Based on the recent Internet advances, congestion control is considered as an important issue and has spurred a significant amount of research. In this study, second-order sliding mode control is used to adjust the average queue length and maintain the closed-loop system performance. The control law is obtained in two steps. First, the nonlinear state-space form of the network is extracted based on state variables as the average queue length and congestion window size. Then, the proportional-Integrator-derivative and proportional-derivative sliding surface are defined according to the tracking error. Also, in order to avoid chattering, the derivative of the sliding surface is considered and the closed-loop system stability is investigated based on Lyapunov theory. The proposed scheme renders good tracking specifications and closed-loop system robustness. The simulation results show that the proposed methods outperform proportional integral (PI) and proportional integral derivative (PID) schemes. Also, robustness to disturbances increases and chattering and transient response degradation are avoided.

In this paper buffer dynamic modeling for wireless sensor networks (WSNs) as a highly nonlinear system is accomplished in discrete time and the overall model is gained by blending subsystems obtained based on delay. Based on queue utilization and channel estimation algorithm, congestion is detected and a suitable rate is selected by an adaptive back-off interval selection. In this paper, a new approach is proposed for controller synthesis of our system based on non-quadratic Lyapunov functions, and a controller is designed to stabilize each subsystem. The controller synthesis results are expressed as a set of Linear Matrix Inequalities (LMIs). Moreover, the performance is considered and decay rate is guaranteed. Finally, a set of new LMI-based congestion control schemes (LCC) is obtained for WSNs. The closed-loop systems are globally asymptotically stable (GAS) in case of delay changes resulted from queue size changes. The simulation results using MATLAB and OPNET simulator confirm the effectiveness of our proposed schemes.

One of the problems with today's TCP/IP networks is their transmission system. If the bandwidth of a network is full, human and physical factors must be used for a new transmission system with a higher capacity to provide its bandwidth, which is very time consuming and costly. In this article, we proposed a method that in addition to the optimal use of available bandwidth, if the network capacity is full, it will be automatically transferred to a higher bandwidth network. For this purpose first, by designing a fuzzy PID controller for the existing network, it is tried to congestion control them and make use of it. It can be seen that the proposed controller performs much better in terms of an output response, following the queue length, stability and uncertainly, compared to the classical controller. If the input data to the network is increased, more packets are lost and this reduces the quality of the network. To solve this problem by using bandwidth management, by considering the threshold for packets loss in each network, if exceeding this limit, the existing network is switched to a network with a higher capacity and the problem of bandwidth and network quality is solved and causes subscriber satisfaction.

Routing in wireless sensor networks is one of the main challenges which directly influences the reliability and efficiency of the network. In this research, we combined several flows using inter-coding technique and hierarchical tree alternative path (HTAP) technique in order to efficiently control the congestion. It uses random network coding idea to increases network efficiency and decreases the congestion implicitly. Also, it explicitly reroutes the congested flows along alternative paths when the congestion condition is detected in congested nodes. The proposed method was simulated in different scenarios using MATLAB software and the simulation results showed that it decreases the number of transmitted packets, improves efficiency, and decreases energy consumption in comparison to original HTAP.

Traffic congestion in road networks is one of the main issues to be addressed, also vehicle traffic congestion and monitoring has become one of the critical issues in road transport. With the help of Intelligent Transportation System (ITS), current information of traffic can be used by control room to improve the traffic efficiency. The suggested system utilize technologies for realtime collection, organization and transmission of information to provide an efficient and accurate estimation of traffic density which can be exploited by traffic-aware applications. So, the proposed architecture of Vehicle Traffic congestion control & Monitoring System in IoT would perform well. A short overview of the main currently used traffic control methods for freeways will be explained. The tangible Internet of Things (IoT) based service models which are helpful to academic and industrial world to understand IoT business will be discussed.

The main idea of IoT is to connect several objects to each other through Internet. In the field of Computer Network the main problem identified by researchers is network congestion. Now a day’ s network congestion is increasing very rapidly because IoT connect a huge number of devices to internet. A transport layer protocol TCP (Transmission control Protocol) is accountable for network congestion control. The behavior of TCP is not stable as it takes long time to fill the available capacity of the network. It also continuously keeps assessing the capacity of data transmission through increasing the limits. TCP drops its data transmission rate aggressively when packets are dropped, which significantly reduces the throughput. This paper suggests a new approach, stable transmission control protocol for IoT applications. The experimental results show that stable transmission control protocol achieves better performance in terms of goodput.