Paper Info
Title
Towards load shedding and scheduling schemes for data streams that maintain quality and timing requirements of query results.
Abstract
Real-time stream processing is essential for many real-life stream-based applications. Systems designed to run such applications must be prepared to operate under overloaded conditions. In this paper, the load shedding problem is studied for an important class of real-time data stream monitoring applications. In particular, we adopt the \((m,k)\) deadline model, instead of the commonly used random dropping policy, to capture the QoS requirements of such applications. Based on this model, we propose a Safe lOad Shedding Approach (SOSA) that aims to reduce the workload imposed on the system while at the same time preserve system timing constraints by exploiting data stream semantics. SOSA categorizes stream processing into two different modes and allows one to place provably lighter loads on streams that operate in one particular mode. To demonstrate the usefulness of SOSA, we introduce a concrete \((m,k)\) scheduling algorithm called SOSA-DBP by combining SOSA with DBP, a well-known \((m,k)\) scheduling algorithm. Probabilistic analysis and experimental results show that SOSA-DBP has significant performance gain over DBP.
Year
DOI
Venue
2016
10.1007/s00500-015-1617-5
soft computing
Keywords
Field
DocType
Schedule Algorithm, Mode Change, Priority Level, Continuous Query, Dynamic Failure
Data stream mining,Mathematical optimization,Computer science,Scheduling (computing),Workload,Data stream,Quality of service,Probabilistic analysis of algorithms,Stream processing,Load Shedding,Distributed computing
Journal
Volume
Issue
ISSN
20
5
1433-7479
Citations 
PageRank 
References 
0
0.34
20
Authors
4
Name
Order
Citations
PageRank
Guo-Qin Ning100.34
Hongya Wang2175.71
Lihchyun Shu313017.32
GuangRew Yeh400.34