Enhanced Rate Control Data Collection (Ercdc) For Congestion Control and Maximisation Of Information in Wirelsess Sensor Networks

Abstract

Over the recent decade, mobile networks have made great development and will play an essential part in access networks. Next-generation mobile networks are predicted to enable Gbps uplink/downlink speeds, ubiquity, and huge interconnectedness. With the advancement of smart phone technology and mobile networks, several real-time applications have evolved that need high throughput and little end-to-end latency, which may create network congestion. Next-generation networks use mmWave to satisfy the increasing bandwidth and low latency needs of various applications. Wireless connections, on the other hand, suffer from significant route and penetration losses. Furthermore, the mobile network will evolve dynamically with the introduction of next generation mobile network services such as Device to Device (D2) communications, Internet of Things (IoT), Internet of Vehicles (IoV), and so on. Mobile networks are often linked together through wired backbone networks. The aforementioned network modifications will have an impact on the transport and network layer protocols. Since the past two decades, the Transmission Control Protocol (TCP) has been extensively used for dependable and error-checked data transport. Many network applications, such as HyperText Transfer Protocol (HTTP), streaming video, peer-to-peer file sharing, telnet, file transfer, simple mail transfer protocol, secure shell, and others, use the Transmission Control Protocol/Internet Protocol (TCP/IP). Intelligent communication technology has the potential to improve user experience. However, since wireless sensor networks (WSNs) have limited resources, congestion arises when a node's traffic load exceeds its available capacity. Congestion may lead to major difficulties. such as excessive packet loss and poor throughput, which have a severe negative effect on performance network of WSNs. An Enhanced Rate Control Data Collection (ERCDC) approach is presented to address this problem. To prevent or reduce network congestion the ERCDC scheme will reduce congestion by automatically decreasing data that includes less information, while maintaining the  network's information collection distortion rate at lower level. The ERCDC  primarily prevents or mitigates Congestion on the spatial and temporal levels which is  caused by information entropy theory, which also provides  lowest distortion rate. 1) Spatial congestion reduction :There is a geographical link between sensing data, when a given quantity of data is collected, some Matrix completion theory may restore missing data in space from other spatially obtained data. As a result, when congestion arises in the ERCDC  system, the quantity of data communicated (forwarded) for Congested nodes will be decreased using intelligent technique, which is  allowing congestion to be mitigated.2) Temporal congestion reduction : When there is congestion, the data gathering time windows are reduced. Carrying less information in order to limit the amount of data that must be delivered and thereby prevent congestion while decreasing the network's data distortion rate.