Development of a simulation-based tool suite for modeling QoS/QoE versus cost trade-offs for cloud-deployed distributed software systems and services

云计算的出现为现代公共和私营部门组织提供了机会，使其能够更好地管理与获取和操作支持其运营所需的计算资源相关的成本和效率。 尽管存在许多不同的计算云变体，从商品商业云（如Amazon EC2和Microsoft Azure）到更定制的混合云（如RackSpace提供的），再到完全定制和定制的组织持有和运营的完全私有云。服务质量（QoS）和客户感知的体验质量（QoE）水平可以根据给定组织的分布式软件系统和/或服务如何部署到哪种类型的云实例中而极大地变化。成本也有很大差异，因为需要更定制的云部署来满足所需的QoS/QoE。目前，在不进行成本高昂的、通常是迭代的、跨各种选项的试错部署的情况下，评估这些QoS/QoE与成本权衡的性质是相当困难的。 该CRD项目旨在通过开发QoS/QoE与成本云部署模拟工具套件来解决这个问题，然后组织可以使用该工具套件来经济高效地探索其各种云部署选项的可能优势和劣势，其中包括探索“假设”场景。出于技术原因，模拟器将被构建为广泛使用的OMNet++分组级网络模拟器的扩展，并设计为包括：a）云模拟模块，B）应用层分布式系统模块，c）传入工作负载流量模块，以及d）和底层云间和云内批量数据传输模块。因此，该CRD工作寻求扩展现有云仿真平台中当前提供的QoS/QoE仿真细节的丰富性，以提高其QoS/QoE预测的准确性。这将使现实世界的组织能够更全面地评估其云部署选项，特别是在由此产生的QoS/QoE与成本权衡方面。CRD是与Referral SaaSquatch Inc.合作完成的。（维多利亚，BC）。

Cloud computing's emergence offers opportunities by which modern public and private sector organizations can better manage the costs and efficiencies associated with acquiring and operating the computing resources required to support their operations. Many different variations of computing clouds though exist, spanning commodity commercial clouds, such as Amazon EC2 and Microsoft Azure, through to more tailored hybrid clouds, such as offered by RackSpace, to fully customized and tailored organizationally-held and operated fully private clouds. The quality of service (QoS) and customer-perceived quality of experience (QoE) levels can vary greatly depending on how a given organization's distributed software systems and/or services are deployed into which type of cloud instance. Costs also vary substantially as more tailored cloud deployments are required to meet the QoS/QoE that are desired. It is currently quite difficult to assessing the nature of these QoS/QoE versus cost trade-offs without engaging in costly and, typically, iterative trial-by-error deployments across the various options. This CRD project seeks to address this problem through developing a QoS/QoE versus cost cloud-deployment simulation tools suite that organizations can then use to cost-effectively explore the likely advantages and disadvantages of their various cloud deployment options, where this is inclusive of exploring "what-if" scenarios. For technical reasons, the simulator will be constructed as extensions to the widely used OMNet++ packet-level network simulator and designed to include: a) a cloud simulation module, b) an application-layer distributed system module, c) an incoming workload traffic module, and d) and an underlying inter- and intra-cloud bulk data transfer module. As such this CRD work seeks to extend the richness of QoS/QoE simulation detail currently provided in existing cloud simulation platforms in order to increase the accuracy of their QoS/QoE predictions. This will then allow real-world organizations to more informatively assess their cloud deployment options, particularly in terms of the resulting QoS/QoE versus cost trade-offs. The CRD is being done in collaboration with Referral SaaSquatch Inc. (Victoria, BC).