Optimized Disk Layouts for Adaptive Storage of Interaction Graphs
Robert Soul\'e, B\"ugra Gedik

TL;DR
This paper introduces the railway layout, an adaptive disk storage method for interaction graphs that improves query efficiency by partitioning attributes into sub-blocks, balancing storage overhead and I/O performance.
Contribution
The paper proposes a novel adaptive disk layout called the railway layout, with ILP and heuristic algorithms for optimal and scalable partitioning of interaction graph data.
Findings
The railway layout improves query I/O performance in interaction graphs.
Heuristic approaches achieve near-optimal results with better scalability.
Experimental results demonstrate significant benefits over baseline storage methods.
Abstract
We are living in an ever more connected world, where data recording the interactions between people, software systems, and the physical world is becoming increasingly prevalent. This data often takes the form of a temporally evolving graph, where entities are the vertices and the interactions between them are the edges. We call such graphs interaction graphs. Various application domains, including telecommunications, transportation, and social media, depend on analytics performed on interaction graphs. The ability to efficiently support historical analysis over interaction graphs require effective solutions for the problem of data layout on disk. This paper presents an adaptive disk layout called the railway layout for optimizing disk block storage for interaction graphs. The key idea is to divide blocks into one or more sub-blocks, where each sub-block contains a subset of the…
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Taxonomy
TopicsGraph Theory and Algorithms · Distributed and Parallel Computing Systems · Parallel Computing and Optimization Techniques
