Department of Information & Technology, Dr. NGP Institute of Technology, Coimbatore, India.
Department of Computer Science & Engineering, Coimbatore Institute of Technology, Coimbatore, India.
J Med Syst. 2019 Jan 8;43(2):37. doi: 10.1007/s10916-018-1155-7.
With the development of Internet and the make use of Internet for medical information, the demand for huge scale and reliable managing medical information has brought out the huge scale Internet data centers. This work that has been presented here highlights the structural lay out and formulation of the medical information model. The aim of presenting this to aid medical departments as well as workers to exchange information and integrate available resources that help facilitate the analysis to be conducted on the given information. Software here comprises of medical information and offers a comprehensive service structure that benefits medical data centers. VNM or Virtual Network Mapping (VNM) essentially relates to substrate network that involves the installation and structuring of on demand virtual machines. These however are subjective to certain limitations that are applicable in relation to latency, capacity as well as bandwidth. Data centers need to dynamically handle cloud workloads effectively and efficiently. Simultaneously, since the mapping of virtual and physical networks with several providers' consumes more time along with energy. In order to resolve this issue, VNM has been mapped by making use of Graph Theory (GT) matching, a well-studied database topic. (i) Brain Storm Optimization Graph Theory (BSOGT) is introduced for modeling a virtual network request in the form of a GT with different resource constraints, and the substrate networks here is considered being a graph. For this graph the nodes and edges comprise of attributes that indicate their constraints. (ii) The algorithm that has been recently introduced executes graph decomposition into several topology patterns. Thereafter the BSOGT is executed to solve any issues that pertain to mapping. (iii) The model that has been presented here, ERVNM and the BSOGT are used with a specific mapping energy computation function.(iv) Issues pertaining to these are categorized as being those related to virtual network mapping as the ACGT and optimal solution are drawn by using effective integer linear programming. ACGT, pragmatic approach, as well as the precise and two-stage algorithms performance is evaluated by means of cloud Simulator environment. The results obtained from simulation indicate that the BSOGT algorithm attains the objectives of cloud service providers with respect to Acceptance ratio, mapping percentage, processing time as well as Convergence Time.
随着互联网的发展和对医疗信息的利用，对大规模可靠管理医疗信息的需求催生了大规模互联网数据中心。这里介绍的工作重点介绍了医疗信息模型的结构布局和制定。提出这一目标是为了帮助医疗部门和工作人员交换信息并整合可用资源，从而促进对给定信息的分析。该软件包含医疗信息，并提供全面的服务结构，使医疗数据中心受益。虚拟网络映射（VNM）本质上涉及到涉及按需虚拟机安装和结构的基础网络。然而，这些虚拟机受到与延迟、容量和带宽相关的某些限制。数据中心需要有效地、高效地动态处理云工作负载。同时，由于与多个提供商的虚拟和物理网络的映射会消耗更多的时间和能源。为了解决这个问题，VNM 已经通过利用图论（GT）匹配来映射，这是一个经过充分研究的数据库主题。（i）引入了头脑风暴优化图论（BSOGT）来对虚拟网络请求进行建模，采用不同资源约束的 GT 形式，基础网络被视为图。对于该图，节点和边包含表示其约束的属性。（ii）最近引入的算法将图分解为几个拓扑模式。然后执行 BSOGT 以解决与映射相关的任何问题。（iii）提出的模型，ERVNM 和 BSOGT 与特定的映射能量计算函数一起使用。（iv）与这些相关的问题被归类为与虚拟网络映射相关的问题，因为 ACGT 和最佳解决方案是通过使用有效的整数线性规划来绘制的。ACGT、实用方法以及精确和两阶段算法的性能是通过云模拟器环境来评估的。模拟结果表明，BSOGT 算法在接受率、映射百分比、处理时间和收敛时间方面实现了云服务提供商的目标。
