A robust congestion control scheme for cluster wireless multimedia sensor networks with propagation delay and external interference

Abstract

Congestion control in cluster wireless multimedia sensor networks is capable of delivering and gathering multimedia information, while propagation delay and external interference may cause it unable to achieve the maximal network throughput without congestion control. To solve the problem, based on the additive-increase multiplicative-decrease adjustment strategy, a robust congestion control model is proposed with a scheduling scheme in cluster wireless multimedia sensor networks considering the neighbor feedback. The robust congestion control model is a Lur'e-type system. The cluster wireless multimedia sensor network is capable of achieving the desired cluster synchronization with network parameters provided by Lyapunov-Krasovskii functionals. Sufficient conditions of the robust congestion control are formulated by linear matrix inequalities. Numerical results show the effectiveness of the proposed scheme.

WOA-Based Robust Congestion Control Scheme with Two Kinds of Propagation Latencies and External Disturbance in Software-Defined Wireless Networks

“…The authors of [ 35 ] proposed a fault-prone, concurrent control scheme for robust policy implementation in distributed SDNs. The authors of [ 36 , 37 , 38 ] proposed robust congestion control schemes for achieving maximal network throughput by considering the propagation latency in device-to-device paths.…”

“…Information forwarding and control algorithm [ 36 , 37 , 38 ]: The previous algorithm that addresses network congestion implements the robust control of partial networks instead of control incorporating a global view of the SDWN, which is often used for robust congestion control without considering the propagation latency in device–controller pairs.…”

“…In terms of the information-forwarding and control algorithm, to solve the network congestion problem, existing works such as [ 2 , 34 , 35 , 36 ] emphasize the robust control of partial networks instead of employing a global view of SDWN. This may result in the wireless network failing to achieve global SDWN robustness when the propagation latencies in device–controller pairs are not considered.…”

“…In terms of robust control algorithms, various forwarding information control algorithms have been proposed through analyses of SDWN-centralized controllers with respect to improving network robustness and reacting to failures [ 2 , 23 , 33 , 34 , 35 ]. In [ 36 , 37 , 38 ], robust congestion control schemes have been proposed in order to achieve maximal network throughput in device-to-device paths by using Lyapunov–Krasovskii functionals. In terms of meta-heuristic optimization algorithms, several meta-heuristic optimization algorithms, such as the Social Spider Optimization (SSO) algorithm [ 39 ], Bat Algorithm [ 40 ], and Particle Swarm Optimization (PSO) algorithm [ 41 ], have been utilized in wireless networks to greatly reduce the number of network data required to solve the network congestion problem [ 42 ].…”

“…Next, the forwarding devices follow these control instructions and make proper adjustments to the sending rates at the source-side. Previous works, such as [ 36 , 37 , 38 ], studied the robust congestion control scheme with propagation latency in device–controller pairs, while this paper defines the propagation latency in both device–controller pairs and device-to-device paths as an upper bound of latency. Thus, two closed-loop congestion control models are established for the further research of the robust congestion control scheme.…”