Microservers (MSs, ARM-based mobile devices) with built-in sensors and network connectivity have become increasingly pervasive and their computational capabilities continue to be improved. Many works present that the ...
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Microservers (MSs, ARM-based mobile devices) with built-in sensors and network connectivity have become increasingly pervasive and their computational capabilities continue to be improved. Many works present that the heterogeneous clusters, consist of the low-power MSs and high-performance nodes (x86-based servers), can provide competitive performance and energy efficiency. However, they make simple modifications in existing distributedcomputing systems for adaptation, which have been proven not to fully exploit the various heterogeneous resources. In this paper, we argue that these heterogeneous clusters also call for flexible and efficient computational resource sharing and scheduling. We then present Aries, a platform to support abstracting, sharing and scheduling the cluster resources, scaling from embedded devices to high performance servers, between multiple distributedcomputing frameworks (Hadoop, Spark, etc.). In Aries, we propose a two-layer scheduling mechanism to enhance the resource utilization of these heterogeneous clusters. Specifically, the resource abstraction layer in Aries is constructed for overall coordination of resources, which provide computation and energy management. A hybrid resource abstraction approach is designed to manage HS and MS resources in fine and coarse granularity separately in this layer to support efficient resource offer based on "resource slot". And the task schedule layer supports various sophisticated schedulers of existing distributed frameworks and decides how many resources to offer computing frameworks. Furthermore, Aries adopts a novel strategy to support smart switch in three system models for energy-saving effectiveness. We evaluate Aries by a variety of typical data center workloads and datasets, and the result shows that Aries can achieve more efficient utilization of resources when sharing the heterogeneous cluster among diverse frameworks.
The development of complex networked multi-core systems, like compute nodes in the Internet-of-Things, requires new simulation and design concepts. In this paper we present an environment for the asynchronous simulati...
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ISBN:
(纸本)9781479968909
The development of complex networked multi-core systems, like compute nodes in the Internet-of-Things, requires new simulation and design concepts. In this paper we present an environment for the asynchronous simulation of networked multi-core systems, based on SystemC. Combined with the open-source machine emulator and virtualizer QEMU, a virtual network is created. The compute nodes act similar to recent Systems-on-Chip from Xilinx and Altera. By combining an ARM processing system with programmable logic, a high flexibility is provided. We exemplary simulate these systems by extending QEMU, following its device model abstraction qdev. The resulting network benefits from the execution on different host systems. It is highly scalable and designed for the development of complex networked multi-core systems. For the non-distributed execution on one processor we implemented an alternative communication method which takes only 2/3 of the time for networked simulation.
Due to ongoing changes in the power grid towards decentralised and highly volatile energy production, smart electricitymeters are required to provide fine-grained measurement and timely remote access to consumption an...
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ISBN:
(纸本)9783319459301;9783319459318
Due to ongoing changes in the power grid towards decentralised and highly volatile energy production, smart electricitymeters are required to provide fine-grained measurement and timely remote access to consumption and production data. This enables flexible tariffing and dynamic load optimisation. As the power grid forms part of the critical infrastructure of our society, increasing the resilience of the grid's software components against failures and attacks is vitally important. In this paper we explore the use of Protected Module Architectures (PMAs) to securely implement and deploy software for smart electricity meters. Outlining security challenges and an architectural solution in the light of security features provided by PMAs, we evaluate a proof-of-concept implementation of a security-focused smart metering scenario. Our implementation is based on Sancus, an embedded PMA for low-power microcontrollers. The evaluation of our prototype provides strong indication for the feasibility of implementing a PMA-based high assurance smart meter with a very small software Trusted computing Base, which would be suitable for security certification and formal verification.
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