast, DGS enables implementations with scalable performance, the resulting synchronization plans offer throughput improvements when implemented manually in existing systems, and the programming overhead is small compared to writing sequential code.
Population protocols are a model of computation in which an arbitrary number of indistinguishable finite-state agents interact in pairs. The goal of the agents is to decide by stable consensus whether their initial gl...
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ISBN:
(纸本)9781450385480
Population protocols are a model of computation in which an arbitrary number of indistinguishable finite-state agents interact in pairs. The goal of the agents is to decide by stable consensus whether their initial global configuration satisfies a given property, specified as a predicate on the set of configurations. The state complexity of a predicate is the number of states of a smallest protocol that computes it. Previous work by Blondin et al. has shown that the counting predicates x >= eta have state complexity O(log eta) for leaderless protocols and O(log log eta) for protocols with leaders. We obtain the first non-trivial lower bounds: the state complexity of x >= eta is Omega(log log log eta) for leaderless protocols, and the inverse of a non-elementary function for protocols with leaders.
Data provenance, or data lineage, describes the life cycle of data. In scientific workflows on HPC systems, scientists often seek diverse provenance (e.g., origins of data products, usage patterns of datasets). Unfort...
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ISBN:
(纸本)9781450391993
Data provenance, or data lineage, describes the life cycle of data. In scientific workflows on HPC systems, scientists often seek diverse provenance (e.g., origins of data products, usage patterns of datasets). Unfortunately, existing provenance solutions cannot address the challenges due to their incompatible provenance models and/or system implementations. In this paper, we analyze three representative scientific workflows in collaboration with the domain scientists to identify concrete provenance needs. Based on the first-hand analysis, we propose a provenance framework called PROV-IO, which includes an I/O-centric provenance model for describing scientific data and the associated I/O operations and environments precisely. Moreover, we build a prototype of PROV-IO to enable end-to-end provenance support on real HPC systems with little manual effort. The PROV-IO framework provides flexibility in selecting various classes of provenance. Our experiments with realistic workflows show that PROV-IO can address the provenance needs of the domain scientists effectively with reasonable performance (e.g., less than 3.5% tracking overhead for most experiments). Moreover, PROV-IO outperforms a state-of-the-art system (i.e., ProvLake) in our experiments.
The implementation of registers from (potentially) weaker registers is a classical problem in the theory of distributedcomputing. Since Lamport's pioneering work [14], this problem has been extensively studied in...
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Interplanetary distributed systems, such as the Interplanetary Internet, and the Global Positioning System (GPS) are subject to the effects of Einstein's theory of relativity. In this paper, we study relativistic ...
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ISBN:
(纸本)9798400718854
Interplanetary distributed systems, such as the Interplanetary Internet, and the Global Positioning System (GPS) are subject to the effects of Einstein's theory of relativity. In this paper, we study relativistic distributed systems, which are subject to the relativity of simultaneity. We formulate a unified computational model for relativistic and classical distributed systems and study the relationship between properties of distributed algorithms deployed on the two types of systems. Classical executions are totally ordered in time, whereas the steps of a relativistic execution are only partially ordered by the relation of relativistic causality. We relate these two physics-dependent execution types through a third—purely mathematical—notion of a computational execution, which partially orders steps by the relation of computational causality. We relate relativistic, classical, and computational executions of distributed algorithms through a central theorem, which states that the following are equivalent for any distributed algorithm A: (1) A satisfies a property P classically; (2) every relativistic execution of A satisfies P in the reference frame of every observer; and (3) every total ordering of every computational execution of A satisfies P. As a direct consequence, we prove the equivalence of the standard, relativistic, and computational formulations of linearizability. Our results show that a host of algorithms originally designed for classical distributed systems will behave consistently when deployed in relativistic, interplanetary distributed systems.
We initiate the study of distributed graph algorithms with predictions in synchronous message passing systems. Each node in the graph is given a prediction, which is some extra information about the problem instance t...
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ISBN:
(纸本)9798400718854
We initiate the study of distributed graph algorithms with predictions in synchronous message passing systems. Each node in the graph is given a prediction, which is some extra information about the problem instance that may be incorrect. The better the prediction, the fewer rounds the algorithm should perform. We present a framework for evaluating distributed graph algorithms with predictions and some methods for transforming existing algorithms without predictions to effectively use predictions. Our approach is illustrated using the Maximal Independent Set problem.
Resolving an open question from 2006 [14], we prove the existence of light-weight bounded-degree spanners for unit ball graphs in the metrics of bounded doubling dimension, and we design a simple O(log∗ n)-round distr...
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Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an u...
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ISBN:
(纸本)9781450385480
Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed systems problem. This paper presents an efficient solution to the load balancing problem in such systems that improves on and overcomes problems of previous solutions. The load balancing problem is formulated as a stochastic optimization problem, and an efficient algorithmic solution is obtained based on a subtle mathematical analysis of the problem. Finally, extensive evaluation of the solution on simulated data shows that it outperforms previous solutions. Moreover, the resulting dispatching policy can be computed very efficiently, making the solution practically viable.
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