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Distributed Load-Balancing Method for CCA Parallel Component Applications
by
Guo, Lei
, Lv, Feiya
, Guo, Xin
in
Algorithms
/ Class libraries
/ Clusters
/ Communication
/ Computation
/ Data flow analysis
/ Dynamic loads
/ Libraries
/ Load balancing
/ Methods
/ Nodes
/ parallel component
/ parallel computing
/ performance optimization
/ Resource management
/ Resource utilization
/ Software
/ Static loads
2025
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Distributed Load-Balancing Method for CCA Parallel Component Applications
by
Guo, Lei
, Lv, Feiya
, Guo, Xin
in
Algorithms
/ Class libraries
/ Clusters
/ Communication
/ Computation
/ Data flow analysis
/ Dynamic loads
/ Libraries
/ Load balancing
/ Methods
/ Nodes
/ parallel component
/ parallel computing
/ performance optimization
/ Resource management
/ Resource utilization
/ Software
/ Static loads
2025
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Do you wish to request the book?
Distributed Load-Balancing Method for CCA Parallel Component Applications
by
Guo, Lei
, Lv, Feiya
, Guo, Xin
in
Algorithms
/ Class libraries
/ Clusters
/ Communication
/ Computation
/ Data flow analysis
/ Dynamic loads
/ Libraries
/ Load balancing
/ Methods
/ Nodes
/ parallel component
/ parallel computing
/ performance optimization
/ Resource management
/ Resource utilization
/ Software
/ Static loads
2025
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Distributed Load-Balancing Method for CCA Parallel Component Applications
Journal Article
Distributed Load-Balancing Method for CCA Parallel Component Applications
2025
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Overview
Numerous universities and national laboratories in the United States have collaboratively established a Common Component Architecture (CCA) forum to conduct research on parallel component technology. Given the overhead associated with component connection and management, performance optimization is of utmost importance. Current research often employs static load-balancing strategies or centralized dynamic approaches for load-balancing in parallel component applications. By analyzing the operational mechanism of CCA parallel components, this paper introduces a dynamic and distributed load-balancing method for such applications. We have developed a class library of computing nodes utilizing an object-oriented approach. The resource-management node deploys component applications onto sub-clusters generated by an aggregation algorithm. Dependency among different component calls is determined through data flow analysis. We maintain the load information of computing nodes within the sub-cluster using a distributed table update algorithm. By capturing the dynamic load information of computing nodes at runtime, we implement a load-balancing strategy in a distributed manner. Our dynamic and distributed load-balancing algorithm is capable of balancing component instance tasks across different nodes in a heterogeneous cluster platform, thereby enhancing resource utilization efficiency. Compared to existing static or centralized load-balancing methods, the proposed method demonstrates superior performance and scalability.
Publisher
MDPI AG
Subject
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