Finite state automata congestion control

Today's IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. The Internet of Things (IoT) has gained popularity in recent years. Lu, Yifei Ling, Zhen Zhu, Shuhong Tang, Ling SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications. The results are tested within a simulation example and the effectiveness of the proposed design method is verified. The procedure of the control synthesis is implemented by solving a linear matrix inequality (LMI. For this purpose, a dynamic output feedback controller with mode dependent parameters is synthesized to stochastically stabilize the TCP/AQM dynamics. An Active Queue Management (AQM technique is then used to adjust the queue level of the congested link to a predefined value. The randomness of link capacity, round trip time delay and the number of TCP sessions is modeled with a continuous-time finite state Markov process. The linear dynamic model of TCP New Reno in congestion avoidance mode is considered which contains round trip delays in both state and input. Syntheses of the control algorithms are illustrated with two application examples.TCP Congestion Control for the Networks with Markovian Jump ParametersДirectory of Open Access Journals (Sweden)ДЇull Text Available This paper is concerned with the problem of TCP congestion control for the class of communication networks with random parameters. The computational complexity of the optimal control synthesis is polynomial in n. Synthesis of the optimal control policy requires at most n iterations, where n is the number of states of the DFSA model generated from the unsupervised plant language. The signed real measure quantifies the behaviour of controlled sublanguages based on a state transition cost matrix and a characteristic vector as reported in earlier publications. The performance index for the optimal policy is obtained by combining a measure of the supervised plant language with (possible) penalty on disabling of controllable events. Syntheses of the control algorithms are illustrated with two application examples.ДЄB - This paper presents optimal supervisory control of dynamical systems that can be represented by deterministic finite state automaton (DFSA) models. N2 - This paper presents optimal supervisory control of dynamical systems that can be represented by deterministic finite state automaton (DFSA) models. This work has been supported in part by Army Research Office (ARO) under Grant No.ДAAD19-01-1-0646 and NASA Glenn Research Center under Grant No. T1 - Optimal supervisory control of finite state automata

Finite state automata congestion control