Improving Android Memory Utilization using Markov Decision Processes

• Main Authors: Bo-Shiung Chi, 紀柏雄
• Other Authors: Cheng-Zen Yang
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/53362084059398863127

碩士 === 元智大學 === 資訊工程學系 === 99 === In Android, resource management has significant impacts on system performance. Especially, memory management is the most crucial. According to our observations, current memory management in Android is based on the Least Recently Used (LRU) algorithm to claim for more free memory space. In addition, it uses a Garbage Collection (GC) mechanism to perform memory recycling. If numerous applications are executed in the limited memory space, currently Android may suffer from the lengthened loading problem. Therefore, in this research we propose a predictive memory management scheme using the Markov Decision Processes (MDP) model to improve the memory utilization. The proposed scheme has two following contributions: (1) the MDP-based memory management can efficiently improve the memory utilization in Android, and (2) it can effectively reduce the loading time while many applications are executed.