QoS-Aware Offloading Based on Communication-Computation Resource Coordination for 6G Edge Intelligence

Driven by the demands of diverse artificial intelligence(AI)-enabled application,Mobile Edge Computing(MEC)is considered one of the key technologies for 6G edge intelligence.In this paper,we consider a serial task model and design a quality of service(QoS)-aware task offloading via communication-computation resource coordination for multi-user MEC systems,which can mitigate the I/O interference brought by resource reuse among virtual machines.Then we construct the system utility measuring QoS based on application latency and user devices’energy consumption.We also propose a heuristic offloading algorithm to maximize the system utility function with the constraints of task priority and I/O interference.Simulation results demonstrate the proposed algorithm’s significant advantages in terms of task completion time,terminal energy consumption and system resource utilization.

Study on the detection methods of S&T frontier from the multi-dimensional perspective

The development of network and information technology has brought changes to the information environment.The sources of information are becoming more diverse,and intelligence acquisition will be more complicated.The intelligence reflected by different dimensions of scientific and technologi-cal(S&T)data will have their own focuses.It has become inevitable to carry out the multi-dimen-sional research of S&T frontier,which is also a current research hotspot.This paper uses quantita-tive and qualitative research methods to conduct research and analysis of S&T frontier detection from three dimensions including S&T research projects,S&T papers and patents,and proposes related re-search methods and development tools.This work analyzes the S&T frontiers in the field of artificial intelligence and draws conclusions based on the analysis results of real and effective S&T data in three dimensions.

EXPERIMENTS ON THE GROUP GENERALIZATIONG OF CONTOUR LINES FOR TOPOGRAPHIC MAPS

This paper analyzes the advantages and disadvantages of two techni-cal lines for automatic group generalization of contour lines.The author suggeststhat it is possible to get faster and better generalization results if we simulate theintelligence of human experts in program designing,retrieve geomorphologicalstructural information using the input data of 2-D contour lines and derive andoutput the generalied 2-D results directly.

Application Strategy of Big Data Processing Technology in Intelligent Transportation

With the rapid development of China’s society and economy,the process of urbanization has been accelerated,and the transportation system has become more complicated,especially the frequent occurrence of traffic accidents,traffic congestions,and environmental pollution.In the context of the rapid development of Internet technology,digital technology,artificial intelligence technology,etc.We apply them to traffic management as effective ways to improve China’s traffic operation management.Based on big data processing technology,this paper discusses its application strategy in intelligent transportation,in hope of serving as a reference.

6G-Enabled Edge AI for Metaverse:Challenges, Methods,and Future Research Directions

Sixth generation(6G)enabled edge intelligence opens up a new era of Internet of everything and makes it possible to interconnect people-devices-cloud anytime,anywhere.More and more next-generation wireless network smart service applications are changing our way of life and improving our quality of life.As the hottest new form of next-generation Internet applications,Metaverse is striving to connect billions of users and create a shared world where virtual and reality merge.However,limited by resources,computing power,and sensory devices,Metaverse is still far from realizing its full vision of immersion,materialization,and interoperability.To this end,this survey aims to realize this vision through the organic integration of 6G-enabled edge artificial intelligence(AI)and Metaverse.Specifically,we first introduce three new types of edge-Metaverse architectures that use 6G-enabled edge AI to solve resource and computing constraints in Metaverse.Then we summarize technical challenges that these architectures face in Metaverse and the existing solutions.Furthermore,we explore how the edge-Metaverse architecture technology helps Metaverse to interact and share digital data.Finally,we discuss future research directions to realize the true vision of Metaverse with 6G-enabled edge AI.

Simplified Group Search Optimizer Algorithm for Large Scale Global Optimization

A simplified group search optimizer algorithm denoted as"SGSO"for large scale global optimization is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problems.The SGSO adopts an improved sharing strategy which shares information of not only the best member but also the other good members,and uses a simpler search method instead of searching by the head angle.Furthermore,the SGSO increases the percentage of scroungers to accelerate convergence speed.Compared with genetic algorithm(GA),particle swarm optimizer(PSO)and group search optimizer(GSO),SGSO is tested on seven benchmark functions with dimensions 30,100,500 and 1 000.It can be concluded that the SGSO has a remarkably superior performance to GA,PSO and GSO for large scale global optimization.