scispace - formally typeset
Search or ask a question
Topic

Distributed algorithm

About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: The problem of judiciously and transparently redistributing the load of the system among its nodes so that overall performance is maximized is discussed and conclusions about which algorithm might help in realizing the most benefits of load distributing are drawn.
Abstract: The problem of judiciously and transparently redistributing the load of the system among its nodes so that overall performance is maximized is discussed. Several key issues in load distributing for general-purpose systems, including the motivations and design trade-offs for load-distributing algorithms, are reviewed. In addition, several load-distributing algorithms are described and their performances are compared. These algorithms are sender-initiated algorithms, receiver-initiated algorithms, symmetrically initiated algorithms, and adaptive algorithms. Load-distributing policies used in existing systems are examined, and conclusions about which algorithm might help in realizing the most benefits of load distributing are drawn. >

583 citations

Proceedings ArticleDOI
31 May 1999
TL;DR: A novel and efficient distributed algorithm, called -link matching, which performs just enough computation at each node to determine the subset of links to which an event should be forwarded and yields higher throughput than flooding when subscriptions are selective.
Abstract: The publish/subscribe (or pub/sub) paradigm is an increasingly popular model for interconnecting applications in a distributed environment. Many existing pub/sub systems are based on pre-defined subjects, and hence are able to exploit multicast technologies to provide scalability and availability. An emerging alternative to subject-based systems, known as content-based systems, allow information consumers to request events based on the content of published events. This model is considerably more flexible than subject-based pub/sub. However, it was previously not known how to efficiently multicast published events to interested content-based subscribers within a large and geographically distributed network of broker (or router) machines. We develop and evaluate a novel and efficient distributed algorithm for this purpose, called -link matching". Link matching performs just enough computation at each node to determine the subset of links to which an event should be forwarded. We show via simulations that: link matching yields higher throughput than flooding when subscriptions are selective; and the overall CPU utilization of link matching is comparable to that of centralized matching.

582 citations

Journal ArticleDOI
TL;DR: This thesis proposes a distributed computational economy as an effective metaphor for the management of resources and application scheduling and proposes an architectural framework that supports resource trading and quality of services based scheduling that enables the regulation of supply and demand for resources.
Abstract: Computational Grids, emerging as an infrastructure for next generation computing, enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. As the resources in the Grid are heterogeneous and geographically distributed with varying availability and a variety of usage and cost policies for diverse users at different times and, priorities as well as goals that vary with time. The management of resources and application scheduling in such a large and distributed environment is a complex task. This thesis proposes a distributed computational economy as an effective metaphor for the management of resources and application scheduling. It proposes an architectural framework that supports resource trading and quality of services based scheduling. It enables the regulation of supply and demand for resources and provides an incentive for resource owners for participating in the Grid and motives the users to trade-off between the deadline, budget, and the required level of quality of service. The thesis demonstrates the capability of economic-based systems for peer-to-peer distributed computing by developing users' quality-of-service requirements driven scheduling strategies and algorithms. It demonstrates their effectiveness by performing scheduling experiments on the World-Wide Grid for solving parameter sweep applications.

579 citations

Journal ArticleDOI
TL;DR: An iterative cluster Primal Dual Splitting algorithm for solving the large-scale sSVM problem in a decentralized fashion, which extracts important features discovered by the algorithm that are predictive of future hospitalizations, thus providing a way to interpret the classification results and inform prevention efforts.

577 citations

Journal Article
TL;DR: This work presents the distributed mini-batch algorithm, a method of converting many serial gradient-based online prediction algorithms into distributed algorithms that is asymptotically optimal for smooth convex loss functions and stochastic inputs and proves a regret bound for this method.
Abstract: Online prediction methods are typically presented as serial algorithms running on a single processor. However, in the age of web-scale prediction problems, it is increasingly common to encounter situations where a single processor cannot keep up with the high rate at which inputs arrive. In this work, we present the distributed mini-batch algorithm, a method of converting many serial gradient-based online prediction algorithms into distributed algorithms. We prove a regret bound for this method that is asymptotically optimal for smooth convex loss functions and stochastic inputs. Moreover, our analysis explicitly takes into account communication latencies between nodes in the distributed environment. We show how our method can be used to solve the closely-related distributed stochastic optimization problem, achieving an asymptotically linear speed-up over multiple processors. Finally, we demonstrate the merits of our approach on a web-scale online prediction problem.

565 citations


Network Information
Related Topics (5)
Server
79.5K papers, 1.4M citations
94% related
Scheduling (computing)
78.6K papers, 1.3M citations
91% related
Network packet
159.7K papers, 2.2M citations
91% related
Wireless network
122.5K papers, 2.1M citations
91% related
Wireless sensor network
142K papers, 2.4M citations
89% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202381
2022135
2021583
2020759
2019876
2018845