The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This...The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This is further catalysed through the need for society to make informed policies and decisions that can properly support their emerging growth.While data systems and platforms exist,they are often proprietary,being only compatible to the products that they are designed for.Given the products and services generate energy and spatial-temporal data that can often correlate,a lack of interoperability between these systems would impede decision making,as data from each system must be considered independently.By studying currently available data platforms and frameworks,this paper weighs the problems that these products address,and identifies necessary gaps for a more cohesive platform to exist.This is performed through a top-down approach,whereby broader vehicle-toeverything approaches are first studied,before moving to the components that could comprise a data platform to integrate and ingest these various data feeds.Finally,potential design considerations for a data platform is presented,along with examples of application bene.展开更多
The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance ...The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a temporal evolution network. Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal's adequacy in terms of its accuracy.展开更多
文摘The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This is further catalysed through the need for society to make informed policies and decisions that can properly support their emerging growth.While data systems and platforms exist,they are often proprietary,being only compatible to the products that they are designed for.Given the products and services generate energy and spatial-temporal data that can often correlate,a lack of interoperability between these systems would impede decision making,as data from each system must be considered independently.By studying currently available data platforms and frameworks,this paper weighs the problems that these products address,and identifies necessary gaps for a more cohesive platform to exist.This is performed through a top-down approach,whereby broader vehicle-toeverything approaches are first studied,before moving to the components that could comprise a data platform to integrate and ingest these various data feeds.Finally,potential design considerations for a data platform is presented,along with examples of application bene.
基金supported by the National Natural Science Foundation of China(Grant No.61300183)the National Science Fund for Distinguished Young Scholars in China(Grant No.61425012)
文摘The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a temporal evolution network. Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal's adequacy in terms of its accuracy.