Ontology-Based Semantic Multi-agent Framework for Micro-grids with Cyber Physical Concept

The distributed hierarchical control based on multi-agent system(MAS) is the main control method of micro-grids.By allowing more flexible interactions between computing components and their physical environments,cyber physical system(CPS) presents a new approach for the distributed hierarchical engineering system,with micro-grids included.The object of this paper is to integrate the CPS concept with MAS technology and propose a new control framework for micro-grids.With the analysis of the operating mode and control method of micro-grids,the cyber physical control concepts of ontologybased semantic agent are discussed.Then an MAS-based architecture of cyber physical micro-grid system and an intelligent electronic device(IED) function structure are proposed.Finally,in order to operate and test the cyber physical micro-grid concept,an integrated simulation model is presented.

4D-MAP:Multipath Adaptive Packet Scheduling for Live Streaming over QUIC

In recent years,live streaming has become a popular application,which uses TCP as its primary transport protocol.Quick UDP Internet Connections(QUIC)protocol opens up new opportunities for live streaming.However,how to leverage QUIC to transmit live videos has not been studied yet.This paper first investigates the achievable quality of experience(QoE)of streaming live videos over TCP,QUIC,and their multipath extensions Multipath TCP(MPTCP)and Multipath QUIC(MPQUIC).We observe that MPQUIC achieves the best performance with bandwidth aggregation and transmission reliability.However,network fluctuations may cause heterogeneous paths,high path loss,and band-width degradation,resulting in significant QoE deterioration.Motivated by the above observations,we investigate the multipath packet scheduling problem in live streaming and design 4D-MAP,a multipath adaptive packet scheduling scheme over QUIC.Specifically,a linear upper confidence bound(LinUCB)-based online learning algorithm,along with four novel scheduling mechanisms,i.e.,Dispatch,Duplicate,Discard,and Decompensate,is proposed to conquer the above problems.4D-MAP has been evaluated in both controlled emulation and real-world networks to make comparison with the state-of-the-art multipath transmission schemes.Experimental results reveal that 4D-MAP outperforms others in terms of improving the QoE of live streaming.

A multipath routing algorithm for satellite networksbased on service demand and traffic awareness

With the reduction in manufacturing and launch costs of low Earth orbit satellites and the advantages of large coverage and high data transmission rates,satellites have become an important part of data transmission in air-ground networks.However,due to the factors such as geographical location and people’s living habits,the differences in user’demand for multimedia data will result in unbalanced network traffic,which may lead to network congestion and affect data transmission.In addition,in traditional satellite network transmission,the convergence of network information acquisition is slow and global network information cannot be collected in a fine-grained manner,which is not conducive to calculating optimal routes.The service quality requirements cannot be satisfied when multiple service requests are made.Based on the above,in this paper artificial intelligence technology is applied to the satellite network,and a software-defined network is used to obtain the global network information,perceive network traffic,develop comprehensive decisions online through reinforcement learning,and update the optimal routing strategy in real time.Simulation results show that the proposed reinforcement learning algorithm has good convergence performance and strong generalizability.Compared with traditional routing,the throughput is 8%higher,and the proposed method has load balancing characteristics.