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In this paper we present a novel Code Execution Framework that can execute code of different problem solving environments (PSE), such as MATLAB, R and Octave, in parallel.
In this work, a novel mobile cloud execution framework is proposed to execute mobile applications in a cloud-based virtualized execution environment controlled by mobile applications and users, with encryption and isolation to protect against eavesdropping from cloud providers.
In this paper we have presented a novel Code Execution Framework (CEF) that is able to execute problem solving environment (PSE) source code in parallel, using a cloud infrastructure.
Ray, a low-latency distributed execution framework for machine learning and reinforcement learning applications.
"A Distributed Data-Parallel Execution Framework in the Kepler Scientific Workflow System".
In this blog post we introduce Ray RLlib, an RL execution toolkit built on the Ray distributed execution framework.
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Moreover, we compare the application execution frameworks on the basis of significant optimization parameters that affect performance of the applications and mobile devices in MCC.
This paper presents the state-of-the-art mobile application execution frameworks and provides the readers a discussion on the optimization strategies that facilitate attaining the effective design, efficient deployment, and application migration with optimal performance in MCC.
Seamless application execution frameworks in MCC are also highlighted in [32] with detailed comparisons and analysis.
The above mentioned parallel or cloud based execution frameworks have great potential allowing to manage parallel/cloud based code execution for a single PSE.
Finally, in order to validate and showcase the time and cost efficiency of our approach, we compare our performance with Swift, one of the most widely used and state-of-the-art high performance workflow execution frameworks.
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