Dynamic Voltage Scaling Technology Research Articles

On Random Dynamic Voltage Scaling for Internet-of-Things: A Game-Theoretic Approach

Security is one of the top considerations in hardware designs for Internet-of-Things (IoT), where embedded cryptosystems are extensively used. Traditionally, random dynamic voltage scaling technology has been shown to be very effective in improving the resistance of cryptosystems against side-channel attacks. However, in this paper we demonstrate that the resistance can be undermined by providing lower off-chip power supply voltage. In order to address this issue, we then further propose to monitor the off-chip power supply voltage, and trigger an alarm to protect valued information once the power supply voltage is lower than the expected voltage (threshold voltage). However, considering both maintenance cost of IoT devices and the environment noise on power supply voltage, we first formulated this problem as a nonzero sum game model, and the attacker and the circuit supplier (defender) are the players of this game. The analysis of the Nash equilibria in this game show interesting guideline to the defender about the choice of threshold voltage, which is based on parameters of cryptosystem including the value of information, denial-of-service cost in IoT, etc.

A new high-performance open CNC system and its energy-aware scheduling algorithm

Computer numerical control (CNC) systems are shifting to a direction of open architecture which has better flexibility, adaptability, versatility, and expansibility. Existing CNC systems tend to have a high level energy consumption. This paper introduces a new open CNC system based on the low-power embedded platform, named open and high-performance CNC (OHP-CNC). OHP-CNC is able to achieve high precision, high efficiency, and low power consumption by making use of international standards, open components such as hardware and software, and an energy-aware real-time scheduling algorithm. The proposed algorithm for mixed tasks, including periodic and aperiodic tasks, is divided into two phases. Firstly, the slack time and utilization are calculated on each processor and tasks are assigned to the processor according to the load. Secondly, because there is a trade-off between the energy-saving and the response times of the aperiodic task, the scheduling server is used to schedule aperiodic tasks in order to meet the response time constraints of aperiodic tasks. Meanwhile, periodic tasks recycle the slack time with dynamic voltage scaling technology to achieve low power consumption. Experiment results show that the energy-aware real-time algorithm yields high-performance and effective machining processes.

Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling

The incorporation of dynamic voltage scaling technology into computation offloading offers more flexibilities for mobile edge computing. In this paper, we investigate partial computation offloading by jointly optimizing the computational speed of smart mobile device (SMD), transmit power of SMD, and offloading ratio with two system design objectives: energy consumption of SMD minimization (ECM) and latency of application execution minimization (LM). Considering the case that the SMD is served by a single cloud server, we formulate both the ECM problem and the LM problem as nonconvex problems. To tackle the ECM problem, we recast it as a convex one with the variable substitution technique and obtain its optimal solution. To address the nonconvex and nonsmooth LM problem, we propose a locally optimal algorithm with the univariate search technique. Furthermore, we extend the scenario to a multiple cloud servers system, where the SMD could offload its computation to a set of cloud servers. In this scenario, we obtain the optimal computation distribution among cloud servers in closed form for the ECM and LM problems. Finally, extensive simulations demonstrate that our proposed algorithms can significantly reduce the energy consumption and shorten the latency with respect to the existing offloading schemes.

Power-Aware Parallel Loop Scheduling Method for Heterogeneous System

PDF HTML阅读 XML下载 导出引用 引用提醒 异构系统功耗感知的并行循环调度方法 DOI: 10.3724/SP.J.1001.2011.03883 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(60921062, 60903059, 60903044); 国家科技重大专项(2009ZX01036-001-003-001) Power-Aware Parallel Loop Scheduling Method for Heterogeneous System Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以类OpenMP的并行程序为研究对象,在满足性能约束的条件下,结合异构系统并行循环调度和处理器动态电压调节技术优化系统功耗.首先建立了异构系统功耗感知的并行循环调度问题基本模型;然后,通过分析方法给出异构系统并行循环调度的能耗下界,该下界可用于评估功耗优化方法的实际效率;进而将异构系统并行循环调度问题归纳为整数规划问题,在此基础上,提出了处理器内循环再调度方法进一步降低功耗.最后,以CPU-GPU 异构系统为平台评测了10 个典型kernel 程序.实验结果表明,该方法可以有效降低系统功耗,提高系统效能. Abstract:Based on the OpenMP-like parallel program, a loop scheduling and dynamic voltage scaling technology is coordinated to optimize system power consumption under the given performance constraint. First, the basic model for power-aware loop scheduling on the heterogeneous system is presented. After that, through theoretical analysis, it has been concluded that the lower bound of energy consumption for parallel loop scheduling on heterogeneous systems, can be used as a baseline to evaluate the efficiency of optimization technology. Furthermore, this paper induces the scheduling problem as a typical integer programming problem and proposes inner-processor loop re-scheduling method to further reduce power consumption. Finally, 10 typical kernel programs on a CPU-GPU heterogeneous system are created. The experimental results demonstrate that the proposed method can effectively reduce the total energy consumption of the whole system and improve the system energy efficiency. 参考文献 相似文献 引证文献

A Scheduling with DVS Mechanism for Embedded Multi-Core Real-Time Systems

Abstract With the advancement of technology, embedded systems have been widely used in portable devices. Portable embedded systems must have rather superior computing capability in order to meet real-time application demands. It is very important for the design of portable embedded system to enable minimum energy consumption while meeting real-time application demands. Dynamic voltage scaling technology enables effective reduction of energy consumption by utilizing slack time to modify operation voltage and frequency of processor in order to reduce energy consumption. Multi-core systems have gradually become mainstream products providing better throughput capacity than single-core systems under the same working clock frequency. However, in multi-core environment the real-time scheduling is an NP-hard issue. A real-time scheduling mechanism proposed for multi-core systems which in conjunction with dynamic voltage scaling can reduce energy consumption. The proposed ME-DVS (Modified EDF with Dynamic Voltage Scaling) scheduling algorithm can effectively reduce energy consumption in multi-core environment and ensure all tasks to meet their deadlines. The experimental results have shown that in 4-core environment, the energy consumption can be reduced by 3% when increasing the number of tasks to 30, 87% of processor total utilization, and by 52% when increasing the number of tasks to 5, 18% of processor total utilization. Similar results can be found in 8-core and 16-core environments.