Information collection centric techniques for cloud resource management: Taxonomy, analysis and challenges

Abstract

The emergence of cloud computing has gained massive attention for both industry and academia. Resource management in cloud computing is a challenging task due to the complex nature of user requirements and fluctuating workloads. The current research has primarily focused on scheduling algorithms, load balancing, and efficient resource sharing in computational clouds, however; classifying state information collection strategies have largely been neglected. This paper presents a survey of Information Collection Centric Techniques (ICCT) for cloud resource management. The paper contributes by providing a thematic taxonomy of the current state-of-the-art techniques to present a comprehensive classification of the state information collection mechanisms. Moreover, a thorough comparative analysis based on various parameters of the state-of-the-art ICCT have been carried out to highlight their merits and demerits. Finally, the paper concludes by presenting recommendations, issues and open research challenges that should be considered while proposing and designing novel resource management techniques.