@inproceedings{6f35550fabe94267a17078900883e3d6,
title = "Hybrid workflow management in cloud broker system",
abstract = "In Cloud broker system, workflow application requests from different users are managed through workflow scheduling and resource provisioning. In workflow scheduling phase, most existing algorithms allocate each task on certain VM in serial. In general, single task does not fully utilize allocated resource such as CPU, memory, and so on. When multiple tasks are processed with same resource in parallel, the resource utilization is improved that leads to saving the cost. In order to solve this problem, the Parallel Task Merging scheme in the same VM is proposed, which saves the cost of execution while satisfying SLA deadline. After workflow scheduling, VM resource provisioning is required. Auto-scaling VM resources approach is proposed, which adjusts the number of VMs while the number of requests varies. In this paper, we do experiment the parallel task merging and auto-scaling approaches on different environments to observe on which conditions these two approaches are working well or not.",
keywords = "Cloud resource provisioning, Virtual machine allocation, Workflow scheduling",
author = "Dongsik Yoon and Kim, \{Seong Hwan\} and Kang, \{Dong Ki\} and Youn, \{Chan Hyun\}",
note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.; 6th International Conference on Cloud Computing, CloudComp 2015 ; Conference date: 28-10-2015 Through 29-10-2015",
year = "2016",
doi = "10.1007/978-3-319-38904-2\_15",
language = "English",
isbn = "9783319389035",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Verlag",
pages = "145--155",
editor = "Yin Zhang and Chan-Hyun Youn and Limei Peng",
booktitle = "Cloud Computing - 6th International Conference, CloudComp 2015",
}