Scheduling Algorithm Design for Virtualized Hardware Accelerator in C-RAN

2016 ◽  
Author(s):  
Hui Zhu ◽  
Zhifeng Zhang ◽  
Jun Wu ◽  
Dong Guo ◽  
Shaoxian Tang
Keyword(s):  
Scheduling Algorithm ◽  
Algorithm Design ◽  
Hardware Accelerator

scholarly journals Scheduling computations with provably low synchronization overheads

2021 ◽  
Author(s):  
Guilherme Rito ◽  
Hervé Paulino
Keyword(s):  
Great Improvement ◽  
Execution Time ◽  
Path Length ◽  
State Of The Art ◽  
Critical Path ◽  
Scheduling Algorithm ◽  
Algorithm Design ◽  
Work Stealing ◽  
Maximum Cost

Abstract We present a Work Stealing scheduling algorithm that provably avoids most synchronization overheads by keeping processors’ deques entirely private by default and only exposing work when requested by thieves. This is the first paper that obtains bounds on the synchronization overheads that are (essentially) independent of the total amount of work, thus corresponding to a great improvement, in both algorithm design and theory, over state-of-the-art Work Stealing algorithms. Consider any computation with work T1 and critical-path length T1 executed by P processors using our scheduler. Our analysis shows that the expected execution time is O T1 P + T1 , and the expected synchronization overheads incurred during the execution are at most O ((CCAS + CMF ence) P T1), where CCAS and CMF ence respectively denote the maximum cost of executing a Compare-And-Swap instruction and a Memory Fence instruction.

Scheduling Algorithm Design for Enhanced Scheduling Fairness

2011 ◽  
Vol 30 (6) ◽  
pp. 1462-1465
Author(s):  
Bin-yang Xu ◽  
He-ping Pu ◽  
Shao-qian Li
Keyword(s):  
Scheduling Algorithm ◽  
Algorithm Design

scholarly journals Artificial Fuzzy-PID Gain Scheduling Algorithm Design for Motion Control in Differential Drive Mobile Robotic Platforms

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Najah Yousfi Allagui ◽  
Farhan A. Salem ◽  
Awad M. Aljuaid
Keyword(s):  
Mobile Robot ◽  
Control Algorithm ◽  
Scheduling Algorithm ◽  
Algorithm Design ◽  
System Response ◽  
System Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Differential Drive ◽  
Proportional Integral

Mobile robots are promising devices which are dedicated to human comfort in all areas. However, the control algorithm of the wheels of mobile robot is entirely challenging due to the nonlinearity. Recently, the classical PID (proportional-integral-derivative) controllers are frequently used in robotics for their high accuracy and the smooth determination of their parameters. A robust approach called fuzzy control which is based on the conversion of linguistic inference sets in a suitable control value is a widely used method in industrial system control in our days. A new challenging method to solve the problem of intelligent navigation of nonholonomic mobile robot is suggested. In this work, the presented methodology is based on three hybrid fuzzy logic PID controllers which are adapted to guarantee target achievement and trajectory tracking. A fuzzy-PID control algorithm is designed with 2 inputs and 3 outputs. By the information given by the system response, error and error derivate can be used to extract and adopt the PID controller parameters: proportional, integral, and derivative gains. Besides, a tuning value A is introduced to improve the resulted response in terms of speeding up and reducing error, overshoot, and oscillation, as well as reducing ISE and IAE values. A modelization of a differential drive mobile robot is presented. The developed algorithm is tested and implemented to this mobile robot model via Simulink/MATLAB.

scholarly journals ANALYSIS OF THE INFLUENCE OF BIOCHEMICAL INDEXES OF ATHLETES UNDER TRAINING BASED ON THE INTERNET OF THINGS AND CLOUD COMPUTING

2021 ◽  
Vol 27 (spe2) ◽  
pp. 27-30
Author(s):  
Weidong Yang ◽  
Huan Huang
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Scheduling Algorithm ◽  
Algorithm Design ◽  
Computing Methods ◽  
The Internet ◽  
Communication Model ◽  
Computing Technology ◽  
Optimal Value ◽  
The Internet Of Things

ABSTRACT For athletes under training, it is more efficient to use the Internet of Things (IoT) and cloud computing methods to collect and process biochemical indicators, and this study is about research based on the IoT and cloud computing technology for athletes under training. The problems are put forward in this study. The requirements of related algorithm design and the communication model properties are comprehensively analyzed. Scheduling the link and allocating the transmit power of the nodes are comprehensively considered, with design and analysis of wireless sensor network scheduling algorithm. The factors influencing the scheduling efficiency of the algorithm are analyzed, considering the node density and the influence of different power allocation schemes on the scheduling result. This study shows that the algorithm of this thesis can collect the biochemical index data of athletes during training period. As the number of nodes increases, the running results will gradually move towards the optimal value. This research study is of important theoretical significance for the application of IoT and cloud computing technology and the improvement of athlete training effect.

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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