Paralleling the rapid advancement in the network evolution is the need for advanced network traffic management surveillance. The increasing number and variety of services being offered by communication networks has fuelled the demand for optimized load management strategies. The problem of Load Control Management in Intelligent Networks has been studied previously and four Multi-Agent architectures have been proposed. The objective of this thesis is to investigate one of the quality attributes namely, scalability of the four Multi-Agent architectures. The focus of this research would be to resize the network and study the performance of the different architectures in terms of Load Control Management through different scalability attributes. The analysis has been based on experimentation through simulations. It has been revealed through the results that different architectures exhibit different performance behaviors for various scalability attributes at different network sizes. It has been observed that there exists a trade-off in different scalability attributes as the network grows. The factors affecting the network performance at different network settings have been observed. Based on the results from this study it would be easier to design similar networks for optimal performance by controlling the influencing factors and considering the trade-offs involved.