W. Chen

QoS-aware virtual machine scheduling for video streaming services in multi-cloud

Video streaming services are trending to be deployed on cloud. Cloud computing offers better stability and lower price than traditional IT facilities. Huge storage capacity is essential for video streaming service. More and more cloud providers appear so there are increasing cloud platforms to choose. A better choice is to use more than one data center, which is called multi-cloud. In this paper a closed-loop approach is proposed for optimizing Quality of Service (QoS) and cost. Modules of monitoring and controlling data centers are required as well as the application feedback such as video streaming services. An algorithm is proposed to help choose cloud providers and data centers in a multi-cloud environment as a video service manager. Performance with different video service workloads are evaluated. Compared with using only one cloud provider, dynamically deploying services in multi- cloud is better in aspects of both cost and QoS. If cloud service costs are different among data centers, the algorithm will help make choices to lower the cost and keep a high QoS.

Customized Virtual Machines for Software Provisioning in Scientific Clouds

Scientific applications require special data computing and analysis software, which may not mature enough at a production level. Software provisioning, especially in a cloud computing environment, bring new challenges. In this work, software package management systems are summarized. A customized software provisioning service is developed using virtualization technology. According to users requirements, virtual machines with required software deployed ready-for-use can be obtained in a very straightforward way. This work is being applied in the LIGO (Laser Interferometer Gravitational-wave Observatory) Scientific Collaboration for gravitational-wave data analysis. With software virtual machines available, scientific applications can benefit from cloud computing technology and resources.

Enabling Distributed Computing Systems with ElopTM

In the era of Internet, one of the most ultimate goals is that users can seamlessly access to any computing application or service at anywhere anytime. Computing infrastructuralization is the path to gradually address the challenge. In this work, elop computing is proposed that encapsulates and integrates various computing elements as services, benefiting from existing advanced computing technology, e.g. virtualization and SaaS. Higher levels of services are also provided, e.g. metadata management, resource management and scheduling, security and authorization, which can be utilized to build distributed computing systems in a scalable way. In this paper, the architecture of elop computing is illustrated and corresponding middleware implementation is introduced in details. A typical scenario is given to demonstrate the potential of enabling distributed computing systems with elopTM.