A Task Scheduling Method for Edge Computing in Intelligent Building System

Author(s):  
Lingzhi Yi ◽  
Xiaodong Feng ◽  
Xieyi Gao ◽  
Lv Fan ◽  
Huina Song ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Lei Fang

At present, the fast-paced work and life make people under great pressure, and people’s enthusiasm for fitness is getting higher and higher, which is in contradiction with the shortage of existing stadiums. So it is considerably significant to open shared stadiums near where citizens live for booking. Therefore, how to allow citizens to book a suitable stadium according to their own needs through mobile phones or computers is an urgent problem to be solved. The booking of the shared stadium can be regarded as a mobile edge computing (MEC) scenario, and the problem can be transformed into task scheduling research under MEC through intelligent scheduling method. When using edge computing (EC) technology for service calculation, the mobile terminal needs to offload the service to the edge computing server. After the server completes the calculation, the calculation results will be sent back to the mobile terminal. Therefore, the calculation time and system energy consumption in the calculation process can be further reduced through task scheduling to improve user satisfaction. In this study, joint scheduling of service caching and task algorithm is proposed to reduce the latency of booking shared stadium request and improve user experience. The simulation results show that the proposed algorithm with edge cooperation idea can achieve lower average system latency at lower load level and can significantly reduce the cloud offloading ratio under low and middle pressure. In addition, the proposed algorithm uses the secondary transfer of more tasks to reduce the pressure of local task running. Finally, the quality of experience (QoE) satisfaction rate under low pressure is guaranteed.


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 955
Author(s):  
Zhiyuan Li ◽  
Ershuai Peng

With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.


IEEE Network ◽  
2021 ◽  
Vol 35 (3) ◽  
pp. 102-108
Author(s):  
Laisen Nie ◽  
Xiaojie Wang ◽  
Wentao Sun ◽  
Yongkang Li ◽  
Shengtao Li ◽  
...  

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 5609-5622 ◽  
Author(s):  
Li Tianze ◽  
Wu Muqing ◽  
Zhao Min ◽  
Liao Wenxing

2019 ◽  
Vol 12 ◽  
pp. 232-239
Author(s):  
Cezary Kryczka

This article is an attempt to answer the question whether and under what conditions it is beneficial to develop an own intelligent building system, when many free open source systems are available. The publication presents the characteristics of author's own home automation system - sHome, as well as the open-source system - Domoticz, in a configuration that is as close to the functionality of the author's system as possible. The work ends with a comparative analysis of the systems and conclusions from the analysis.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 65085-65095
Author(s):  
Ming Yang ◽  
Hao Ma ◽  
Shuang Wei ◽  
You Zeng ◽  
Yefeng Chen ◽  
...  

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