KEYWORDS: Signal processing, Telecommunications, Radar, Data communications, Fourier transforms, Wavefronts, Thulium, Systems engineering, Sodium, Reliability
In order to give full play to the high parallel and high efficiency characteristics of heterogeneous signal processing platforms, relevant scholars at home and abroad have proposed many task scheduling algorithms with their own advantages to improve processing efficiency. However, for communication intensive tasks, the existing task deployment methods are no longer applicable because of their higher communication requirements and communication delay becomes the key to limit the performance of the platform. For communication-intensive signal tasks, this paper proposes a load balancing scheduling method based on edge clustering. Tasks are abstracted as directed acyclic graph, we aggregate the qualified task edges according to the rating function to reduce the computational complexity, and task duplication is used to replicate the tasks on the critical path to reduce communication overhead and dynamically balance processor load. Through the experimental verification of random task graphs and radar task, it is concluded that the algorithm has a good scheduling result for communication intensive tasks, which can achieve good processor load balancing and system scheduling length reduction.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.