deadline scheduling
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2020 ◽  
Vol 4 (5) ◽  
pp. 957-963
Author(s):  
Haidar Hendri Setyawan ◽  
Wisnu Widiarto ◽  
Ardhi Wijayanto

Resource Scheduling is one of the most challenging parts of grid computing. A number of algorithms have been designed and developed to create effective resource scheduling. In this research, the algorithms that have been used are the improvised prioritized deadline scheduling algorithm (IPDSA), and the parallel virtual machine version 3 (PVM3) has been used for efficient task execution, with a deadline limit for each task. PVM3 is a software library that optimizes resources flexibly and heterogeneously on a computer. These resources have been connected to various architectures in parallel, so that they can complete tasks well, even though they are very large and complex. This research has implemented the IPDSA resource scheduling algorithm to optimize scheduling and Grid resources in a computer laboratory as a grid environment, where the computers (hosts) are the Grid resource. This research has also developed an IPDSA resource scheduling algorithm by giving priority to each task and implemented using PVM3. The IPDSA resource scheduling algorithm has been successfully implemented using PVM3, with average Tardiness showing a stable value and getting a Non-Delayed Task value above 97.3%, because the resources and tasks that are carried out can be distributed evenly according to the number of hosts used.


2019 ◽  
Vol 46 (3) ◽  
pp. 56-61 ◽  
Author(s):  
Yorie Nakahira ◽  
Andres Ferragut ◽  
Adam Wierman

2018 ◽  
Vol 63 (8) ◽  
pp. 2343-2358 ◽  
Author(s):  
Zhe Yu ◽  
Yunjian Xu ◽  
Lang Tong

2018 ◽  
Vol 76 ◽  
pp. 354-366 ◽  
Author(s):  
Mihai Varga ◽  
Alina Petrescu-Nita ◽  
Florin Pop

2018 ◽  
Author(s):  
Mohammad Noormohammadpour ◽  
Cauligi S. Raghavendra ◽  
Sriram Rao ◽  
Asad M. Madni

Datacenter-based Cloud Computing services provide a flexible, scalable and yet economical infrastructure to host online services such as multimedia streaming, email and bulk storage. Many such services perform geo-replication to provide necessary quality of service and reliability to users resulting in frequent large inter-datacenter transfers. In order to meet tenant service level agreements (SLAs), these transfers have to be completed prior to a deadline. In addition, WAN resources are quite scarce and costly, meaning they should be fully utilized. Several recently proposed schemes, such as B4 [1], TEMPUS [2], and SWAN [3] have focused on improving the utilization of inter-datacenter transfers through centralized scheduling, however, they fail to provide a mechanism to guarantee that admitted requests meet their deadlines. Also, in a recent study, authors propose Amoeba [4], a system that allows tenants to define deadlines and guarantees that the specified deadlines are met, however, to admit new traffic, the proposed system has to modify the allocation of already admitted transfers. In this paper, we propose Rapid Close to Deadline Scheduling (RCD), a close to deadline traffic allocation technique that is fast and efficient. Through simulations, we show that RCD is up to 15 times faster than Amoeba, provides high link utilization along with deadline guarantees, and is able to make quick decisions on whether a new request can be fully satisfied before its deadline.


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