Efficient Data Gathering in Cloud Computing Using Clustering Schemes, Cloud Agent-Based Data Schemes and Efficient Path Planning Techniques

Abstract

Cloud computing is a rapidly evolving field with a wide range of applications, including data storage, processing, and analysis. Clustering schemes, cloud agent-based data schemes, and efficient path planning techniques are all important aspects of cloud computing. Clustering schemes are used to group similar data items together, which can improve the efficiency of data processing and analysis. Cloud agent-based data schemes allow for the collection and management of data from a variety of sources, including cloud and edge devices. Efficient path planning techniques are used to optimize the routing of data packets in cloud networks. This research paper provides a comprehensive overview of clustering schemes, cloud agent-based data schemes, and efficient path planning techniques for cloud computing. The paper discusses the different types of clustering schemes and cloud agent-based data schemes, as well as their advantages and disadvantages. The paper also presents an overview of efficient path planning techniques for cloud computing. The paper concludes by discussing the challenges and future research directions in cloud computing. The authors believe that cloud computing is a rapidly evolving field with a bright future, and they encourage researchers to continue to develop new and innovative solutions for cloud computing.