Young Pil Kim

DAoT: Dynamic and energy-aware authentication for smart home appliances in Internet of Things

The Internet of Things (IoT) is beneficial to individuals, business, and society because it creates a wide range of value-added services by interconnecting diverse devices and information objects. However, as IoT devices have resource constraints to employ powerful security mechanisms, they are vulnerable to sophisticated security attacks such as the main-in-the-middle (MITM) attack. Therefore, an intelligent authentication mechanism that considers both resource constraints and security is required. In this paper, we suggest a dynamic and energy-aware authentication scheme for the Internet of Things (DAoT). DAoT uses a feedback control scheme to dynamically select an energy-efficient authentication policy. With DAoT, IoT devices with limited resources can be safely interconnected because DAoT finds and adopts the best cost-effective authentication mechanism.

Performance impact of JobTracker failure in Hadoop

In this paper, we analyze the performance impact of JobTracker failure in Hadoop. A JobTracker failure is a serious problem that affects the overall job processing performance. We describe the cause of failure and the system behaviors because of failed job processing in the Hadoop. On the basis of the analysis, we build a job completion time model that reflects failure effects. Our model is based on a stochastic process with a node crash probability. With our model, we run simulation of performance impact with very credible failure data available from USENIX called computer failure data repository that have been collected for past 9years. The results show that the performance impact is very severe in that the job completion time increases about four times typically, and in a worst case, it increases up to 68 times. Copyright

Real-time scheduling in a virtualized CE device

Recently, virtualization has been widely adopted in embedded systems. Because most of embedded systems have real-time requirements, real-time property needs to be preserved in a virtual machine system. We present how we can deal with real-time issues in an embedded virtual machine. Our contribution is that we provide a new abstract periodic interface to a real-time virtual machine so that the virtual machine can meet the physical execution condition.

Synchronization support for parallel applications in virtualized clouds

Cloud computing platforms have become very attractive for parallel applications, thanks to the system virtualization technology that allows versatile and pliable computing environments. However, owing to the virtualization overhead, parallel applications can suffer from poor performance when executing synchronization operations. In this paper, we propose sc scheduling, which is a synchronization-conscious scheduling algorithm that can mitigate the existing virtualization overhead. For this purpose, the proposed scheduler understands the synchronization phases of each parallel application. Based on this comprehension, it then eliminates unnecessary CPU spinning of parallel threads and its incurred waste of valuable CPU time. In addition, it prevents their long blocking, which otherwise causes unfairness between concurrent virtual machines (VMs) and other VMs. We implemented these simple concepts and thoroughly evaluated them in a recent Xen hypervisor release. Our results demonstrate that our approach can significantly improve the speed of concurrent virtual machines compared to the original credit scheduler in Xen.

Performance prediction and evaluation of parallel applications in KVM, Xen, and VMware

Cloud computing platforms are considerably attractive for parallel applications that perform large-scale, computationally intensive tasks. These platforms can provide elastic computing resources to the parallel software owing to system virtualization technology. Almost every cloud service provider operates on a pay-per-use basis, and therefore, it is important to estimate the performance of parallel applications before deploying them. However, a comprehensive study that can predict the performance of parallel applications remains unexplored and is still a research topic. In this paper, we provide a theoretical performance model that can predict the performance of parallel applications in different virtual machine scheduling policies and evaluate the model in representative hypervisors including KVM, Xen, and VMware. Through this analysis and evaluation, we show that our performance prediction model is accurate and reliable.

The Impact of Container Virtualization on Network Performance of IoT Devices

Container-based virtualization offers advantages such as high performance, resource efficiency, and agile environment. These advantages make Internet of Things (IoT) device management easy. Although container-based virtualization has already been introduced to IoT devices, the different network modes of containers and their performance issues have not been addressed. Since the network performance is an important factor in IoT, the analysis of the container network performance is essential. In this study, we analyze the network performance of containers on an IoT device, Raspberry Pi 3. The results show that the network performance of containers is lower than that of the native Linux, with an average performance difference of 6% and 18% for TCP and UDP, respectively. In addition, the network performance of containers varies depending on the network mode. When a single container runs, bridge mode achieves higher performance than host mode by 25% while host mode shows better performance than bridge mode by 45% in the multicontainer environment.

Test-driven development of consumer electronics device drivers: A user-level device driver approach

Developing device drivers is important for innovative consumer electronics because device driver implements key functionalities of new devices. This paper suggests a test-driven development (TDD) of device drivers, taking advantage of user-level driver. Applying TDD to device drivers is difficult because usually device drivers are implemented inside kernel, and are tightly coupled with complex kernel driver framework, which hinders driver developers from using TDD. Therefore, testing the device driver mostly focused on interaction with the rest of the kernel, rather than the device operations. Recent user-level device driver separates device drivers from the kernel. Thus, we can easily apply TDD on device drivers, circumventing complex kernel operations, and focusing on device operations. In addition, we can effectively enlarge testing coverage, enhancing software quality.

CRIM: Conditional Remapping to Improve the Reliability of Solid-State Drives with Minimizing Lifetime Loss

Solid-state drive (SSD) becomes popular as the main storage device. However, over time, the reliability of SSD degrades due to bit errors, which poses a serious issue. The periodic remapping (PR) has been suggested to overcome the issue, but it still has a critical weakness as PR increases lifetime loss. Therefore, we propose the conditional remapping invocation method (CRIM) to sustain reliability without lifetime loss. CRIM uses a probability-based threshold to determine the condition of invoking remapping operation. We evaluate the effectiveness of CRIM using the real workload trace data. In our experiments, we show that CRIM can extend a lifetime of SSD more than PR by up to 12.6% to 17.9% of 5-year warranty time. In addition, we show that CRIM can reduce the bit error probability of SSD by up to 73 times in terms of typical bit error rate in comparison with PR.

AKC: advanced KSM for cloud computing

Kernel samepage merging (KSM) in Linux kernel archive is a memory deduplication scheme that finds duplicate pages and shares the page in order to alleviate memory bottleneck in cloud. However, because the KSM has to scan all pages in memory to find duplicate pages, KSM consumes high CPU cycles and so causes virtual machines (VMs) performance degradation [1]. This degradation of VMs performance is an obstacle in cloud to service real-time applications (i.e. Netflix) [3]. A previous work, CMD [1] proposed page grouping scheme to reduce page comparisons, but it requires special monitoring hardware, XLH [2] enhanced page sharing with the information of guest VM I/O operation. However, the CPU overhead of XLH is still very high - similar to the default KSM. to make KSM more useful, we need an optimization scheme that consume less CPU cycles. Therefore, we first profile the CPU cycle consumption of KSM and the results show that page comparison (28.77%) and page checksum (26.14%) take most of cycles. Based on the results, we propose advanced KSM for cloud computing (AKC) that consumes less CPU cycles than the default KSM. to reduce the number of page comparisons, we apply checksum based RB-tree structure. In addition, AKC decreases page checksum overhead with hardware-accelerated crc32 hash function.

SSD-Tailor: Automated Customization System for Solid-State Drives

Enterprise servers require customized solid-state drives (SSDs) to satisfy their specialized I/O performance and reliability requirements. For effective use of SSDs for enterprise purposes, SSDs must be designed considering requirements such as those related to performance, lifetime, and cost constraints. However, SSDs have numerous hardware and software design options, such as flash memory types and block allocation methods, which have not been well analyzed yet, but on which the SSD performance depends. Furthermore, there is no methodology for determining the optimal design for a particular I/O workload. This paper proposes SSD-Tailor, a customization tool for SSDs. SSD-Tailor determines a near-optimal set of design options for a given workload. SSD designers can use SSD-Tailor to customize SSDs in the early design stage to meet the customer requirements. We evaluate SSD-Tailor with nine I/O workload traces collected from real-world enterprise servers. We observe that SSD-Tailor finds near-optimal SSD designs for these workloads by exploring only about 1% of the entire set of design candidates. We also show that the near-optimal designs increase the average I/O operations per second by up to 17% and decrease the average response time by up to 163% as compared to an SSD with a general design.