157,858 research outputs found
PREDICTIVE AND ADAPTIVE MAC LEARNING AS A SERVICE FOR CLOUD AND WIRELESS ENVIRONMENTS
The protocols typically used by overlay technologies, such as Ethernet Virtual Private Network (EVPN), Virtual Extensible Local Area Network (VxLAN), Network Virtualization Overlays (NVO3), etc. are not designed to perform Media Access Control (MAC) learning validation. Thus, overlay environments may be subject to Denial-of-Service (DOS attacks), MAC spoofing, and other potential attacks/issues. Presented herein are techniques to facilitate a centralized service that performs MAC learning, referred to herein as MAC Learning-as-a-Service (MLaaS), such that MAC addresses, Internet Protocol (IP) addresses, and network virtualization edge (NVE) devices can be learned for an overlay environment. Such techniques as presented herein can provide for increasing the MAC scale when compared to network devices, can facilitate providing MAC/AP address priorities in Ternary Content-Addressable Memory (TCAM) of NVE devices based on certain device groups, can facilitate efficient MAC/IP address validation via machine learning and simulated direct probing, and can prevent traffic loss during MAC movement, which can be predicted through machine learning
CyberLiveApp: a secure sharing and migration approach for live virtual desktop applications in a cloud environment
In recent years we have witnessed the rapid advent of cloud computing, in which the remote software is delivered as a service and accessed by users using a thin client over the Internet. In particular, the traditional desktop application can execute in the remote virtual machines without re-architecture providing a personal desktop experience to users through remote display technologies. However, existing cloud desktop applications mainly achieve isolation environments using virtual machines (VMs), which cannot adequately support application-oriented collaborations between multiple users and VMs. In this paper, we propose a flexible collaboration approach, named CyberLiveApp, to enable live virtual desktop applications sharing based on a cloud and virtualization infrastructure. The CyberLiveApp supports secure application sharing and on-demand migration among multiple users or equipment. To support VM desktop sharing among multiple users, a secure access mechanism is developed to distinguish view privileges allowing window operation events to be tracked to compute hidden window areas in real time. A proxy-based window filtering mechanism is also proposed to deliver desktops to different users. To support application sharing and migration between VMs, we use the presentation streaming redirection mechanism and VM cloning service. These approaches have been preliminary evaluated on an extended MetaVNC. Results of evaluations have verified that these approaches are effective and useful
Operating-system support for distributed multimedia
Multimedia applications place new demands upon processors, networks and operating systems. While some network designers, through ATM for example, have considered revolutionary approaches to supporting multimedia, the same cannot be said for operating systems designers. Most work is evolutionary in nature, attempting to identify additional features that can be added to existing systems to support multimedia. Here we describe the Pegasus project's attempt to build an integrated hardware and operating system environment from\ud
the ground up specifically targeted towards multimedia
HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges
High Performance Computing (HPC) clouds are becoming an alternative to
on-premise clusters for executing scientific applications and business
analytics services. Most research efforts in HPC cloud aim to understand the
cost-benefit of moving resource-intensive applications from on-premise
environments to public cloud platforms. Industry trends show hybrid
environments are the natural path to get the best of the on-premise and cloud
resources---steady (and sensitive) workloads can run on on-premise resources
and peak demand can leverage remote resources in a pay-as-you-go manner.
Nevertheless, there are plenty of questions to be answered in HPC cloud, which
range from how to extract the best performance of an unknown underlying
platform to what services are essential to make its usage easier. Moreover, the
discussion on the right pricing and contractual models to fit small and large
users is relevant for the sustainability of HPC clouds. This paper brings a
survey and taxonomy of efforts in HPC cloud and a vision on what we believe is
ahead of us, including a set of research challenges that, once tackled, can
help advance businesses and scientific discoveries. This becomes particularly
relevant due to the fast increasing wave of new HPC applications coming from
big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR
- ā¦