The question of whether an ideal network exists with global scalability in its full life cycle has always been a first-principles problem in the research of network systems and architectures.Thus far,it has not been p...The question of whether an ideal network exists with global scalability in its full life cycle has always been a first-principles problem in the research of network systems and architectures.Thus far,it has not been possible to scientifically practice the design criteria of an ideal network in a unimorphic network system,making it difficult to adapt to known services with clear application scenarios while supporting the ever-growing future services with unexpected characteristics.Here,we theoretically prove that no unimorphic network system can simultaneously meet the scalability requirement in a full cycle in three dimensions—the service-level agreement(S),multiplexity(M),and variousness(V)—which we name as the“impossible SMV triangle”dilemma.It is only by transforming the current network development paradigm that the contradiction between global scalability and a unified network infrastructure can be resolved from the perspectives of thinking,methodology,and practice norms.In this paper,we propose a theoretical framework called the polymorphic network environment(PNE),the first principle of which is to separate or decouple application network systems from the infrastructure environment and,under the given resource conditions,use core technologies such as the elementization of network baselines,the dynamic aggregation of resources,and collaborative software and hardware arrangements to generate the capability of the“network of networks.”This makes it possible to construct an ideal network system that is designed for change and capable of symbiosis and coexistence with the generative network morpha in the spatiotemporal dimensions.An environment test for principle verification shows that the generated representative application network modalities can not only coexist without mutual influence but also independently match well-defined multimedia services or custom services under the constraints of technical and economic indicators.展开更多
During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place i...During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place in 2019.One fundamental question is how we can push forward the development of mobile wireless communications while it has become an extremely complex and sophisticated system.We believe that the answer lies in the huge volumes of data produced by the network itself,and machine learning may become a key to exploit such information.In this paper,we elaborate why the conventional model-based paradigm,which has been widely proved useful in pre-5 G networks,can be less efficient or even less practical in the future 5 G and beyond mobile networks.Then,we explain how the data-driven paradigm,using state-of-the-art machine learning techniques,can become a promising solution.At last,we provide a typical use case of the data-driven paradigm,i.e.,proactive load balancing,in which online learning is utilized to adjust cell configurations in advance to avoid burst congestion caused by rapid traffic changes.展开更多
This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural prope...This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural properties of social groups matter to computer science and communications. Authors such as Moreno, John Barnes and Harrison C. White provide evidence of a growing body of literature addressing the networking of people, organizations and communities to explain the structure of society. This perspective has passed from sociology to other fields, changing understandings of social phenomena. Social networks remain a potent concept for analyzing computer science and communications. This paper shows how and why this has occurred and examines substantive areas in which social network analysis has been applied—mainly how the advantages of graphic visualization and computer software packages have influenced SNA in different audiences and publics leading to the unfolding of social networking to different audiences and publics.展开更多
基金supported by the National Key Research and Development Program of China(2022YFB2901403)the Songshan Laboratory Project(221100210900-02).
文摘The question of whether an ideal network exists with global scalability in its full life cycle has always been a first-principles problem in the research of network systems and architectures.Thus far,it has not been possible to scientifically practice the design criteria of an ideal network in a unimorphic network system,making it difficult to adapt to known services with clear application scenarios while supporting the ever-growing future services with unexpected characteristics.Here,we theoretically prove that no unimorphic network system can simultaneously meet the scalability requirement in a full cycle in three dimensions—the service-level agreement(S),multiplexity(M),and variousness(V)—which we name as the“impossible SMV triangle”dilemma.It is only by transforming the current network development paradigm that the contradiction between global scalability and a unified network infrastructure can be resolved from the perspectives of thinking,methodology,and practice norms.In this paper,we propose a theoretical framework called the polymorphic network environment(PNE),the first principle of which is to separate or decouple application network systems from the infrastructure environment and,under the given resource conditions,use core technologies such as the elementization of network baselines,the dynamic aggregation of resources,and collaborative software and hardware arrangements to generate the capability of the“network of networks.”This makes it possible to construct an ideal network system that is designed for change and capable of symbiosis and coexistence with the generative network morpha in the spatiotemporal dimensions.An environment test for principle verification shows that the generated representative application network modalities can not only coexist without mutual influence but also independently match well-defined multimedia services or custom services under the constraints of technical and economic indicators.
基金partially supported by the National Natural Science Foundation of China(61751306,61801208,61671233)the Jiangsu Science Foundation(BK20170650)+2 种基金the Postdoctoral Science Foundation of China(BX201700118,2017M621712)the Jiangsu Postdoctoral Science Foundation(1701118B)the Fundamental Research Funds for the Central Universities(021014380094)
文摘During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place in 2019.One fundamental question is how we can push forward the development of mobile wireless communications while it has become an extremely complex and sophisticated system.We believe that the answer lies in the huge volumes of data produced by the network itself,and machine learning may become a key to exploit such information.In this paper,we elaborate why the conventional model-based paradigm,which has been widely proved useful in pre-5 G networks,can be less efficient or even less practical in the future 5 G and beyond mobile networks.Then,we explain how the data-driven paradigm,using state-of-the-art machine learning techniques,can become a promising solution.At last,we provide a typical use case of the data-driven paradigm,i.e.,proactive load balancing,in which online learning is utilized to adjust cell configurations in advance to avoid burst congestion caused by rapid traffic changes.
文摘This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural properties of social groups matter to computer science and communications. Authors such as Moreno, John Barnes and Harrison C. White provide evidence of a growing body of literature addressing the networking of people, organizations and communities to explain the structure of society. This perspective has passed from sociology to other fields, changing understandings of social phenomena. Social networks remain a potent concept for analyzing computer science and communications. This paper shows how and why this has occurred and examines substantive areas in which social network analysis has been applied—mainly how the advantages of graphic visualization and computer software packages have influenced SNA in different audiences and publics leading to the unfolding of social networking to different audiences and publics.
