A Congestion-Aware Clustering and Routing (CCR) Protocol for Mitigating Congestion in WSN

Farsi, Mohammed; Badawy, Mahmoud; Moustafa, Mona; Ali, Hesham; AbdulAzeem, Yousry M.

doi:10.1109/access.2019.2932951

Cited by 42 publications

(30 citation statements)

References 29 publications

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“…The data which is transmitted consists of little additional information such as the iteration count, level information, section information, address, ratio of message that has to be transmitted and the free space details. Each transmission consists of periods which are created using the data size of the node and CH count in the level of the node [ 59 ].…”

Section: Proposed Methodsmentioning

confidence: 99%

MWCSGA—Multi Weight Chicken Swarm Based Genetic Algorithm for Energy Efficient Clustered Wireless Sensor Network

Ajmi

Helali

Lorenz

et al. 2021

Sensors

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Nowadays due to smart environment creation there is a rapid growth in wireless sensor network (WSN) technology real time applications. The most critical resource in in WSN is battery power. One of the familiar methods which mainly concentrate in increasing the power factor in WSN is clustering. In this research work, a novel concept for clustering is introduced which is multi weight chicken swarm based genetic algorithm for energy efficient clustering (MWCSGA). It mainly consists of six sections. They are system model, chicken swarm optimization, genetic algorithm, CCSO-GA cluster head selection, multi weight clustering model, inter cluster, and intra cluster communication. In the performance evaluation the proposed model is compared with few earlier methods such as Genetic Algorithm-Based Energy-Efficient Adaptive Clustering Protocol For Wireless Sensor Networks (GA-LEACH), Low energy adaptive Clustering hierarchy approach for WSN (MW-LEACH) and Chicken Swarm Optimization based Genetic Algorithm (CSOGA). During the comparison it is proved that our proposed method performed well in terms of energy efficiency, end to end delay, packet drop, packet delivery ratio and network throughput.

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Section: Proposed Methodsmentioning

confidence: 99%

MWCSGA—Multi Weight Chicken Swarm Based Genetic Algorithm for Energy Efficient Clustered Wireless Sensor Network

Ajmi

Helali

Lorenz

et al. 2021

Sensors

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“…Authors of [32] proposed a novel protocol called Congestion-Aware Clustering and Routing (CCR) to eliminate the congestion and clustering in Wireless Sensor Networks (WSN). Sender-side congestion control and modelbased bandwidth estimation for TCP traffic over contentionfree Time-division multiple access (TDMA) based MANETs was proposed in [33].…”

Section: Literature Reviewmentioning

confidence: 99%

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

Bhardwaj

El-Ocla

2020

IEEE Access

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Mobile ad hoc network (MANET) is a cluster of wireless mobile gadgets that creates a temporary network without seeking support from any infrastructure or central management. Energy consumption should be considered as one of the foremost vital limitations in MANETs because the mobile nodes do not possess a constant power supply and its shortage will minimize the network's lifetime. MANETs get energy from the batteries which get exhausted very quickly because of issues like node mobility, computation power, frequent data retransmissions needed in wireless communication, etc. Secondly, there is a data packet loss caused by different reasons such as traffic congestion or random loss as a result of nodes mobility or noise. This data loss, in turn, would delay packets delivery degrading data transmission in real-time applications. This paper provides management for this combination of major problems in MANETs. We present a new fitness function (FFn) used in the Genetic Algorithm (GA) to obtain the optimized route from those routes offered by the Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol. Accordingly, we propose a routing protocol titled as AOMDV with FFn (AOMDV-FFn). We also integrate the AOMDV mechanism with the genetic algorithm (AOMDV-GA). These protocols provide an optimization process to select the efficient routes that have the highest fitness values implementing the shortest route, maximum residual energy, and less data traffic even if a random loss of data packets happens. In this regard, we introduce a mechanism where the TCP Congestion Control Enhancement for Random Loss (TCP CERL) can be utilized in the FFn to optimize the efficient route. The performance of the proposed mechanisms is compared with other preferred protocols proposed in this area. INDEX TERMS congestion control, energy-efficient protocol, fitness function, genetic algorithm, mobile ad hoc network, multipath routing, shortest distance.

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“…Another case is that EN j receives µ sr and also µ d from S i but the quality of service of the network is not up to the mark [57]. EN j is a powerful node which can keep the quality of the communication up to the mark [57]. For example, SH A k may forward the UDP packets but not the TCP packets.…”

Section: Sinkhole Attacker Node Confirmation Algorithm In Eiotmentioning

confidence: 99%

“…If the integrity does not hold, S i is treated as the SH A k which has modified µ d . • Case 4: EN j receives µ sr and also µ d from S i , but the quality of service of the network is not up to the mark [57]. Since EN j is a powerful node, it can run some technique to maintain the quality of the service of the network [57].…”

mentioning

confidence: 99%

Designing Efficient Sinkhole Attack Detection Mechanism in Edge-Based IoT Deployment

Pundir

Wazid

Singh

et al. 2020

Sensors

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The sinkhole attack in an edge-based Internet of Things (IoT) environment (EIoT) can devastate and ruin the whole functioning of the communication. The sinkhole attacker nodes ( S H A s) have some properties (for example, they first attract the other normal nodes for the shortest path to the destination and when normal nodes initiate the process of sending their packets through that path (i.e., via S H A ), the attacker nodes start disrupting the traffic flow of the network). In the presence of S H A s, the destination (for example, sink node i.e., gateway/base station) does not receive the required information or it may receive partial or modified information. This results in reduction of the network performance and degradation in efficiency and reliability of the communication. In the presence of such an attack, the throughput decreases, end-to-end delay increases and packet delivery ratio decreases. Moreover, it may harm other network performance parameters. Hence, it becomes extremely essential to provide an effective and competent scheme to mitigate this attack in EIoT. In this paper, an intrusion detection scheme to protect EIoT environment against sinkhole attack is proposed, which is named as SAD-EIoT. In SAD-EIoT, the resource rich edge nodes (edge servers) perform the detection of different types of sinkhole attacker nodes with the help of exchanging messages. The practical demonstration of SAD-EIoT is also provided using the well known NS2 simulator to compute the various performance parameters. Additionally, the security analysis of SAD-EIoT is conducted to prove its resiliency against various types of S H A s. SAD-EIoT achieves around 95.83 % detection rate and 1.03 % false positive rate, which are considerably better than other related existing schemes. Apart from those, SAD-EIoT is proficient with respect to computation and communication costs. Eventually, SAD-EIoT will be a suitable match for those applications which can be used in critical and sensitive operations (for example, surveillance, security and monitoring systems).

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A Congestion-Aware Clustering and Routing (CCR) Protocol for Mitigating Congestion in WSN

Cited by 42 publications

References 29 publications

MWCSGA—Multi Weight Chicken Swarm Based Genetic Algorithm for Energy Efficient Clustered Wireless Sensor Network

MWCSGA—Multi Weight Chicken Swarm Based Genetic Algorithm for Energy Efficient Clustered Wireless Sensor Network

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

Designing Efficient Sinkhole Attack Detection Mechanism in Edge-Based IoT Deployment

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