Exploration of in-memory computing for big data analytics using queuing theory

Assigning suitable memory chunk for Big Data analysis is posing serious problems for Business Analysts. There are plentiful solutions that came along to solve the issue of memory management. The noteworthy solutions to the problems included JVM based and Container based solutions. However, both of these solutions suffered from disk I/O bottleneck. To reduce disk, I/O bottleneck, in-memory system was introduced, which supports interactive data analytics. Present study conducts request time processing for in-memory system using three types of queue models- MG1, GM1 and GG1.