This Letter reports a method to obtain fine-grained energy consumption analysis of programs running on the low-power internet of things (IoT) devices. In the energy estimation domain, most state-ofthe-art solutions focus on the coarse-grained approach to monitor the energy consumption of a device or an application. However, few solutions addressed energy monitoring to analyse fine-grained energy consumption of a program, especially for IoT appliances. Therefore, the authors present a fine-grained gem5-based energy profiling tool to help developers to evaluate the energy efficiency of hot spots in their programs. The authors demonstrate its usability by applying it to profiling garbage collection and property lookup in Jerryscript, a JavaScript engine specifically designed for resource-constrained IoT devices, and discover that these two operations are consuming, as they account for 17.67 and 12.26% of total energy, respectively. Therefore, this tool can aid the developers to gain insight into the energy efficiency of their software.
Existing RAID-6 code extensions assume that failures are independent and instantaneous, overlooking the underlying mechanism of multifailure occurrences. Also, the effect of reconstruction window is ignored. Additionally, these coding extensions have not been adapted to occurrence patterns of failure in real-world applications. As a result, the third parity drive is set to handle the triple-failure scenario; however, the lower level failure situations have been left unattended. Therefore, a new methodology of extending RAID-6 codes named RAID-6Plus with better compromise has been studied in this paper. RAID-6Plus (Deng et al., 2015) employs short combinations which can greatly reuse overlapped elements during reconstruction to remake the third parity drive. A sample extension code called RDP+ is given based on RDP. Moreover, we extended the study to present another extension example called X-code+ which has better update penalty and load balance. The analysis shows that RAID-6Plus is a balanced tradeoff of reliability, performance, and practicality. For instance, RDP+ could achieve speedups as high as 33.4% in comparison to the RTP with conventional rebuild, 11.9% in comparison to RTP with the optimal rebuild, 47.7% in comparison to STAR with conventional rebuild, and 26.2% for a single failure rebuild.
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