Computing Power Network:A Survey

With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.

Efficient Digital Twin Placement for Blockchain-Empowered Wireless Computing Power Network

As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.

Computing Power Network:The Architecture of Convergence of Computing and Networking towards 6G Requirement

In 6G era,service forms in which computing power acts as the core will be ubiquitous in the network.At the same time,the collaboration among edge computing,cloud computing and network is needed to support edge computing service with strong demand for computing power,so as to realize the optimization of resource utilization.Based on this,the article discusses the research background,key techniques and main application scenarios of computing power network.Through the demonstration,it can be concluded that the technical solution of computing power network can effectively meet the multi-level deployment and flexible scheduling needs of the future 6G business for computing,storage and network,and adapt to the integration needs of computing power and network in various scenarios,such as user oriented,government enterprise oriented,computing power open and so on.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

Resource pre-allocation algorithms for low-energy task scheduling of cloud computing

In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the redundant, turn on the demanded＂ strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling problem to the virtual machine deployment issue with the virtualization technology. Secondly, the future workloads of system need to be predicted： a cubic exponential smoothing algorithm based on the conservative control（CESCC） strategy is proposed, combining with the current state and resource distribution of system, in order to calculate the demand of resources for the next period of task requests. Then, a multi-objective constrained optimization model of power consumption and a low-energy resource allocation algorithm based on probabilistic matching（RA-PM） are proposed. In order to reduce the power consumption further, the resource allocation algorithm based on the improved simulated annealing（RA-ISA） is designed with the improved simulated annealing algorithm. Experimental results show that the prediction and conservative control strategy make resource pre-allocation catch up with demands, and improve the efficiency of real-time response and the stability of the system. Both RA-PM and RA-ISA can activate fewer hosts, achieve better load balance among the set of high applicable hosts, maximize the utilization of resources, and greatly reduce the power consumption of cloud computing systems.

The Paradigm of Power Bounded High-Performance Computing

Modern computer systems are increasingly bounded by the available or permissible power at multiple layers from individual components to data centers.To cope with this reality,it is necessary to understand how power bounds im-pact performance,especially for systems built from high-end nodes,each consisting of multiple power hungry components.Because placing an inappropriate power bound on a node or a component can lead to severe performance loss,coordinat-ing power allocation among nodes and components is mandatory to achieve desired performance given a total power bud-get.In this article,we describe the paradigm of power bounded high-performance computing,which considers coordinated power bound assignment to be a key factor in computer system performance analysis and optimization.We apply this paradigm to the problem of power coordination across multiple layers for both CPU and GPU computing.Using several case studies,we demonstrate how the principles of balanced power coordination can be applied and adapted to the inter-play of workloads,hardware technology,and the available total power for performance improvement.

The TianHe-1A Supercomputer: Its Hardware and Software

This paper presents an overview of TianHe-lA （TH-1A） supercomputer, which is built by National University of Defense Technology of China （NUDT）. TH-1A adopts a hybrid architecture by integrating CPUs and GPUs, and its interconnect network is a proprietary high-speed communication network. The theoretical peak performance of TH-1A is 4700TFlops, and its LINPACK test result is 2566TFlops. It was ranked the No. 1 on the TOP500 List released in November, 2010. TH-1A is now deployed in National Supercomputer Center in Tianjin and provides high performance computing services. TH-1A has played an important role in many applications, such as oil exploration, weather forecast, bio-medical research.

Shaping the future of application for information and communication technology in national economic analysis

Characterized by networking,digitization,and intellectualization,the new generation of Information and Communication Technologies(ICTs)has promoted integration of various national economic industries,with a more significant leading role in the socio-economic development.In order to describe the influence of ICT industries on economic growth,this paper has comprehensively analyzed the contribution mechanism of ICTs to current economy.Crucial indicators,such as Total Telecommunications Business(TTB),Data Traffic(DT),and Computing Power Development Index(CPDI),have been innovatively selected to sufficiently describe the data circulation scale and the processing capacity in the era of digital economy.Based on relevant statistics of 31 provinces(municipalities or autonomous regions)in China from 2011 to 2020,quantitative results have been put forward to interpret the impact of ICT industries on the national economy development by using correlation coefficient analysis and data regression analysis methods.The measurement results show that TTB,DT,and CPDI are positively correlated with the national economic development,indicating that each 1%increasement of TTB,DT,and CPDI increases Gross Domestic Product(GDP)by 0.08%,0.09%,and 0.6%,respectively.