scholarly journals An Optimized Load Balancing Using Firefly Algorithm in Flying Ad-Hoc Network

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 252
Author(s):  
Manjit Kaur ◽  
Deepak Prashar ◽  
Mamoon Rashid ◽  
Zeba Khanam ◽  
Sultan S. Alshamrani ◽  
...  

In flying ad hoc networks (FANETs), load balancing is a vital issue. Numerous conventional routing protocols that have been created are ineffective at load balancing. The different scope of its applications has given it wide applicability, as well as the necessity for location assessment accuracy. Subsequently, implementing traffic congestion control based on the current connection status is difficult. To successfully tackle the above problem, we frame the traffic congestion control algorithm as a network utility optimization problem that takes different parameters of the network into account. For the location calculation of unknown nodes, the suggested approach distributes the computational load among flying nodes. Furthermore, the technique has been optimized in a FANET utilizing the firefly algorithm along with the traffic congestion control algorithm. The unknown nodes are located using the optimized backbone. Because the computational load is divided efficiently among the flying nodes, the simulation results show that our technique considerably enhances the network longevity and balanced traffic.

2020 ◽  
Vol 8 (5) ◽  
pp. 1970-1974

Congestion is a very big issue in mobile ad hoc network. In MANET has various congestion control algorithm to solve this issue. RED algorithm is the one of the congestion control algorithm. It increasing buffer space of the queue and it reduce the packet loss and control transmission delay. In the proposed technique first fine out the energy aware auction based route selection then used the red algorithm to control the congestion. This techniques give a better result comparatively other techniques. Reduce the transmission delay so it increase the network throughput and avoid the packet losses and also give a better packet delivery ratio.


Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3484 ◽  
Author(s):  
Jiashuai Wang ◽  
Xiaoping Yang ◽  
Ying Liu ◽  
Zhihong Qian

Existing hop-by-hop congestion control algorithms are mainly divided into two categories: those improving the sending rate and those suppressing the receiving rate. However, these congestion control algorithms have problems with validity and limitations. It is likely that the network will be paralyzed due to the unreasonable method of mitigating congestion. In this paper, we present a contention-based hop-by-hop bidirectional congestion control algorithm (HBCC). This algorithm uses the congestion detection method with queue length as a parameter. By detecting the queue length of the current node and the next hop node, the congestion conditions can be divided into the following four categories: 0–0, 0–1, 1–0, 1–1 (0 means no congestion, 1 means congestion). When at least one of the two nodes is congested, the HBCC algorithm adaptively adjusts the contention window of the current node, which can change the priority of the current node to access the channel. In this way, the buffer queue length of the congested node is reduced. When the congestion condition is 1–1, the hop-by-hop priority congestion control (HPCC) method proposed in this paper is used. This algorithm adaptively changes the adjustment degree of the current node competition window and improves the priority of congestion processing of the next hop node. The NS2 simulation shows that by using the HBCC algorithm, when compared with distributed coordination function (DCF) without congestion control, the proposed unidirectional congestion control algorithms hop-by-hop receiving-based congestion control (HRCC) and hop-by-hop sending-based congestion control (HSCC), and the existing congestion control algorithm congestion alleviation—MAC (CA-MAC), the average saturation throughput increased by approximately 90%, 62%, 12%, and 62%, respectively, and the buffer overflow loss ratio reduced by approximately 80%, 79%, 44%, and 79%.


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