Header

UZH-Logo

Maintenance Infos

The CLOCK Data-Aware Eviction Approach: Towards Processing Linked Data Streams with Limited Resources


Gao, Shen; Scharrenbach, Thomas; Bernstein, Abraham (2014). The CLOCK Data-Aware Eviction Approach: Towards Processing Linked Data Streams with Limited Resources. In: The 11th Extended Semantic Web Conference, Crete, Greece, 25 May 2014 - 29 May 2014.

Abstract

Processing streams rather than static files of Linked Data has gained increasing importance in the web of data. When processing data streams system builders are faced with the conundrum of guaranteeing a constant maximum response time with limited resources and, possibly, no prior information on the data arrival frequency. One approach to address this issue is to delete data from a cache during processing – a process we call eviction. The goal of this paper is to show that data- driven eviction outperforms today’s dominant data-agnostic approaches such as first-in-first-out or random deletion. Specifically, we first introduce a method called Clock that evicts data from a join cache based on the likelihood estimate of contributing to a join in the future. Second, using the well-established SR-Bench benchmark as well as a data set from the IPTV domain, we show that Clock outperforms data-agnostic approaches indicating its usefulness for resource-limited linked data stream processing.

Abstract

Processing streams rather than static files of Linked Data has gained increasing importance in the web of data. When processing data streams system builders are faced with the conundrum of guaranteeing a constant maximum response time with limited resources and, possibly, no prior information on the data arrival frequency. One approach to address this issue is to delete data from a cache during processing – a process we call eviction. The goal of this paper is to show that data- driven eviction outperforms today’s dominant data-agnostic approaches such as first-in-first-out or random deletion. Specifically, we first introduce a method called Clock that evicts data from a join cache based on the likelihood estimate of contributing to a join in the future. Second, using the well-established SR-Bench benchmark as well as a data set from the IPTV domain, we show that Clock outperforms data-agnostic approaches indicating its usefulness for resource-limited linked data stream processing.

Statistics

Citations

Downloads

69 downloads since deposited on 24 Mar 2014
15 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:29 May 2014
Deposited On:24 Mar 2014 14:06
Last Modified:11 Aug 2017 23:06
Publisher:Springer
Series Name:Lecture Notes in Computer Science
ISSN:0302-9743
Other Identification Number:merlin-id:9324

Download

Preview Icon on Download
Preview
Content: Accepted Version
Language: English
Filetype: PDF
Size: 439kB