Date of Award
Master of Science
Mobile devices such as smartphones and tablets are energy and memory limited, and implement graphical user interfaces that are intolerant of computational delays. Mobile device platforms supporting apps implemented in languages that require automatic memory man- agement, such as the Dalvik (Java) virtual machine within Google's Android, have become dominant. It is essential that automatic memory management avoid causing unacceptable interface delays while responsibly managing energy and memory resource usage. Dalvik's automatic memory management policies for heap growth and garbage collection scheduling utilize heuristics tuned to minimize memory footprint. These policies result in only marginally acceptable response times and garbage collection signicantly contributes to apps' CPU time and therefore energy consumption. The primary contributions of this research include a characterization of Dalvik's \base- line" automatic memory management policy, the development of a new \adaptive" policy, and an investigation of the performance of this policy. The investigation indicates that this adaptive policy consumes less CPU time and improves interactive performance at the cost of increasing memory footprint size by an acceptable amount.
Received from ProQuest
MD ABU JAHID
Jahid, Md Abu, "Automatic Memory Management Policies For Low Power, Memory Limited, And Delay Intolerant Devices" (2013). Open Access Theses & Dissertations. 1849.