A Network Scheduling Strategy of Android-Based Virtual Reality System

Mobile platform develops rapidly in recent years, with its performance and capacity increasing. A large number of virtual reality applications such as 3D simulation and visualization have appeared on mobile platform. However, due to restrictions, such as the lack of computing resources and the limited network bandwidth, the virtual reality systems on mobile platform could not have comparable performance as their peers on desktop platform. Taking resource restrictions into consideration, trade-offs have been made regarding the display of virtual reality systems. We propose a unified network scheduling strategy based on asynchronous multi-thread, database cache, prioritization and elimination of overdue requests. This strategy has been tested on the prototype system of virtual reality system on Android. The results demonstrate higher network resource utilization and better user experience.

Reliable Scheduling Method for Sensitive Power Business Based on Deep Reinforcement Learning

The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.

Strategy of constructing virtual peaking unit by public buildings’central air conditioning loads for day-ahead power dispatching

With the gradually widely usage of the air conditioning(AC) loads in developing countries, the urban power grid load has swiftly increased over the past decade.Especially in China, the AC load has accounted for over30% of the maximum load in many cities during summer.This paper proposes a scheme of constructing a virtual peaking unit(VPU) by public buildings’ cool storage central AC(CSCAC) systems and non-CSCAC(NCSCAC)systems for the day-ahead power network dispatching(DAPND). Considering the accumulation effect of different meteorological parameters, a short term load forecasting method of public building’s central AC(CAC) baseline load is firstly discussed. Then, a second-order equivalent thermal parameters model is established for the public building’s CAC load. Moreover, the novel load reduction control strategies for the public building’s CSCAC system and the public building’s NCSCAC system are respectively presented. Furthermore, based on the multiple-rank control strategy, the model of the DAPND with the participation of a VPU is set up. The VPU is composed of large-scale regulated public building’s CAC loads. To demonstrate the effectiveness of the proposed strategy, results of a sample study on a region in Nanjing which involves 22 public buildings’ CAC loads are described in this paper. Simulated results show that, by adopting the proposed DAPND scheme, the power network peak load in the region obviously decreases with a small enough deviation between the regulated load value and the dispatching instruction of the VPU. The total electricity-saving amount accounts for7.78% of total electricity consumption of the VPU before regulation.