Title :
Planning in the Cloud: Massively Parallel Planning
Author :
Thompson, Tommy ; Voorhis, Dave
Author_Institution :
Dept. of Comput. & Math., Univ. of Derby, Derby, UK
Abstract :
This paper describes preliminary work in creating a scalable service for the purposes of automated planning and scheduling: a methodology within artificial intelligence that requires flexible computational resources on a per-problem basis. We describe the challenges of automated planning and how moving solution construction to a distributed system alleviates issues faced in the application of planning in real-world problems. We explore how the current system has been designed and give indication of how this work moves towards creating an online planning service that is scalable to the needs of both individual users and the overall workload required of the system.
Keywords :
cloud computing; planning (artificial intelligence); artificial intelligence; automated planning; automated scheduling; cloud computing; distributed system; flexible computational resources; massively parallel planning; moving solution construction; online planning service; Cloud computing; Conferences; Planning; Search problems; Servers; Throughput; Automated planning; cloud computing; utility;
Conference_Titel :
Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
Conference_Location :
London
DOI :
10.1109/UCC.2014.67