Title
Light-weight kernel instrumentation framework using dynamic binary translation
Abstract
Mobile platforms such as Android and iOS, which are based on typical operating systems, have been widely adopted in various computing devices from smart phones even to smart TVs. Along with this, the necessity of kernel instrumentation framework has also grown up for efficient development and debugging of a kernel itself and its components. Although the existing approaches are providing some information about the kernel state including physical register value and primitive memory map, it is hard for the developers to understand and exploit the information. Moreover, the excessive analysis overhead in the existing approach makes them impractical to be used in real systems. Meanwhile, there have been a few studies on analyzing the user-level applications using dynamic binary translation and they are now widely used. In this paper, by extending this idea of dynamic binary translation for user-level applications to the kernel, we propose a new dynamic kernel instrumentation framework. Our framework focuses on the modules such as device drivers, rather than the kernel itself, since the modules comprise a large portion of OS development. Because of the frequent execution of kernel modules, the dynamic kernel instrumentation framework should guarantee the quality of the translated target code. However, costly optimizations to achieve high execution performance are rather harmful to the overall performance. Therefore, in order to improve performance of both translations, we suggest light-weight translator based on pseudo-machine instruction representation and tabular-base translation instead of typical intermediate representation. We implement our framework on Linux system, and our experimental evaluations show that it could quite effectively instrument the target with nominal overhead.
Year
DOI
Venue
2013
10.1007/s11227-013-0954-3
The Journal of Supercomputing
Keywords
Field
DocType
high execution performance,user-level application,new dynamic kernel instrumentation,dynamic kernel instrumentation framework,light-weight kernel instrumentation framework,existing approach,dynamic binary translation,kernel module,kernel state,overall performance,kernel instrumentation framework
Kernel (linear algebra),Android (operating system),sysfs,Computer science,Parallel computing,Exploit,Binary translation,Kernel preemption,Memory map,Debugging,Distributed computing
Journal
Volume
Issue
ISSN
66
3
1573-0484
Citations 
PageRank 
References 
1
0.37
13
Authors
7
Name
Order
Citations
PageRank
Dongwoo Lee1244.91
Inhyuk Kim2114.33
Jeehong Kim353.20
Hyung Kook Jun431.76
Won Tae Kim56112.27
Sang-Won Lee61536106.03
Young Ik Eom731658.40