Proceedings ArticleDOI
Pregel: a system for large-scale graph processing
Grzegorz Malewicz,Matthew H. Austern,Aart J. C. Bik,James C. Dehnert,Ilan Horn,Naty Leiser,Grzegorz Czajkowski +6 more
- pp 135-146
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TLDR
A model for processing large graphs that has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier.Abstract:
Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. In this paper we present a computational model suitable for this task. Programs are expressed as a sequence of iterations, in each of which a vertex can receive messages sent in the previous iteration, send messages to other vertices, and modify its own state and that of its outgoing edges or mutate graph topology. This vertex-centric approach is flexible enough to express a broad set of algorithms. The model has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier. Distribution-related details are hidden behind an abstract API. The result is a framework for processing large graphs that is expressive and easy to program.read more
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Proceedings ArticleDOI
TenantGuard: Scalable Runtime Verification of Cloud-Wide VM-Level Network Isolation
Yushun Wang,Taous Madi,Suryadipta Majumdar,Yosr Jarraya,Amir Alimohammadifar,Makan Pourzandi,Lingyu Wang,Mourad Debbabi +7 more
TL;DR: TenantGuard is presented, a scalable system for verifying cloud-wide, VM-level network isolation at runtime that takes advantage of the hierarchical nature of virtual networks, efficient data structures, incremental verification, and parallel computation to reduce the performance overhead of security verification.
Proceedings ArticleDOI
Using property graphs for rich metadata management in HPC systems
TL;DR: This paper proposes a rich metadata management approach that unifies metadata into one generic property graph and argues that this approach supports not only simple metadata operations such as directory traversal and permission validation but also rich metadata operationssuch as provenance query and security auditing.
Journal ArticleDOI
GrapH: Traffic-Aware Graph Processing
TL;DR: GrapH is developed, the first graph processing system using vertex-cut graph partitioning that considers both, diverse vertex traffic and heterogeneous network costs, and the main idea is to avoid frequent communication over expensive network links using an adaptive edge migration strategy.
Proceedings ArticleDOI
DStress: Efficient Differentially Private Computations on Distributed Data
TL;DR: DStress is presented, a system that can efficiently perform computations on graphs that contain confidential data and protects privacy by enforcing tight, provable limits on how much each participant can learn about the rest of the graph.
Journal ArticleDOI
Cogset: a high performance MapReduce engine
TL;DR: Cogset's architecture is presented and its performance as a MapReduce engine is evaluated, comparing it with Hadoop, showing that Cogset generally outperforms Hadoops by a significant margin.
References
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Journal ArticleDOI
A note on two problems in connexion with graphs
TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This paper presents the implementation of MapReduce, a programming model and an associated implementation for processing and generating large data sets that runs on a large cluster of commodity machines and is highly scalable.
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This presentation explains how the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
Journal ArticleDOI
The anatomy of a large-scale hypertextual Web search engine
Sergey Brin,Lawrence Page +1 more
TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.
Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.