A Fuzzy-Hierarchical Routing Algorithm for MANET Networks Allocation Rates Problem

Garaaghaji, Ali; Alfi, Alireza

doi:10.1007/s40998-019-00253-z

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…Attacker detection automation of Bees Colony Optimization (ADABCP) was developed to overcome route optimization concerns on the MANET against rushing assaults. Route Organization and Route Reorganization are two steps of the ADABCP [ 22 , 83 ]. A significant data stream is evaluated while defining Route Organization, which gets values for numerous mobile node attributes.…”

Section: Routing Protocols Communication For Rushing Attacker Detectionmentioning

confidence: 99%

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Efficient Mobile Ad Hoc Route Maintenance Against Social Distances Using Attacker Detection Automation

Allimuthu

Mahalakshmi

2022

Mobile Netw Appl

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In MANET, routing plays a vital role in packet interaction and data transmission. It is always easy to manage the data transmission over the MANET because of uncentralized control on the MANET nodes. Since the efficient route on MANET controls the packets and does not simplify the route between the source and destination. Hence the maintenance of route interaction becomes a crucial process. Methods: It is critical to enhance the route and decrease the attacker to sustain successful data transfers via the MANET Network. MANET, on the other hand, permits route interaction with security threads. The four processing schema are proposed in this study work to retain the security safeguards against Routing Protocols. The Rushing Attacker has significantly influenced MANET packet-based data transfer, particularly node communication. The Attacker Detection Automation of Bee Colony Optimization (ADABCP) Method is proposed in this article. Results: Existing ESCT, ZRDM-LFPM, and ENM-LAC techniques were compared to the suggested outcome. Consequently, routing and data transfer have enhanced the proposed illustration (SIRT-ADABCP-HRLD). Compared to the recommended approach, the end-to-end latency, communication overhead, packet delivery ratio, network lifetime, and energy usage are all improved. Discussion: The performance evaluation results of SIRT–ADABCP-HRLD with existing methods in terms of low End to End Delay (ms) of 49.8361% compared to existing methods ESCT, ENM-LAC, and ZRDM-LFPM. In terms of low Communication Overhead, an 81.4462% decrease compared to existing methods. However, it improves packet delivery by 56.9775%, more than ESCT, ENM-LAC, and ZRDM-LFPM. The energy consumption decreased by 36.31% less value than the existing process.

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Section: Routing Protocols Communication For Rushing Attacker Detectionmentioning

confidence: 99%

“…They are regarded as the attacker. To remove the attacker (misbehavior extinct member) from the grocery shopping mall, by using manual removing [ 15 , 22 ]…”

Section: Introductionmentioning

confidence: 99%

Efficient Mobile Ad Hoc Route Maintenance Against Social Distances Using Attacker Detection Automation

Allimuthu

Mahalakshmi

2022

Mobile Netw Appl

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“…The destination node contains the details of the link establishment for each destination node. Network knowledge of each link with the present quality level helps distinguish malicious nodes and each routing node in the network environment [16]. In this era, some nodes get removed from the routing path based on packet transmission speed and routing speed-accuracy rate, and the quality of service paths provides help to any failure node.…”

Section: Use Best Approximationmentioning

confidence: 99%

Intelligent route discovery towards rushing attacks in ad hoc wireless networks

Allimuthu

Mahalakshmi

2021

J Ambient Intell Human Comput

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MANET (Mobile Ad-hoc Networks) are distributed or delegated away from a central server, authoritative location of wireless networks that communicate without pre-existing structure. Ad-hoc networks are compromising the many types of attacks and routing. In MANET, the routing plays a vital role in terms of packets interaction and data transmission. Due to decentralized control, the MANET data transmission becomes insecure because of dispersed routing on the mobile ad-hoc nodes. Since the efficient route on MANET only controls the packets and does not simplify the route between the source to the destination, the maintenance of route interaction becomes a crucial process. Maintain effective data transactions over the MANET network, and it is essential to improve the route and locate the attacker. Nevertheless, MANET allows for route interaction against security threads. In this research article, four processing schemes are suggested to preserve the security measures against routing protocols. Especially in node communication, the rushing attacker has a significant impact on packet-based data transmission in MANET. Also, for this research, an Attacker detection automation of the Bees Colony Optimization (ADABCP) method is used, as a result of which the desired result is brought about in the effective attacker detection on the routing process. Moreover, the proposed Hybrid Random Late Detection (HRLD) routing protocol manages the MANET routing and overcomes the MANET congestion communication. The Swift Implicit Response Round Trip Time (SIRT) mechanism is generated by the Route Finding Manipulation (RFM) to enhance the performance. This RFM scheme helps to find the optimal routing in a secured manner. The proposed (SIRT-ADABCP-HRLD) approach was compared to the existing ESCT, ZRDM-LFPM, and ENM-LAC approaches, found to have improved by routing and data transmission. Compared to the conventional method, the method mentioned above achieves a better ratio for the end-to-end delay, communication overhead, packet delivery ratio, network lifetime, and energy consumption.

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“…16,17 For optimization, environmentally motivated algorithms are strategies, which mimic the effectiveness of nature. Because of their benefits, these sorts of algorithms can tackle a wide range of issues 18,19 : To begin, we do not need to use specific mathematical methodologies to arrive at a solution. 20 Consequently, the findings are quick as well as precise.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Mobile Ad Hoc Network cluster based routing: Energy prediction via improved deep learning technique

Murugan,

Unhelkar

2024

Int J Communication

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SummaryMobile Ad Hoc Network (MANETs) are indeed autonomous, fast‐deployable wireless networks that are ideal for communications in areas with limited radio infrastructure, outdoor events, military operations, and disaster relief. But the primary problem is with routing because of the nodes' mobility. This paper proposes a cluster‐based routing under energy prediction via deep learning techniques. Here, proposes a new model termed as Concatenation of Convolutional with Max‐Avg Pooling layer in Deep Convolutional Neural Network (CCMAP‐DCNN) for energy prediction, in which additional layers are inserted into the extant DCNN structure to ensure the effectiveness of energy prediction. As a result, clusters are created by grouping the nodes together. Constraints like energy, trust, distance, and latency are taken into account while choosing the cluster leader. For cluster head selection and optimal routing, proposes a new hybrid Namib Beetle Upgraded Jellyfish Search Optimization (NBUJSO) algorithm that utilizes the NBO strategy to the JSO algorithm making the selection process more optimal. The best route is then chosen by the optimum routing method, which takes into account variables like network quality and mobility to send data packets from source to destination as efficiently as possible. Finally, the data aggregation process is followed for eliminating the redundant transmission.

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A Fuzzy-Hierarchical Routing Algorithm for MANET Networks Allocation Rates Problem

Cited by 5 publications

References 19 publications

Efficient Mobile Ad Hoc Route Maintenance Against Social Distances Using Attacker Detection Automation

Efficient Mobile Ad Hoc Route Maintenance Against Social Distances Using Attacker Detection Automation

Intelligent route discovery towards rushing attacks in ad hoc wireless networks

Optimizing Mobile Ad Hoc Network cluster based routing: Energy prediction via improved deep learning technique

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