An alternative algorithm is necessary, especially for a large scale network.
However, Gröbner algorithm works only for polynomials and moreover for a large scale network, it takes a long CPU time.
Then we apply the proposed architecture to the case of a large scale network which takes inspiration by traffic networks application.
We have implemented a concept proof prototype system and use NS-2 simulations to study the performance of the VMITN in a large scale network.
Due to the physical speed, using single robot to collect data in a large scale network may result in a long collection time.
We propose a new criteria called normalized eigenvalue variance as the measure of the convergence rate of a large scale network system with consensus.
In this paper, a robust decentralized congestion control strategy is developed for a large scale network with Differentiated Services (Diff-Serv) traffic.
However, the practicality of the proposed approach may be reduced if some practical challenges faced in a large scale network (such as many antennas, a lot of users, channel estimation error, and block diagonalization error) cannot be properly addressed.
Second, traffic overhead caused by frequent handovers increases because an OpenFlow Controller (OFC) has its own local domain and is not suitable for managing a large scale network as it is.
Taking these different aspects into consideration, this performance assessment must involve the evaluation of a large scale network, measuring the stability and overhead of this concept, as well as its overall traffic delivery performance.
