Special Issue on Virtualization for Future Computing Systems (Future Virtualization 2019)
• 大类 : 工程技术 - 3区
• 小类 : 计算机：理论方法 - 3区
Virtualization is a widely used technology intended to enable efficient management of resources in computing systems that range from small desktops and clusters to large facilities such as Cloud data centers. This technology increases the utilization of the underlying hardware by offering multi-tenancy. Furthermore, isolation among multiple users on the same resource is also provided, which is a mechanism for effective deployment of workloads. On the other hand, virtualization is a platform to deal with heterogeneity of resources. Consequently, the virtualization technology impacts the entire computing stack-the hardware, middleware and application layers. Rapid advances in hardware acceleration, the drive towards efficiently achieving exascale computing, harnessing the use of multiple and decentralized Clouds and opportunities in decoupling physical and logical networks is paving way for significant innovation in the virtualization arena. Virtualization may be used in many other domains and for many other purposes, some of them not even thought yet.
This special issue invites authors to submit original and innovative research articles that impact any avenue of virtualization for future computing systems.
TOPICS OF INTEREST
Topics of interest include all avenues of virtualization that affects future computing systems, but are not limited to:
- Platforms: Desktops, Clouds, Supercomputers, High-Performance Computing (HPC) clusters, micro data centers; for upcoming Fog/Edge computing and Internet-of-Things platforms
- Middleware: Hypervisor support for the above; Abstraction of heterogeneous resources; Extending existing functionalities; Novel API Remoting and Hypervisor abstraction approaches in accelerator virtualization; Scheduling of virtualized resources; Multi-tenancy and its benefits
- Technologies: Virtual machines, Containers, Unikernels; Frameworks dealing with any aspect of management, such as scheduling, live migration and orchestration; Support for multi-kernel approaches; Lightweight virtualization for resource constrained environments
- Systems: Programming languages and models to support virtualization; Approaches relying on virtualization for improving reliability, energy-efficiency, latencies, resource under-utilization, resource availability, application performance and fault tolerance
- Applications: Use of virtualization for traditional workloads on any platforms indicated above; Novel workloads in deep learning, mobile apps, IoT, smart cities, etc that rely on virtualization