The approach aims at runtime monitoring of container-based SOA execution environments.
In this paper, we present RTC, a runtime monitoring tool that instruments unsafe code and monitors the program execution.
A good methodology for energy prediction could have a great impact on power-aware programming, compilation, or runtime monitoring.
To develop a practical runtime monitoring system we used a power monitoring technique based on a battery monitor IC (Integrated Circuit) which is typically used in embedded systems.
A first observation that can be made is that, for most properties, the BeepBeep runtime monitor is many orders of magnitude slower than any MapReduce implementation.
We also employ runtime monitoring technique to estimate future bandwidth utilization so as to ensure budget reservation as close as to the required amount.
We implemented MCM within the Aristotle tool environment, an extensible, GCC-based architecture for instrumenting C programs for the purpose of runtime monitoring.
Unlike the other state-of-the-art techniques, the proposed methodology can be easily used to design the runtime monitoring setup without having netlist information of IP modules.
First, they extract a set of static features, and then they insert context monitoring code into a PDF document, a code that later cooperates with the runtime monitor used for the detection task.
The first tool included in our survey is a runtime monitor we developed in earlier work called BeepBeep [33].b BeepBeep receives a stream of events produced by some application or process, and constantly analyzes it against a specification given beforehand.
Therefore, we propose a runtime monitoring enforcement module (called Kernel Call Controller) which is compatible both with Android and SEAndroid and is able to enforce security policies on kernel call invocations.
