KEYWORDS: Network architectures, Systems modeling, Complex systems, Probability theory, Mathematical modeling, Process modeling, Modeling, Computing systems, Performance modeling, System identification
A constrained preferential attachment mechanism is proposed for the modeling of network architecture and system
designing, network growth and node balancing in large and complex network systems. The mechanism applied to
optimize a balanced growth in the network architecture. The methods for random networks to display real world network
behavior with growth and balance are explored. An idea of best node is introduced to formulate a balanced model of
network architecture with preservation of resources for network growth. New terms are introduced and existing terms are
also reviewed and explored. Network graph theory reviewed to answer the important questions related to complex
network systems.
A constrained preferential attachment mechanism is proposed for the load balancing and the constrained preferential
attachment mechanism [16] is explored for the robustness in large and complex network systems. The constrained
preferential attachment policy method applied to optimize the load balancing of services or resources in grid computing
environment for quality of services. It is presented how uniform utilization of resources can be achieved by using constrained
preferential attachment policy method. A mathematical model is designed to work with constrained preferential attachment
mechanism [16] for the network nodes/load re-balancing in case of attack or failure. Network graph theory reviewed to
answer the important questions related to complex network systems load balancing and robustness.
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