Paper Info
Title
Dependability of On-Line Optimization Techniques in Real-Time Applications
Abstract
Real-time problem solvers require dependable, real-time search algorithms to meet task deadlines and to predict deadline violations. Presently it is difficult for existing real-time search algorithms to search and execute the solution by the deadline and to make deadline violation prediction. In this paper, we introduce a real-time search algorithm called Self-Adjusting Real-Time Search (SARTS). Given a timing constraint, SARTS adjusts itself based on the remaining time to deadline and allocates the planning time. As the timing constraints are relaxed, it will continue to improve its solutions progressively. The algorithm is able to predict deadline violations. Theoretical analyses and experimental results reveal that, compared to the existing techniques, SARTS demonstrates a higher degree of predictability and a higher deadline compliance ability.
Year
DOI
Venue
1999
10.1109/WORDS.1999.806576
Santa Barbara, CA
Keywords
Field
DocType
real-time search algorithm,task deadline,higher deadline compliance ability,existing technique,deadline violation,real-time applications,on-line optimization techniques,planning time,timing constraint,higher degree,deadline violation prediction,real-time problem solvers,search algorithm,real time systems,software reliability,real time,real time applications
Dependability,Predictability,Search algorithm,Computer science,Real-time computing,Software quality,Distributed computing
Conference
ISBN
Citations 
PageRank 
0-7695-0101-X
0
0.34
References 
Authors
5
2
Name
Order
Citations
PageRank
Hamidzadeh Babak118424.99
Shashi Shekhar243521098.43