Infrastructure as a service (IaaS) has attracted significant attention from cloud research communities. While compute and storage resource management has been developed and studied to a greater extent, the use of netw...
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ISBN:
(纸本)9781509026197
Infrastructure as a service (IaaS) has attracted significant attention from cloud research communities. While compute and storage resource management has been developed and studied to a greater extent, the use of network resource management in the context of IaaS is still in its early stages. There is a need for a comprehensive virtualization framework capable of providing users with low-level network and compute resource control while improving underlying resource utilization. We propose a software-definednetworking (SDN) IaaS framework that explicitly integrates network virtualization, including computing and storage, into a cloud platform. Our proposed framework abstracts data-center compute and network resources into a virtualized pool of resources, links them to logically compose virtual networks, and performs automated configurations to serve IaaS requests from users. We designed and constructed an SDN test-bed to verify the operation of the proposed framework. We successfully demonstrated our system's ability to meet our design objectives: (i) providing high degree of control over connectivity and Quality of Service (QoS), (ii) fully automated service delivery, (iii) fast and low overhead resource provisioning. We evaluated the feasibility and scalability of the proposed framework using statistics gathered from its deployment.
Mobile Cloud Computing enables resource limited mobile devices to support rich application services. Among three types of cloud services, Infrastructure-as-a-Service (IaaS) clouds provides compute infrastructure for m...
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ISBN:
(纸本)9781509061969
Mobile Cloud Computing enables resource limited mobile devices to support rich application services. Among three types of cloud services, Infrastructure-as-a-Service (IaaS) clouds provides compute infrastructure for mobile applications on demand. In IaaS-based mobile clouds, latency and bandwidth requirements can considered as critical factors impacting Quality of Service (QoS). Opposed to centralized clouds, geographically distributed clouds realize higher QoS benefiting the proximity to the end user. In this paper, we propose an IaaS framework with regional datacenters for mobile clouds. With the benefits of software-definednetworking (SDN), we address impacts on QoS during mobility by serving mobile user via the optimum datacenter. A test-bed was developed to measure the performance of service allocation and relocation in proposed framework.
The threat landscape is changing significantly;complexity and rate of attacks is ever increasing, and the network defender does not have enough resources (people, technology, intelligence, context) to make informed de...
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ISBN:
(纸本)9781509007707
The threat landscape is changing significantly;complexity and rate of attacks is ever increasing, and the network defender does not have enough resources (people, technology, intelligence, context) to make informed decisions. The need for network defenders to develop and create proactive threat intelligence is on the rise. Network deception may provide analysts the ability to collect raw intelligence about threat actors as they reveal their Tools, Tactics and Procedures (TTP). This increased understanding of the latest cyber-attacks would enable cyber defenders to better support and defend the network, thereby increasing the cost to the adversary by making it more difficult to successfully attack an enterprise. Using a deception framework, we have created a live, unpredictable, and adaptable Deception Environment leveraging virtualization/cloud technology, softwaredefinednetworking, introspection and analytics. The environment not only provides the means to identify and contain the threat, but also facilitates the ability to study, understand, and develop protections against sophisticated adversaries. By leveraging actionable data, in real-time or after a sustained engagement, the Deception Environment may be easily modified to interact with and change the perception of the adversary on-the-fly. This ability to change what and where the attacker is on the network, as well as change and modify the content of the adversary on exfiltration and infiltration, is the defining novelty of our Deception Environment.
Cloud Infrastructure-as-a-Service (IaaS) is a form of utility computing which has emerged with the recent innovations in the service computing and data communication technolo- gies. Regardless of the fact that IaaS is...
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Cloud Infrastructure-as-a-Service (IaaS) is a form of utility computing which has emerged with the recent innovations in the service computing and data communication technolo- gies. Regardless of the fact that IaaS is attractive for application service providers, satisfying user requests while ensuring cloud operational objectives is a complicated task that raises several resource management challenges. Among these challenges, limited controllability over network services delivered to cloud consumers is prominent in single datacenter cloud environments. In addition, the lack of seamless service migration and optimization, poor infrastructure utilization, and unavailability of efficient fault tolerant techniques are noteworthy challenges in geographically distributed datacenter clouds. Initially in this thesis, a datacenter resource management framework is presented to address the challenge of limited controllability over cloud network traffic. The proposed framework integrates network virtualization functionalities offered by softwaredefinednetworking (SDN) into cloud ecosystem. To provide rich traffic control features to IaaS consumers, control plane virtualization capabilities offered by SDN have been employed. Secondly, a quality of service (QoS) aware seamless service migration and optimization framework has been proposed in the context of geo-distributed datacenters. Focus has been given to a mobile end-user scenario where frequent cloud service migrations are required to mitigate QoS violations. Finally, an SDN-based dynamic fault restoration scheme and a shared backup-based fault protection scheme have been proposed. The fault restoration has been achieved by introducing QoS-aware reactive and shared risk link group-aware proactive path computation algorithms. Shared backup protection has been achieved by optimizing virtual and backup link embedding through a novel integer linear programming approach. The proposed solutions significantly improve bandwidth u
Infrastructure as a service (IaaS) has attracted significant attention from cloud research communities. While compute and storage resource management has been developed and studied to a greater extent, the use of netw...
详细信息
Infrastructure as a service (IaaS) has attracted significant attention from cloud research communities. While compute and storage resource management has been developed and studied to a greater extent, the use of network resource management in the context of IaaS is still in its early stages. There is a need for a comprehensive virtualization framework capable of providing users with low-level network and compute resource control while improving underlying resource utilization. We propose a software-definednetworking (SDN) IaaS framework that explicitly integrates network virtualization, including computing and storage, into a cloud platform. Our proposed framework abstracts data-center compute and network resources into a virtualized pool of resources, links them to logically compose virtual networks, and performs automated configurations to serve IaaS requests from users. We designed and constructed an SDN test-bed to verify the operation of the proposed framework. We successfully demonstrated our system's ability to meet our design objectives: (i) providing high degree of control over connectivity and Quality of Service (QoS), (ii) fully automated service delivery, (iii) fast and low overhead resource provisioning. We evaluated the feasibility and scalability of the proposed framework using statistics gathered from its deployment.
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