A control strategy of virtual synchronous generator based on power angle characteristics of synchronous generator is designed for independent distributed generation system, which enables the inverter to be connected i...
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The surge in demand for computing resources in data centers coupled with the rise of environmental concerns has motivated cloud providers to reduce carbon emission due to computational energy consumption. An opportuni...
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ISBN:
(纸本)9798331531317;9798331531300
The surge in demand for computing resources in data centers coupled with the rise of environmental concerns has motivated cloud providers to reduce carbon emission due to computational energy consumption. An opportunity lies in the fluctuating availability of renewable energy over time and the variability of power sources over grid regions, leading to variations in space and time in carbon intensity. Exploiting such variations, this paper introduces Caspian, a carbon-aware workload scheduler in multi-cluster Kubernetes environments, which aims at reducing the Carbon Footprint (CFP) due to executing workloads, while satisfying Quality of Service (QoS) requirements. Caspian cooperates with a multi-cluster management platform to apply scheduling and placement decisions over distributed clusters. We present efficient optimization algorithms to achieve these goals. Further, we describe an implementation of Caspian, integrated with Multi Cluster App Dispatcher (MCAD), a multi-cluster management platform which handles queuing and dispatching of workloads over multiple clusters. Our experimental results show that Caspian effectively reduces CFP with reasonable QoS, compared to a baseline scheduler which only satisfies the QoS of workloads. Specifically, Caspian reduces CFP by about 33%, with about 98% of workloads completing at an average fraction of 0.6 of their deadline.
parallelcomputing and distributedcomputing are the popular terminologies of scheduling. With advancement in technology, systems have become much more compact and fast and need of parallelization plays a major role f...
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ISBN:
(纸本)9783031368042;9783031368059
parallelcomputing and distributedcomputing are the popular terminologies of scheduling. With advancement in technology, systems have become much more compact and fast and need of parallelization plays a major role for this compaction. Wireless computing is also a common concept associated with each new development. Scheduling of tasks has always been a challenging area and is an NP-complete problem. Moreover, when it comes to wireless distributedcomputing, reliable scheduling plays an important role in order to complete a task in a wireless distributed system. This work proposes an algorithm to dynamically schedule tasks on heterogeneous processors within a wireless distributedcomputing system. A lot of heuristics, meta-heuristics & genetics have been used earlier with scheduling strategies. However, most of them haven't taken reliability into account before scheduling. Here a heuristic that deals with reliable scheduling is considered. The scheduler also works within an environment which has dynamically changing resources and adapts itself to changing system resources. The testing was carried out with up to 200 tasks being scheduled while testing in a real time wireless distributed environment. Experiments have shown that the algorithm outperforms the other strategies and can achieve a better reliability along with no increase in make-span, in spite of wireless nodes.
Vehicular edge computing (VEC) has emerged in the Internet of Vehicles (IoV) as a new paradigm that offloads computation tasks to Road Side Units (RSU) aiming to reduce the processing delay as well as the resource con...
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ISBN:
(纸本)9781665473156
Vehicular edge computing (VEC) has emerged in the Internet of Vehicles (IoV) as a new paradigm that offloads computation tasks to Road Side Units (RSU) aiming to reduce the processing delay as well as the resource consumption of vehicles. Ideal computation offloading policies for VEC are expected to achieve both low latency and low energy consumption. Although existing works have made great contributions, they rarely consider the coordination of multiple RSUs and the individual Quality of Service (QoS) requirements of different applications resulting in suboptimal offloading policies. In this paper, we present FEVEC, a Fast and Energy-efficient VEC framework with the objective of making the optimal offloading strategy that minimizes both delay and energy consumption. FEVEC coordinates multiple RSUs and considers the application-specific QoS requirement. We formalize the computation offloading problem as a multi-objective optimization problem by jointly optimizing offloading decision and resource allocation, which is a mixed-integer nonlinear programming (MINLP) problem and NP-hard. We propose MOV, a Multi-Objective computing offloading method for VEC, where an improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to obtain the Pareto-optimal solutions with low complexity. Furthermore, the optimal offloading strategy is selected for QoS maximization. Extensive evaluation results based on realistic and simulated vehicle trajectories verify that our proposed algorithm has a better performance compared with the state-of-the-art VEC mechanism.
Convolutional neural network combines low-level features to form more abstract high-level representation attribute categories or features, so as to discover the distributed feature representation of data. At the same ...
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Modeling urban mobility behaviours with micro-scopic traffic flow simulation is now crucial for studying intel-ligent urban decision-making algorithms, such as traffic light control and road congestion charging. Howev...
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The representation of the base station radiation prediction range based on the three-dimensional triangulation grid can more comprehensively and quickly reflect the distribution details of base station radiation predi...
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The new power distribution system is an important part of building a new power system and promoting the realization of the 'double carbon' goal. The massive access of distributed power generation, distributed ...
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This paper provides an overview on scalable deep learning platforms and how they are used in medical context. An introduction highlights the key factors, then an overview on medical context is provided. Afterwards, th...
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ISBN:
(纸本)9781450393867
This paper provides an overview on scalable deep learning platforms and how they are used in medical context. An introduction highlights the key factors, then an overview on medical context is provided. Afterwards, the basic concepts about deep learning and parallel and distributedcomputing are briefly recalled. Then a specific deep learning library for medical applications is described. The last part of the paper is focused on a real use case application of deep learning on medical data. As a result, the main contribution of this paper is a short survey on main scalable deep learning platforms with a first analysis of their features, and the description of a practical example.
The proceedings contain 247 papers. The topics discussed include: importance of cyber security in software quality assurance;an intelligent system for estimation of exergy efficiency of integrated naphtha and isomeriz...
ISBN:
(纸本)9798350315905
The proceedings contain 247 papers. The topics discussed include: importance of cyber security in software quality assurance;an intelligent system for estimation of exergy efficiency of integrated naphtha and isomerization process under uncertainty;smart scheduling of EVS through intelligent home energy management using deep reinforcement learning;cascade failure management in distributed smart grid using multi-agent control;angular accuracy improvement in digital array radar with experimental analysis;a fall detection algorithm for thigh mounted smartphones using random forest and feature selection techniques;analysis of deep learning algorithms on edge in microscopic fabric dataset;multi-exposure image fusion using edge-aware network;employing intrinsic rewards to reduce requirements engineering issues in large distributed ERP teams;and the state of practices in requirement elicitation: an improved methodology for Pak software industry.
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