Title :
Profiling-Based Task Scheduling for Factory-Worker Applications in Infrastructure-as-a-Service Clouds
Author :
Zabolotnyi, Rostyslav ; Leitner, Philipp ; Dustdar, Schahram
Author_Institution :
Distrib. Syst. Group, Vienna Univ. of Technol., Vienna, Austria
Abstract :
With the recent advances of cloud computing, effective resource usage (e.g., CPU, memory or network) becomes an important question as application developers have to continuously pay for rented resources, even if they are not used effectively. In order to maintain required performance levels, it is currently common to reserve resources for peak resource usage or possible resource usage overlaps, if more than one task is executed on a host. While this is a reasonable approach for long-running applications or web servers, for some applications with disperse resource usage over time, this strategy causes significant over-provisioning and thus resource wastage and financial loss. In this paper we present a profiling-based task scheduling approach for factory-worker applications that schedules tasks within the defined resource limitations (e.g., Existing machine memory size or network quota) and distributes the tasks in the cloud environment in order to use resources effectively. The evaluation of our approach approved the efficiency of the proposed algorithm and minimal performance overhead. In case of the evaluated application, the presented scheduling process leads up to 33% resource savings with only 1% of performance loss.
Keywords :
cloud computing; file servers; personnel; production engineering computing; resource allocation; scheduling; Web servers; cloud computing; cloud environment; factory-worker applications; infrastructure-as-a-service clouds; machine memory size; network quota; profiling-based task scheduling approach; resource limitations; resource wastage; Cloud computing; Current measurement; Memory management; Processor scheduling; Random access memory; Schedules; Time measurement; Cloud computing; Elasticity; Factory-worker; Infrastructure-as-a-Service; Profiling; Resource usage; Scheduling;
Conference_Titel :
Software Engineering and Advanced Applications (SEAA), 2014 40th EUROMICRO Conference on
Conference_Location :
Verona
DOI :
10.1109/SEAA.2014.42