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An Organized Study of Congestion Control Approaches in Wireless Sensor Networks
Published in Mangesh M. Ghonge, Ramchandra Sharad Mangrulkar, Pradip M. Jawandhiya, Nitin Goje, Future Trends in 5G and 6G, 2021
Savita Jadhav, Sangeeta Jadhav
Wireless Sensor Networks (WSNs) face many issues due to resource-constrained nature of the nodes. The network congestion is one of the main challenges that takes place when packet entrance rate surpasses the packet service rate. The chapter compares important techniques on the basis of congestion detection, notification, and alleviation. The analysis of this study specifies that network congestion leads to data loss, excess power dissipation, increased delays, and throughput minimization. The papers selected for this revision are beyond 2017. The protocols discussed in this chapter are headed into four groups as traffic rate, resource management-based, queue-assisted, and priority-based. These techniques are application-specific in nature and have their own merits and demerits. Thus it concludes that in case of heavy traffic conditions, using resource control algorithms is more relevant than data rate alteration. As these algorithms appreciably improve network performance due to uniform energy utilization. The limitations of using recourse control method are increased overhead and delay. On the other hand, traffic control methods are less complicated, less costly, and by using this method node level congestion is controlled with low delay. The limitation of using traffic control method is that it has high energy consumption, low-throughput, and valuable data may be lost. Hence, to control congestion, futuristic congestion control approaches should be explored based on computational intelligence and machine learning techniques. Nowadays, many techniques exist but still require further investigation for use under different applications.
Traffic Engineering Concepts
Published in Nam-Kee Tan, MPLS for Metropolitan Area Networks, 2004
Multiple traffic streams vie for the use of network resources such as bandwidth when they are transported through a network. Network congestion occurs when the arrival rate of data packets exceeds the output capacity of the network resources over a period of time. Congestion is highly undesirable because it increases transit delay, delay variation, and packet loss and lowers the predictability of network services. The fundamental challenge in network operation is to increase the efficiency of resource utilization while minimizing the possibility of congestion.
Network congestion and transmission loading relief
Published in Fred I. Denny, David E. Dismukes, Power System Operations and Electricity Markets, 2017
Fred I. Denny, David E. Dismukes
Network congestion can be reduced by cancelling transactions, redispatching generation, reconfiguring transmission, or reducing loads. Obviously, there can be very great financial impacts from taking any of these actions. And, of course, equal or even greater financial impacts can result from allowing network congestion to cause overloads or other operating security limit violations. Consequently, all participants in electric power markets have taken a keen interest in network congestion problems and methods for relieving network congestion.
A brief survey on nonlinear control using adaptive dynamic programming under engineering-oriented complexities
Published in International Journal of Systems Science, 2023
Yuhan Zhang, Lei Zou, Yang Liu, Derui Ding, Jun Hu
Network congestion, which is an inevitable phenomenon in many industrial applications, mainly results from the frequent signal transmissions between system components (i.e. sensors, estimators, and controllers) over a shared communication network with limited bandwidth (Dong et al., 2022; Li et al., 2022; Shen et al., 2022; Yao et al., 2022). Correspondingly, various communication protocols are often adopted to govern the signal transmission process to prevent collisions in the signal transmission process (Liu et al., 2022; Xu et al., 2022). Under the scheduling of communication protocols, only one sensor node is permitted to transmit the current signal at each time instant (Xu et al., 2021). In engineering practice, the widely adopted communication protocols include, but are not limited to, the Round-Robin communication protocol, the stochastic communication protocol, and the try-once-discard communication protocol (Xu et al., 2022).
Towards complex dynamic fog network orchestration using embedded neural switch
Published in International Journal of Computers and Applications, 2021
K. C. Okafor, G. C. Ononiwu, Sam Goundar, V. C. Chijindu, C. C. Udeze
Due to the massive nature of communication pattern in the HDN, a smart Fog layer is needed. Without this layer, there will be frequent high link utilization and workload congestion at aggregation or core layers [8]. This is because, data center networks leverage multiple parallel paths connecting end host pairs to offer high bisection bandwidth for cluster computing applications [9]. Those congested heavy flows often lead to the unavoidable breakdown of the commodity servers while some specialized links within HDN observe higher loss ratio than others [10]. In such networks, Equal Cost Multipath (ECMP) routing protocols seem to be unaware of the traffic–workload due to static flow-to-link assignments which usually causes bandwidth loss arising from flow collisions. While high resource utilization is favorable to service providers partly, network congestion can cause harmful queuing delay and packet loss, and thus affects the network throughput. These consequences could significantly degrade application performance and user experience. Figure 1 shows how the Fog Ethernet switch components are used for connections leading to latency and congestion management similar to a traditional DCN network storage [11,12]. In this case, it is used for the separation of storage, network and HPC traffic into separate virtual fabrics using shared memory partitions. This is useful in a well-managed Fog data center network in order to achieve overall performance efficiency in deployment contexts.
Software Defined Networking Controller (SDNC): a robust security architecture for SDN-based 5G networks
Published in Automatika, 2023
Retransmissions and the quantity of Residual Energy (RE) are important factors when calculating the system's performance [18]. Monitoring packet movement in the network from various sources to sink nodes allows for the detection of network congestion. The queue length is a substantial element in this case for monitoring the congestion. The system-wide distribution of wait length is maintained throughout. Network data packets are routed using window and queue sizes. The buffer size of the receiving node is verified as each packet is sent from a source to that node; if the buffer size is exceeded, either zero or no acknowledgement is sent.