High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

Designing a VM-level vertical scalability service in current cloud platforms: A new hope for wearable computers

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Public clouds are becoming ripe for enterprise adoption. Many companies, including large enterprises, are increasingly relying on public clouds as a substitute for, or a supplement to, their own computing infrastructures. On the other hand, cloud storage service has attracted over 625 million users. However, apart from the storage service, other cloud services, such as the computing service, have not yet attracted the end users’ interest for economic and technical reasons. Cloud service providers offers horizontal scalability to make their services scalable and economical for enterprises while it is still not economical for the individual users to use their computing services due to the lack of vertical scalability. Moreover, current virtualization technologies and operating systems, specifically the guest operating systems installed on virtual machines, do not support the concept of vertical scalability. In addition, network remote access protocols are meant to administer remote machines but they are unable to run the non-administrative tasks such as playing heavy games and watching high quality videos remotely in a way that makes the users feel as if they are sitting locally on their personal machines. On the other hand, the industry is yet unable to make efficient wearable computers a reality due to the limited size of the wearable devices, where it is infeasible to place efficient processors and big enough hard disks. This paper aims to highlight the need for the vertical scalability service and design the appropriate cloud, virtualization layer, and operating system services to incorporate vertical scalability in current cloud platforms in a way that will make it economically and technically efficient for the end users to use cloud virtual machines as if they are using their personal laptops. Through these services, the cloud takes wearable computing to the next stage and makes wearable computers a reality

Desktop Sharing Portal

Desktop sharing technologies have existed since the late 80s. It is often used in scenarios where collaborative computing is beneficial to participants in the shared environment by the control of the more knowledgeable party. But the steps required in establishing a session is often cumbersome to many. Selection of a sharing method, obtaining sharing target’s network address, sharing tool’s desired ports, and firewall issues are major hurdles for a typical non-IT user. In this project, I have constructed a web-portal that helps collaborators to easily locate each other and initialize sharing sessions. The portal that I developed enables collaborated sessions to start as easily as browsing to a URL of the sharing service provider, with no need to download or follow installation instructions on either party’s end. In addition, I have added video conferencing and audio streaming capability to bring better collaborative and multimedia experience

Online Virtual Network Provisioning in Distributed Cloud Computing Data Centers

Efficient virtualization methodologies constitute the core of cloud computing data center implementation. Clients are attracted to the cloud model by the ability to scale available resources dynamically and the flexibility in payment options. However, performance hiccups can push them to return to the buy-and-maintain model. Virtualization plays a key role in the synchronous management of the thousands of servers along with clients\u27 data residing on them. To achieve seamless virtualization, cloud providers require a system that performs the function of virtual network mapping. This includes receiving the cloud client requests and allocating computational and network resources in a way that guarantees the quality of service conditions for clients while maximizing the data center resource utilization and providers\u27 revenue. In this thesis, we introduce a comprehensive system to solve the problem of virtual network mapping for a set of connection requests sent by cloud clients. Connections are collected in time intervals called windows. Subsequently, node mapping and link mapping are performed. Different window size selection schemes are introduced and evaluated. Three schemes to prioritize connections are used and their effect is assessed. Moreover, a technique dealing with connections spanning over more than a window is introduced. Simulation results show that the dynamic window size algorithm achieves cloud service providers objectives in terms of generated revenue, served connections ratio, resource utilization and computational overhead. In addition, experimental results show that handling spanning connections independently improves the results for the performance metrics measured. Moreover, in a cloud infrastructure, handling all resources efficiently in their usage, management and energy consumption is challenging. We propose an energy efficient technique for embedding online virtual network requests in cloud data centers. The core focus of this study is to manage energy efficiently in cloud environment. A fixed windowing technique with spanning connections is used. Our algorithm, and a technique for randomly embedding nodes and links are also explained. The results clearly show that the algorithm used in this study generated better results in terms of energy consumption, served connections and revenue generation