Collaborative Computing Cloud: Architecture and Management Platform

dc.contributor.authorKhalifa, Ahmed Abdelmonem Abuelfotooh Alien
dc.contributor.committeechairHou, Yiwei Thomasen
dc.contributor.committeechairEltoweissy, Mohamed Youssefen
dc.contributor.committeememberRiad, Sedki Mohameden
dc.contributor.committeememberSilva, Luiz A.en
dc.contributor.committeememberChen, Ing-Rayen
dc.contributor.committeememberEl-Nainay, Mustafa Yousryen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2016-09-02T06:00:24Zen
dc.date.available2016-09-02T06:00:24Zen
dc.date.issued2015-03-11en
dc.description.abstractWe are witnessing exponential growth in the number of powerful, multiply-connected, energy-rich stationary and mobile nodes, which will make available a massive pool of computing and communication resources. We claim that cloud computing can provide resilient on-demand computing, and more effective and efficient utilization of potentially infinite array of resources. Current cloud computing systems are primarily built using stationary resources. Recently, principles of cloud computing have been extended to the mobile computing domain aiming to form local clouds using mobile devices sharing their computing resources to run cloud-based services. However, current cloud computing systems by and large fail to provide true on-demand computing due to their lack of the following capabilities: 1) providing resilience and autonomous adaptation to the real-time variation of the underlying dynamic and scattered resources as they join or leave the formed cloud; 2) decoupling cloud management from resource management, and hiding the heterogeneous resource capabilities of participant nodes; and 3) ensuring reputable resource providers and preserving the privacy and security constraints of these providers while allowing multiple users to share their resources. Consequently, systems and consumers are hindered from effectively and efficiently utilizing the virtually infinite pool of computing resources. We propose a platform for mobile cloud computing that integrates: 1) a dynamic real-time resource scheduling, tracking, and forecasting mechanism; 2) an autonomous resource management system; and 3) a cloud management capability for cloud services that hides the heterogeneity, dynamicity, and geographical diversity concerns from the cloud operation. We hypothesize that this would enable 'Collaborative Computing Cloud (C3)' for on-demand computing, which is a dynamically formed cloud of stationary and/or mobile resources to provide ubiquitous computing on-demand. The C3 would support a new resource-infinite computing paradigm to expand problem solving beyond the confines of walled-in resources and services by utilizing the massive pool of computing resources, in both stationary and mobile nodes. In this dissertation, we present a C3 management platform, named PlanetCloud, for enabling both a new resource-infinite computing paradigm using cloud computing over stationary and mobile nodes, and a true ubiquitous on-demand cloud computing. This has the potential to liberate cloud users from being concerned about resource constraints and provides access to cloud anytime and anywhere. PlanetCloud synergistically manages 1) resources to include resource harvesting, forecasting and selection, and 2) cloud services concerned with resilient cloud services to include resource provider collaboration, application execution isolation from resource layer concerns, seamless load migration, fault-tolerance, the task deployment, migration, revocation, etc. Specifically, our main contributions in the context of PlanetCloud are as follows. 1. PlanetCloud Resource Management • Global Resource Positioning System (GRPS): • Global mobile and stationary resource discovery and monitoring. A novel distributed spatiotemporal resource calendaring mechanism with real-time synchronization is proposed to mitigate the effect of failures occurring due to unstable connectivity and availability in the dynamic mobile environment, as well as the poor utilization of resources. This mechanism provides a dynamic real-time scheduling and tracking of idle mobile and stationary resources. This would enhance resource discovery and status tracking to provide access to the right-sized cloud resources anytime and anywhere. • Collaborative Autonomic Resource Management System (CARMS): Efficient use of idle mobile resources. Our platform allows sharing of resources, among stationary and mobile devices, which enables cloud computing systems to offer much higher utilization, resulting in higher efficiency. CARMS provides system-managed cloud services such as configuration, adaptation and resilience through collaborative autonomic management of dynamic cloud resources and membership. This helps in eliminating the limited self and situation awareness and collaboration of the idle mobile resources. 2. PlanetCloud Cloud Management Architecture for resilient cloud operation on dynamic mobile resources to provide stable cloud in a continuously changing operational environment. This is achieved by using trustworthy fine-grained virtualization and task management layer, which isolates the running application from the underlying physical resource enabling seamless execution over heterogeneous stationary and mobile resources. This prevents the service disruption due to variable resource availability. The virtualization and task management layer comprises a set of distributed powerful nodes that collaborate autonomously with resource providers to manage the virtualized application partitions.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:4542en
dc.identifier.urihttp://hdl.handle.net/10919/72866en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCloud Computingen
dc.subjectMobile Computingen
dc.subjectCollaborative Computingen
dc.subjectOn-Demand Computingen
dc.subjectDistributed Resource Managementen
dc.subjectVirtualizationen
dc.titleCollaborative Computing Cloud: Architecture and Management Platformen
dc.typeDissertationen
thesis.degree.disciplineComputer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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