Heterogeneous

This book constitutes the refereed post-conference proceedings of the 13th International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2017, held in Dalian, China, in December 2017. The 25 revised full papers were carefully reviewed and selected from 43 submissions. The papers are organized thematically in tracks, starting with mobile and wireless networks, quality and reliability, wireless networking algorithms and protocols, and smart applications.

This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs.

This book constitutes the refereed post-conference proceedings of the 15th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2019, held in Shenzhen, China, in November 2019. The 16 revised full papers were carefully reviewed and selected from 55 submissions. The papers are organized thematically in tracks, starting with mobile systems, cloud resource management and scheduling, machine learning, telecommunication systems, and network management.

It is over 20 years since the functional data model and functional programming languages were first introduced to the computing community. Although developed by separate research communities, recent work, presented in this book, suggests there is powerful synergy in their integration. As database technology emerges as central to yet more complex and demanding applications in areas such as bioinformatics, national security, criminal investigations and advanced engineering, more sophisticated approaches like those presented here, are needed.

This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs.