Memory allocation algorithm for cloud services

Memory allocation has a major influence on multiuser systems, cloud-based services, virtual machines, and other computer systems. Memory allocation is a process that assigns physical or virtual memory space to programs and services as efficiently and quickly as possible. Economical memory allocation management needs allocation strategies with minimum wastage. In this paper, we introduce a new memory allocation algorithm based on sequential fits and zoning for on-demand (online) cloud services. The memory is divided into multiple zones, where a subgroup of relative request sizes compete in reverse order. We use simulation to compare our new mechanism with existing memory allocation methods that have been deployed using Amazon Elastic Compute Cloud as a test bed. The proposed algorithm is more efficient, and the average saving for the normalized revenue loss is about 7% better than best-fit and 15% better than first-fit memory allocation. In addition, we show that proposed algorithm is robust and faster and has a fairness index that is superior to that of existing techniques.