Optimal Provisioning and Fair Allocation of Resources in Cloud Computing Data Centers
Optimal Provisioning and Fair Allocation of Resources in Cloud Computing Data Centers
批准号:
RGPIN-2020-07158
负责人:
Lambadaris, Ioannis
金额:
$2.04万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
中文摘要
随着计算能力、磁盘存储和高端网络通信成本的大幅下降,云计算已经出现,以提供对大量资源(计算、存储、网络和软件服务)的直观、实用风格的访问。这样的处理能力是相对负担得起的并且容易获得。我们可以自信地说,云计算正在定义互联网!软件定义网络(SDN)是一种计算机网络架构,其提供用于配置原始硬件网络基础设施的灵活手段,以支持具有波动的资源需求的广泛的动态服务需求。虚拟化是SDN的核心,也是从专用和昂贵的中间盒转向软件化解决方案的关键技术。特别是,重要的网络功能(例如,防火墙、NAT、DNS缓存等)可以运行在便宜的现成中间件(例如,通用服务器级计算机主板),其中它们在虚拟机上实现;这样的网络功能被称为虚拟网络功能(VNF)。它们可以以动态的方式进行编排,数据流可以通过称为服务链(SC)的互连VNF进行处理。 网络切片是一种用于在网络中提供资源的技术,最近已应用于移动的云; SDN和网络功能虚拟化(NFV)赋予的权力产生了一种用于建立和重新配置定制的端到端逻辑网络的动态和鲁棒的方法,该端到端逻辑网络使用原始网络基础设施封装专用和共享资源。最后,用于处理和识别流量工作负载趋势的数据分析技术对于下一代敏捷和自配置云至关重要。 目前,该行业正在见证向SDN支持的云网络的重大迁移,这将影响广泛的行业,包括消费者通信/社交网络,电子商务,电子健康和物联网(IoT)应用。因此,SDN技术的影响将对全球市场的网络用户产生长期的影响。
从云获得服务需要设计者/提供商具有丰富的专业知识、经验和时间来定制和配置分配给多个(不一定位于同一地点)虚拟机/VNF的资源。由于不同类型的可用资源、高度波动的工作负载/用户需求、服务器的资源容量的异质性以及关于哪些服务器可由用户池访问的放置约束,在这样的共享计算系统中的高效且公平的资源分配和管理特别具有挑战性。拟议的研究计划的目标是调查公平和有效的资源分配/管理和动态网络切片,结合数据分析,以保持新兴的SDN使能(移动的)云架构中提供的服务质量。
英文摘要
As computation power, disk storage, and high-end network communication costs plummet, cloud computing has emerged to provide intuitive, utility-style access to vast pools of resources (compute, storage, networking, and software services). Such processing power is relatively affordable and readily available. We can confidently say that cloud computing is defining the Internet! Software Defined Networking (SDN) is a computer network architecture that offers a flexible means for configuring raw hardware networking infrastructures to support a wide range of dynamic service demands with fluctuating resource requirements. Virtualization is at the heart of SDN and is the key technology to move away from dedicated and expensive middleboxes to softwarized solutions. In particular, important network functions (e.g., firewalls, NAT, DNS cashing etc. ) can run on cheap off the shelve middleware (e.g., generic server grade computer motherboards) where they are implemented on virtual machines; such network functions are known as Virtual Network Functions(VNF). They can be orchestrated in a dynamic fashion and data flows can be processed through interconnected VNFs called Service Chains (SC). Network slicing is a technique for resource provisioning in networks that has been recently applied to the mobile cloud; empowered by SDN and network function virtualization (NFV) gives rise to a dynamic and robust approach for establishing and reconfiguring customized end-to-end logic networks that encapsulate dedicated and shared resources using raw networking infrastructure. Finally, data analytics techniques for processing and identifying trends of traffic workloads will be crucial for next generation agile and self configurable clouds. Currently the industry is witnessing a major migration towards SDN enabled cloud networking, which will impact a broad range of sectors including consumer communications/social networking, eCommerce, eHealth and Internet of Things (IoT) applications. As such, the impact of the SDN technology will have a long lasting effect on network users in the global market.
Getting services from the cloud, requires the designers/providers to have significant expertise, experience, and time to customise and configure resources that are assigned to a multitude of (not necessarily co-located) virtual machines/VNFs. Efficient and fair resource allocation and management in such a shared computing system is particularly challenging due to diverse types of available resources, highly fluctuating workload/user needs, heterogeneity in the resource capacities of servers, and placement constraints regarding which servers may be accessible by a pool of users. The goal of the proposed research program is to investigate the fair and efficient resource allocation/management and dynamic network slicing, in conjunction with data analytics for maintaining the quality of offered services in the emerging SDN enabled (mobile) cloud architectures.
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会议论文
Optimal Provisioning and Fair Allocation of Resources in Cloud Computing Data Centers
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批准号:RGPIN-2020-07158
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项目类别:Discovery Grants Program - Individual
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负责人:Lambadaris, Ioannis
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依托单位:
Optimal Provisioning and Fair Allocation of Resources in Cloud Computing Data Centers
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批准号:RGPIN-2020-07158
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项目类别:Discovery Grants Program - Individual
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资助金额:$2.04万
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