AODV route maintenance using HoneyPots in MANETs

2015 ◽  
Author(s):  
T. Divya Sai Keerthi ◽  
Pallapa Venkataram
Keyword(s):  
Route Maintenance

scholarly journals A Bioinspired Adaptive Congestion-Avoidance Routing for Mobile Ad Hoc Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Huang Qiong ◽  
Yin Pengfei ◽  
Chen Qianbin ◽  
Gong Pu ◽  
Yang Xiaolong
Keyword(s):  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Threshold Value ◽  
Recovery Phase ◽  
Network Routing ◽  
Delivery Ratio ◽  
Route Maintenance ◽  
Random Manner ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Traditional mobile Ad Hoc network routing protocols are mainly based on the Shortest Path, which possibly results in many congestion nodes that incur routing instability and rerouting. To mitigate the side-efforts, this paper proposed a new bioinspired adaptive routing protocol (ATAR) based on a mathematics biology model ARAS. This paper improved the ARAS by reducing the randomness and by introducing a new routing-decision metric “the next-hop fitness” which was denoted as the congestion level of node and the length of routing path. In the route maintenance, the nodes decide to forward the data to next node according to a threshold value of the fitness. In the recovery phase, the node will adopt random manner to select the neighbor as the next hop by calculation of the improved ARAS. With this route mechanism, the ATAR could adaptively circumvent the congestion nodes and the rerouting action is taken in advance. Theoretical analysis and numerical simulation results show that the ATAR protocol outperforms AODV and MARAS in terms of delivery ratio, ETE delay, and the complexity. In particular, ATAR can efficiently mitigate the congestion.

Adaptive-Sunflower Based Grey Wolf Algorithm For Multipath Routing In Iot Network

2021 ◽  
Vol 17 (2) ◽  
pp. 0-0
Keyword(s):  
Fitness Function ◽  
Optimization Technique ◽  
Multipath Routing ◽  
High Energy ◽  
Grey Wolf ◽  
Maximum Throughput ◽  
Route Maintenance ◽  
Bee Colony ◽  
Direct Trust ◽  
Indirect Trust

This paper devises a routing method for providing multipath routing inan IoT network. Here the Fractional Artificial Bee colony(FABC)algorithm is devised for initiating clustering process. Moreover the multipath routing is performed by the newly devised optimization technique, namely Adaptive-Sunflower based grey wolf(Adaptive-SFG)optimization technique which is designed by incorporating adaptive idea in Sunflower based grey wolf technique. In addition the fitness function is newly devised by considering certain factors that involves Context awareness, link lifetime Energy, Trust, and Delay.For the computation of the trust, additional trust factors like direct trust indirect trust recent trust and forwarding rate factor is considered. Thus, the proposed Adaptive SFG algorithm selects the multipath for routing based on the fitness function.Finally, route maintenance is performed to ensure routing without link breakage.The proposed Adaptive-SFG outperformed other methods with high energy of0.185Jminimal delay of 0.765sec maximum throughput of47.690%and maximum network lifetime of98.7%.

Brain Storm Water Optimisation-Driven Secure Multicast Routing and Route Maintenance in IoT

2021 ◽  
Vol 20 (Supp01) ◽  
pp. 2140010
Author(s):  
Jacob John ◽  
S. Sakthivel
Keyword(s):  
Quality Factor ◽  
Routing Protocol ◽  
Multicast Routing ◽  
Link Quality ◽  
Source Node ◽  
Storm Water ◽  
Route Maintenance ◽  
Optimisation Algorithm ◽  
Multicast Routing Protocol ◽  
Routing Mechanism

In several Internet of Things (IoT) applications, messages are disseminated to some objects or nodes based on multicast transmissions. However, previous multicast routing schemes in IoT focussed mainly on the ad-hoc sensor network, but they are not robust and responsive in the IoT environment. Hence, this paper introduces the multicast routing protocol based on the proposed optimisation algorithm, named Brain Storm Water Optimisation (BSWO), in the IoT network. By the multicast routing protocol, the multicast path is designed from a multicast source node to various destinations. The multicast source node forwards packet to multiple destinations simultaneously. Initially, the nodes in the IoT network are simulated together and perform the multicast routing process effectively using the proposed optimisation framework. The multicast routing protocol performs the multicast routing mechanism using the multiobjective factors, such as distance, delay, energy, link-quality factor and trust. The multicast routing path is effectively chosen based on the developed BSWO through fitness measures. The proposed BSWO is designed by integrating the Brain Storm Optimisation (BSO) and Water Wave Optimisation (WWO), respectively. The path with the minimum distance is selected as an optimal path using the fitness parameters like delay, distance, trust, energy and link-quality factor. The proposed optimisation algorithm effectively performs the multicast routing mechanism by integrating the parametric features from both the optimisation algorithms. Once the multicast routing mechanism is done, the route maintenance process is carried out in the simulated IoT network to recover the link breakage. The proposed BSWO outperformed other methods with the minimal delay of 0.0682[Formula: see text]s, minimal average routing distance of 178.4[Formula: see text]m, maximal energy of 39.59[Formula: see text]J, maximal throughput of 87.75% and maximal trust of 90%, respectively.

The Robustness of RM-DSR Multipath Routing Protocol with Different Network Size in MANET

2013 ◽  
Vol 5 (2) ◽  
pp. 46-57
Author(s):  
Naseer Ali Husieen ◽  
Suhaidi Hassan ◽  
Osman Ghazali ◽  
Lelyzar Siregar
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Mobility Model ◽  
Network Size ◽  
Delivery Ratio ◽  
Network Simulator ◽  
Mobile Nodes ◽  
Route Maintenance ◽  
Dynamic Source

This paper evaluates the performance of Reliable Multipath Dynamic Source Routing Protocol (RM-DSR) protocol with different network size compared to DSR protocol. RM-DSR developed in the mobile ad-hoc network to recover from the transient failure quickly and divert the data packets into a new route before the link is disconnected. The performance of RM-DSR protocol is tested in the Network Simulator (NS-2.34) under the random way point mobility model with varying number of mobile nodes. The network size parameter is used to investigate the robustness and the efficiency of RM-DSR protocol compared to DSR protocol. The network size affects the time of the route discovery process during the route establishment and the route maintenance process which could influence the overall performance of the routing protocol. The simulation results indicate that RM-DSR outperforms DSR in terms of the packet delivery ratio, routing overhead, end-to-end delay, normalized routing load and packet drop.

Istanbul Grand Bazaar Evacuation System Vulnerability Assessment

2010 ◽  
Vol 133-134 ◽  
pp. 611-616 ◽  
Author(s):  
Gül Yücel ◽  
Görün Arun
Keyword(s):  
Vulnerability Assessment ◽  
Hazardous Materials ◽  
Emergency Evacuation ◽  
Vulnerability Factors ◽  
Route Maintenance ◽  
System Vulnerability ◽  
Exit Route ◽  
Safety Evacuation ◽  
Evacuation Route ◽  
Evacuation System

The Grand Bazaar is a historical trade centre more than 500 years in the historical peninsula of Istanbul, Turkey. It consists of almost 3,600 small shops from different sectors (such as jewellery, carpet, leather, souvenir, finance, restaurant, café, confection etc.), two Bedesten, 64 street and 16 Han (inn) buildings. The Bazaar has 21 main gates that open to different streets and have different relation with outside. More than 25000 staff work in the shops and 300-500 thousand users come to Bazaar daily depending on the season and day. The pedestrian density is changeable, depending on the place of the inner street and the type of the sector. The historical disaster records (earthquake, dated 1766 and 1894, the grand bazaar fire, dated 1954) show that there was evacuation vulnerability. The main gates (exit doors) and exit route need some rehabilitation for safety evacuation during any disaster. The aim of this study is to evaluate the Grand Bazaar’s emergency evacuation vulnerability. The evacuation vulnerability factors question the width, length and natural illumination of the evacuation route, maintenance of the roof, presence of hazardous materials, door specifications as size, material, opening direction, maintenance and difference in elevation on the route and exit area such as staircase and thresholds.

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