Currently, with the booming growth of cloud computing, workloads from broad ranges of functions and demands are crammed into a single physical machine. They lay considerable stress on the need of evolution of the operating system underneath, especially the memory subsystem. Even enhancing large pages with main memory compression is not intuitively straightforward due to rigid rules imposed by the state-of-the-art manager Buddy System from the beginning of the design. To relieve the aforementioned problems and provide broader design space for system designers, we propose Zweilous, a clean slate physical memory management framework. It is self-contained, highly decoupled, and thus can co-exist with the vanilla memory manager. Separate self-contained metadata/functions guarantee a flexible extension with little modification to current frameworks. To show it is easy to add enhanced functions that accelerate the evolution of the memory management subsystem, we implement Hzmem, a new large page memory manager redesign enhanced with the function of main memory compression. Our method achieves competitive performance compared with native and virtualized large page support, effective memory size increased and fewer impacts on other parts of the operating system.

Mobile virtualization has emerged fairly recently and is considered a valuable way to mitigate security risks on Android devices. However, major challenges in mobile virtualization include runtime, hardware, resource overhead, and compatibility. In this paper, we propose a lightweight Android virtualization solution named Condroid, which is based on container technology. Condroid utilizes resource isolation based on namespaces feature and resource control based on cgroups feature. By leveraging them, Condroid can host multiple independent Android virtual machines on a single kernel to support mutilple Android containers. Furthermore, our implementation presents both a system service sharing mechanism to reduce memory utilization and a filesystem sharing mechanism to reduce storage usage. The evaluation results on Google Nexus 5 demonstrate that Condroid is feasible in terms of runtime, hardware resource overhead, and compatibility. Therefore, we find that Condroid has a higher performance than other virtualization solutions.

A new traffic signal control system (TSCS) evaluation method that uses computational experiments based on artificial transportation systems (ATSs) is proposed in this paper. Some basic ideas of the method are discussed, i.e., generating reasonable travel demand, modeling the influence of environment, and designing communication interface. Using a 30-day computational experiment on ATSs, a case study is carried out to evaluate three TSCSs, which are implemented using fixed-time (FT), queue-based responsive (QBR), and adaptive dynamic program (ADP) algorithms, respectively. Aside from normal weather, three types of adverse weather, i.e., rain, wind, and fog, are modeled in the computational experiment. After analyzing aggregate data and detailed operating record, reliable evaluation results are obtained from this case study. Furthermore, several interesting phenomena are observed in this case study, which have yet to be noticed by previous work.