717 research outputs found

    FlexClock: Generic Clock Reconfiguration for Low-end IoT Devices

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    Clock configuration within constrained general-purpose microcontrollers takes a key role in tuning performance, power consumption, and timing accuracy of applications in the Internet of Things (IoT). Subsystems governing the underlying clock tree must nonetheless cope with a huge parameter space, complex dependencies, and dynamic constraints. Manufacturers expose the underlying functions in very diverse ways, which leads to specialized implementations of low portability. In this paper, we propose FlexClock, an approach for generic online clock reconfiguration on constrained IoT devices. We argue that (costly) generic clock configuration of general purpose computers and powerful mobile devices need to slim down to the lower end of the device spectrum. In search of a generalized solution, we identify recurring patterns and building blocks, which we use to decompose clock trees into independent, reusable components. With this segmentation we derive an abstract representation of vendor-specific clock trees, which then can be dynamically reconfigured at runtime. We evaluate our implementation on common hardware. Our measurements demonstrate how FlexClock significantly improves peak power consumption and energy efficiency by enabling dynamic voltage and frequency scaling (DVFS) in a platform-agnostic way

    CrowdAdaptor: A Crowd Sourcing Approach toward Adaptive Energy-Efficient Configurations of Virtual Machines Hosting Mobile Applications

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    Applications written by end-user programmers are hardly energy-optimized by these programmers. The end users of such applications thus suffer significant energy issues. In this paper, we propose CrowdAdaptor, a novel approach toward locating energy-efficient configurations to execute the applications hosted in virtual machines on handheld devices. CrowdAdaptor innovatively makes use of the development artifacts (test cases) and the very large installation base of the same application to distribute the test executions and performance data collection of the whole test suites against many different virtual machine configurations among these installation bases. It synthesizes these data, continuously discovers better energy-efficient configurations, and makes them available to all the installations of the same applications. We report a multi-subject case study on the ability of the framework to discover energy-efficient configurations in three power models. The results show that Crowd Adaptor can achieve up to 50% of energy savings based on a conservative linear power model.published_or_final_versio

    Reducing adverse impacts of Amazon hydropower expansion

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    Proposed hydropower dams at more than 350 sites throughout the Amazon require strategic evaluation of trade-offs between the numerous ecosystem services provided by Earth\u27s largest and most biodiverse river basin. These services are spatially variable, hence collective impacts of newly built dams depend strongly on their configuration. We use multiobjective optimization to identify portfolios of sites that simultaneously minimize impacts on river flow, river connectivity, sediment transport, fish diversity, and greenhouse gas emissions while achieving energy production goals. We find that uncoordinated, dam-by-dam hydropower expansion has resulted in forgone ecosystem service benefits. Minimizing further damage from hydropower development requires considering diverse environmental impacts across the entire basin, as well as cooperation among Amazonian nations. Our findings offer a transferable model for the evaluation of hydropower expansion in transboundary basins
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