Paper Info
Title
Opportunistic Content Search of Smartphone Photos
Abstract
Photos taken by smartphone users can accidentally contain content that is timely and valuable to others, often in real-time. We report the system design and evaluation of a distributed search system, Theia, for crowd-sourced real-time content search of smartphone photos. Because smartphones are resource-constrained, Theia incorporates two key innovations to control search cost and improve search efficiency. Incremental Search expands search scope incrementally and exploits user feedback. Partitioned Search leverages the cloud to reduce the energy consumption of search in smartphones. Through user studies, measurement studies, and field studies, we show that Theia reduces the cost per relevant photo by an average of 59%. It reduces the energy consumption of search by up to 55% and 81% compared to alternative strategies of executing entirely locally or entirely in the cloud. Search results from smartphones are obtained in seconds. Our experiments also suggest approaches to further improve these results.
Year
Venue
Keywords
2011
CoRR
information retrieval,real time,search cost,system design,field study
Field
DocType
Volume
Giant impact hypothesis,Search engine,Information retrieval,Computer science,Incremental search,Exploit,Search cost,Search analytics,Energy consumption,Cloud computing
Journal
abs/1106.5568
Citations 
PageRank 
References 
3
0.57
14
Authors
7
Name
Order
Citations
PageRank
Ardalan Amiri Sani114921.84
Wolfgang Richter21128.66
Xuan Bao339025.51
Trevor Narayan471.59
M. Satyanarayanan587741707.65
Lin Zhong63131213.03
Romit Roy Choudhury73951233.31