Abstract
Social networking applications' disk access patterns differ from those of traditional applications. However, today's disk layout techniques aren't adapted to social networking workloads, and thus their performance suffers. The authors' disk layout techniques leverage community structure in a social graph to make placement decisions that optimize read latency. Their layout manager, Bondhu, incorporates these techniques and is integrated into the popular Neo4j graph database engine. Experimental results show that Bondhu improves the median response time for online social network operations by as much as 48 percent.
Original language | English (US) |
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Article number | 6165251 |
Pages (from-to) | 24-36 |
Number of pages | 13 |
Journal | IEEE Internet Computing |
Volume | 16 |
Issue number | 3 |
DOIs | |
State | Published - May 2012 |
Keywords
- data organization
- disk layout
- social network
- storage management
ASJC Scopus subject areas
- Computer Networks and Communications