A Novel Dynamic Optimization Technique for Finding Optimal Trust Weights in Cloud

作     者：Prasad, Aluri V. H. Sai Rajkumar, Ganapavarapu V. S. 

作者机构：Neil Gogte Inst Technol Dept Comp Sci & Engn Hyderabad 500088 Telangana India GITAM Univ GITAM Inst Technol Dept Comp Sci & Engn Visakhapatnam 530045 Andhra Pradesh India 

出 版 物：《KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS》 (KSII Trans. Internet Inf. Syst.)

年 卷 期：2022年第16卷第6期

页      面：2060-2073页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Cloud Computing Cluster based dynamic optimization techniques Dynamic programming Evolutionary Algorithms Task scheduling Meta heuristic algorithms Trust 

摘      要：Cloud Computing permits users to access vast amounts of services of computing power in a virtualized environment. Providing secure services is essential. There are several problems to real-world optimization that are dynamic which means they tend to change over time. For these types of issues, the goal is not always to identify one optimum but to keep continuously adapting to the solution according to the change in the environment. The problem of scheduling in Cloud where new tasks keep coming over time is unique in terms of dynamic optimization problems. Until now, there has been a large majority of research made on the application of various Evolutionary Algorithms (EAs) to address the issues of dynamic optimization, with the focus on the maintenance of population diversity to ensure the flexibility for adapting to the changes in the environment. Generally, trust refers to the confidence or assurance in a set of entities that assure the security of data. In this work, a dynamic optimization technique is proposed to find an optimal trust weights in cloud during scheduling.