Dynamic adjustment of execution order in real-time databases

Author(s):  
Yongyan Wang ◽  
Qiang Wang ◽  
Hongan Wang ◽  
Guozhong Dai
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Bo Hu ◽  
Xin Liu ◽  
Jinghong Zhao ◽  
Siya Xu ◽  
Zhenjiang Lei ◽  
...  

With the development of the energy Internet, power communication services are heterogeneous, and different power communication services have different business priorities. The power communication services with different priorities have different requirements for network bandwidth and real-time performance. For traditional unified service, a scheduling method cannot meet these service requirements at the same time, and electric power communication network cannot guarantee the quality of service. Therefore, how to make full use of the time-varying characteristics of communication resources to meet the business needs of different priorities and achieve the goals of high resource utilization and transmission quality has become one of the urgent problems in the power communication network. For this reason, in order to adapt to the real-time congestion of the network, we have designed a packet scheduling method based on the dynamic adjustment of service priority, which dynamically adjusts the priority of the power service on the node; in addition, an evaluation method for the trust value of wireless forwarding nodes is introduced to improve the security of data transmission; and finally, we valuate the channel quality to establish a reasonable and efficient packet scheduling mechanism for services of different priorities. Simulation results show that this method improves the communication performance of high-priority services and improves the spectrum resource utilization of the entire system.


Author(s):  
Myungryun Yoo ◽  
Takanori Yokoyama

Purpose of the study:The real-time task scheduling on multiprocessor system is known as an NP-hard problem. This paper proposes a new real-time task scheduling algorithmwhich considers the communication time between processors and the execution order between tasks. Methodology:Genetic Algorithm (GA)with Adaptive Weight Approach (AWA) is used in our approach. Main Findings:Our approach has two objectives. The first objective is to minimize the total amount of deadline-miss. And the second objective is to minimize the total number of processors used. Applications of this study:For two objectives,the range of each objective is readjusted through Adaptive Weight Approach (AWA) and more useful result is obtained. Novelty/Originality of this study:This study never been done before.This study also wasprovided current information about scheduling algorithm and heuristics algorithm.


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