scholarly journals Performance Analysis and Evaluation of Ternary Optical Computer Based on Asynchronous Multiple Vacations

2021 ◽  
Author(s):  
Wang Xianchao ◽  
Wang Xianchuan ◽  
Zhang Jie ◽  
Ling Man ◽  
Hou Dayou ◽  
...  
Keyword(s):  
System Performance ◽  
Scheduling Algorithm ◽  
Processor Allocation ◽  
Simulation Experiments ◽  
Analysis And Evaluation ◽  
Task Scheduling Algorithm ◽  
Computer Based ◽  
Optical Computer ◽  
Optical Processor ◽  
Ternary Optical Computer

Abstract Ternary optical computer(TOC) has become a research hotspot in the field because of the advantages such as inherent parallelism, numerous trits, low power consumption, extendibility, bitwise allocability and dynamical bitwise reconfigurability. Meanwhile, its performance evaluation attracts more and more attentions from potential users and researchers. To model its computing ecology more accurately, this paper first builds a three-staged TOC service model by introducing asynchronous multi-vacations and tandem queueing, and then proposes a task scheduling algorithm and an optical processor allocation algorithm with asynchronous vacations of some small optical processors after dividing equally the entire optical processor into several small optical processors which can be used independently. At the same time, the analytical model was established to obtain important performance indicators such as response time, the number of tasks and utilization of optical processor, based on M/M/1 and M/M/n queuing system with asynchronous multi-vacations. In addition, relevant numerical simulation experiments are conducted. The results illustrate that the number of small optical processors, vacation rate and the number of small optical processors allowed to be on vacation have important effects on the system performance. Compared with synchronous vacation, asynchronous vacation not only ensures the system to obtain better maintenance but also improves the system performance to some degree.

Architecture of the Monitor System in Ternary Optical Computer

2012 ◽  
Vol 616-618 ◽  
pp. 2158-2161
Author(s):  
Xian Chao Wang ◽  
Yun Fei Yao ◽  
Chun Sheng Wang ◽  
Wei Wei Sun ◽  
Kang Zhe Wang
Keyword(s):  
Embedded System ◽  
System Architecture ◽  
Monitor System ◽  
Processor Allocation ◽  
Communication Module ◽  
Optical Computer ◽  
Optical Processor ◽  
The Embedded System ◽  
Data Preprocess ◽  
Ternary Optical Computer

The monitor system architecture in ternary optical computer (TOC) was discussed. There were some important modules, such as the client, network communication module (NCM), data preprocess module (DPM), operation-request scheduling module (ORSM), optical processor allocation module (OPAM) and the embedded system in the architecture. And the communication protocols between these modules were analyzed and designed. At the same time, the functions of the modules were introduced.

Resource allocation of English intelligent learning system based on reinforcement learning

2020 ◽  
pp. 1-14
Author(s):  
Jin Jingbo
Keyword(s):  
Scheduling Algorithm ◽  
Dynamic Environment ◽  
Learning System ◽  
System Structure ◽  
Scheduling Problem ◽  
Research Gaps ◽  
System Operation ◽  
Simulation Experiments ◽  
Decision Algorithm ◽  
Task Scheduling Algorithm

The communication energy efficiency of the English intelligent learning system is affected by many factors. In order to improve the system operation efficiency, it is necessary to carry out analysis from the perspective of the mobile edge server and the system structure. However, there are still many research gaps and deficiencies. Based on a dynamic and heterogeneous English intelligent learning system, this paper designs an adaptive offloading decision algorithm ADCO and an online spring slide task scheduling algorithm SSLS. Moreover, this paper has proposed corresponding solutions to the computational offloading problem and online scheduling problem in a dynamic environment and compared and analyzed the performance of this research algorithm through simulation experiments. The research results show that the method proposed in this paper has certain effects.

Corner-Boundary Processor Allocation for 3D Mesh-Connected Multicomputers

2015 ◽  
Vol 5 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Ismail M. Ababneh ◽  
Saad Bani-Mohammad ◽  
Motasem Al Smadi
Keyword(s):  
System Performance ◽  
Allocation Strategy ◽  
Processor Allocation ◽  
Simulation Experiments ◽  
3D Mesh ◽  
Extensive Simulation ◽  
System Utilization ◽  
Free List ◽  
Simulation Results ◽  
Allocation Strategies

This research paper presents a new contiguous allocation strategy for 3D mesh-connected multicomputers. The proposed strategy maintains a list of maximal free sub-meshes and gives priority to allocating corner and boundary free sub-meshes. The goal of corner and boundary allocation is to decrease the number of leftover free sub-meshes and increase their sizes, which is expected to reduce processor fragmentation and improve overall system performance. The proposed strategy, which is referred to as Turning Corner-Boundary Free List (TCBFL) strategy, is compared, using extensive simulation experiments, to several existing allocation strategies for 3D meshes. These are the First-Fit (FF), Turning First-Fit Free List (TFFFL), and Turning Busy List (TBL) allocation strategies. The simulation results show that TCBFL produces average turnaround times and mean system utilization values that are superior to those of previous strategies.

Processor Allocation of a Ternary Optical Computer

2013 ◽  
Vol 19 (6) ◽  
pp. 1714-1717 ◽  
Author(s):  
Xianchao Wang ◽  
Yunfei Yao ◽  
Chunsheng Wang ◽  
Weiwei Sun ◽  
Kangzhe Wang
Keyword(s):  
Processor Allocation ◽  
Optical Computer ◽  
Ternary Optical Computer

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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