Abstract Decision Engine for Task Scheduling in Linux Based Operating Systems

2020 ◽  
pp. 746-750
Author(s):  
Sreeram Sadasivam ◽  
Malin Ewering ◽  
Horst Schwichtenberg
Keyword(s):  
Task Scheduling ◽  
Operating Systems ◽  
Decision Engine

A Review of the Scopes and Challenges of the Modern Real-Time Operating Systems

2018 ◽  
Vol 9 (1) ◽  
pp. 66-82 ◽  
Author(s):  
Amit K. Shukla ◽  
Rachit Sharma ◽  
Pranab K. Muhuri
Keyword(s):  
Operating System ◽  
Embedded System ◽  
Real Time ◽  
Task Scheduling ◽  
Operating Systems ◽  
Computational Cost ◽  
Dynamic Environments ◽  
Real Time Operating System ◽  
Starting Point ◽  
Design Challenges

A real-time operating system (RTOS) is an integral part of a real-time embedded system (RTES). Most of the RTESs work on dynamic environments, and hence, the computational cost of tasks cannot be calculated in advance. Thus, RTOSs play a significant role in the smooth operations of the RTES through efficient task scheduling schemes and resource managements. This article investigates the existing design challenges and scope of the modern RTOSs. A wide variety of latest RTOSs are discussed and elaborated in detail. A comparative study with their prospects has been explained so that interested readers can use the article as a readily available starting point for their further studies on this topic.

How does manipulation of secondary task scheduling affect human performance?

2006 ◽  
Author(s):  
Patrice D. Tremoulet ◽  
Kathleen M. Stibler ◽  
Patrick Craven ◽  
Joyce Barton ◽  
Adam Gifford ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Secondary Task ◽  
Human Performance

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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