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An iterative mathematical decision model for cloud migration: A cost and security risk approach

机译:云迁移的迭代数学决策模型:成本和安全风险方法

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This paper presents an iterative mathematical decision model for organizations to evaluate whether to invest in establishing information technology (IT) infrastructure on-premises or outsourcing IT services on a multicloud environment. This is because a single cloud cannot cover all types of users' functionalonfunctional requirements, in addition to several drawbacks such as resource limitation, vendor lock-in, and prone to failure. On the other hand, multicloud brings several merits such as vendor lock-in avoidance, system fault tolerance, cost reduction, and better quality of service. The biggest challenge is in selecting an optimal web service composition in the ever increasing multicloud market in which each provider has its own pricing schemes and delivers variation in the service security level. In this regard, we embed a module in the cloud broker to log service downtime and different attacks to measure the security risk. If security tenets, namely, security service level agreement, such as availability, integrity, and confidentiality for mission-critical applications, are targeted by cybersecurity attacks, it causes disruption in business continuity, leading to financial losses or even business failure. To address this issue, our decision model extends the cost model by using the cost present value concept and the risk model by using the advanced mean failure cost concept, which are derived from the embedded module to quantify cloud competencies. Then, the cloud economic problem is transformed into a bioptimization problem, which minimizes cost and security risks simultaneously. To deal with the combinatorial problem, we extended a genetic algorithm to find a Pareto set of optimal solutions. To reach a concrete result and to illustrate the effectiveness of the decision model, we conducted different scenarios and a small-to-medium business IT development for a 5-year investment as a case study. The result of different implementation shows that multicloud is a promising and reliable solution against IT on-premises deployment.
机译:本文为组织提供了一个迭代的数学决策模型,用于评估组织是否投资在本地建立信息技术(IT)基础架构还是在多云环境下外包IT服务。这是因为单个云无法满足所有类型的用户功能/非功能需求,此外还存在资源限制,供应商锁定和易于失败等缺点。另一方面,多云带来了许多优点,例如避免供应商锁定,系统容错,降低成本和更好的服务质量。最大的挑战是在不断增长的多云市场中选择最佳的Web服务组成,在该市场中,每个提供商都有其自己的定价方案,并提供服务安全级别的变化。在这方面,我们在云代理中嵌入了一个模块来记录服务停机时间和各种攻击,以衡量安全风险。如果安全原则(即关键任务应用程序的可用性,完整性和机密性等安全服务级别协议)受到网络安全攻击的攻击,那么它将导致业务连续性中断,从而导致财务损失甚至业务失败。为了解决这个问题,我们的决策模型通过使用成本现值概念扩展了成本模型,并通过使用高级平均失效成本概念扩展了风险模型,这些均来自嵌入式模块以量化云计算能力。然后,将云经济问题转化为生物优化问题,从而同时将成本和安全风险降至最低。为了解决组合问题,我们扩展了遗传算法以找到最优解的帕累托集。为了获得具体结果并说明决策模型的有效性,我们进行了不同的方案以及为期5年的中小型企业IT开发的案例研究。不同实施的结果表明,多云是针对IT本地部署的有前途且可靠的解决方案。

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