Hyung Kook Jun

Light-weight kernel instrumentation framework using dynamic binary translation

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.

A Fast Lock-Free User Memory Space Allocator for Embedded Systems

Many embedded systems get improvements on hardware such as massive memory and multi-cores. According these improvements, some application that demands per-formance of excessive operations per seconds has been app-eared. These applications often use dynamic memory allocation. But, existing allocators does not scale well, thus those applications is limited theirs performance by allocators. Moreover, because the applications that run on embedded systems are rarely powered-off, the external fragmentation problem is critical. This paper introduces the allocator, lock-free and scalable that free the synchronization cost and low the fragmentation. Our allocator has per-thread heap and allocate the close size memory instead of the exact size of memory to reduce synchronization cost and allocation/de-allocation time. Our result on test application that can be run with 1 to 32 threads demonstrate that our allocator yields low average fragmentation and improves overall program performance over the standard Linux allocator by up to a factor of 60 on 32 threads, and up to a factor of 10 over the next best allocator we tested.

Interoperable Middleware Gateway Based on HLA and DDS for L-V-C Simulation Training Systems

Recently, by developing many training systems in battle field, the demand for interconnecting and internetworking between Live, Virtual, Constructive training systems has been increased to support efficient data distribution and system control. But, there are lots of problems for them to interwork, because the existing researches only support L-L, V-V, C-C Interoperability. Therefore, we propose L-V-C gateway to provide interoperable simulation environment based on HLA and DDS between them. First, we illustrate FOM Management that parses RPR-FOM XML file to acquire Data information to be shared between them, and generates common data structure and source code used for L-V-C Gateway. L-V-C Gateway created from FOM Management supports Data Conversion and Quality of Service between HLA and DDS. HLA Federate and DDS Domainparticipant in L-V-C Gateway play a role of logical communication channel and relay data from HLA Federation to DDS Domain and vice versa.

Lock-free memory allocator without garbage collection on multicore embedded devices

This paper suggests a new memory allocator for embedded devices. We design a memory allocator that uses lock-free mechanism for reducing overheads incurred by locks in multi-core environment. Experimental results show that our memory allocator is faster and more scalable than existing memory allocator in executing multi-threaded applications in embedded devices. On average, performance improvement of our memory allocator is 26% in producer-consumer pattern and 65% in general pattern.

DyKA: light-weight dynamic kernel analyzing framework based on binary translation method

Platform, which is based on typical OS, has been widely used in various areas from smart phone to TV. Along with this, the need for kernel analyzer has also grown up in order to develop and debug the kernel and its component effectively. Although previous approaches provide us some information about the target, that information is no more than hardware state, or primitive memory map, which is hard to understand. Moreover they cause an amount of overheads during analysis, so that analysis has been unable to work on environment as real. For applications some researches have been studied the analyzer using binary translation, and now it is widely used. Adopting their ideas, we propose dynamic kernel analyzer: DyKA. Kernel analyzers mainly focus on not kernel itself, but its plugins like device driver since the plugins comprise a large portion of OS development. Because of its locality, we should pay attention to the quality of the target code after translation in order to make the dynamic analyzer effective. Thus we apply some optimizations with DyKA as considering the target attribute. We implement the idea of DyKA on Linux system, and make sure, that it could analyze the target without a huge overhead, by experimental evaluation.