CampusCloud: Aggregating Universities Computing Resources in Ad-Hoc Clouds Hany H Ammar 1,5 , Alaa Hamouda 2 , Mustafa Gamal 3 , Walid Abdelmoez 4 , Ahmed Moussa 5 1 The Lane Department of Computer Science and Electrical Engineering, West Virginia University, USA 2 Computer Engineering Department, Faculty of Engineering, Alazhar University, Cairo, Egypt 3 MOVE-IT Company, Cairo, Egypt 4 Arab Academy of Science and Technology, Egypt 5 Computer Science Department, Faculty of Computers and Information, Cairo University, Egypt Abstract — Cloud Computing has recently emerged as a new computing paradigm based on the concept of virtualization with the goal of creating a shared and highly scalable computing infrastructure from aggregated physical resources to deliver seamless and on-demand provisioning of software, hardware, and data as services. Universities typically have large amounts of computing resources to support instructional and research activities. This paper investigates the challenges of developing a Campus Cloud based on aggregating resources in multiple universities. The requirements model and the architecture model of this cloud environment are presented. An implementation methodology using open source cloud middleware is also discussed. Keywords- Cloud Computing; Software Engineering; Grid Computing; High Performance Computing I. INTRODUCTION Resource availability is a key factor to achieve prosperity of any society, and particularly important are computing resources, which are needed in many applications, such as e- learning, e-banking, e-business, and e-government. In particular to allow for faster economic growth, computing infrastructure is essential for small companies in their typical day-to-day business and in research and development activities. However, to attain their full potential, computing resources need to be efficiently utilized in an aggregated manner. Cloud Computing has recently emerged as a new computing paradigm. The Cloud is a type of parallel and distributed computing designed to scale and share computing resources among multiple consumers. This yields improved utilization rates, as servers are not unnecessarily left idle [1]. Deploying applications on a Cloud can help to achieve scalability and simplify/optimize IT environments. A variety of challenges arise when deploying and operating applications and services on a Cloud. Some examples of such challenges are: how to manage and guarantee service level agreements (SLAs) of services deployed in the Cloud; how to integrate services deployed on-premise and on different Clouds; how to deploy applications and business processes and monitor their runtime status, among others [2, 3]. Universities typically have large amounts of computing resources to support instructional and research activities. These are dispersed in instruction/research laboratories and administration offices in most university faculties. Moreover, the university campus has a reasonable level of computer network connectivity among almost all university buildings and to the Internet. However, these resources are underutilized; for instance, most computer labs are expectedly used only during instruction sessions, which span a small fraction of their asset time, and often are used for simple applications that consume a small fraction of their computing power. Taking into consideration that computer manufacturing technology advances in a fast pace, and today’s computers are most likely going to be replaced within three to four years, there is a dire need to make full utilization of the available computing resources before their asset time ends. Several projects were conducted in the past years to develop campus grids. One Example of a campus grid is the University of Virginia Campus Grid (UVaCG) [8]. The grid has been designed explicitly to re-use as much existing infrastructure in the campus environment as possible in creating a grid based on the Web Services Resource Framework (WSRF). Another example of a campus grid is CamGrid at Cambridge University [9]. Cam-Grid is a distributed computing resource based on the Condor middleware [9]. Yet another example of a campus grid that was also developed using the Condor middleware is Oxford University campus grid named OXGrid [10]. The design of the OxGrid system is such that registered users have seamless access to a variety of computational and data storage resources around the university. This paper investigates the challenges of developing a Campus Cloud based on aggregating resources in multiple universities. Section II discusses the requirements model while section III presents the architecture model of the campus cloud environment. The proposed system design is © ICCIT 2012 273