scholarly journals Modifying the MANET Routing algorithm by GBR CNR-Efficient Neighbor Selection Algorithm

2019 ◽  
Vol 8 (10) ◽  
pp. 912-917
Keyword(s):  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Routing Algorithm ◽  
Packet Transmission ◽  
Mobile Nodes ◽  
Routing Overhead ◽  
End To End Delay ◽  
Stay Time ◽  
End To End ◽  
Neighbor Selection

In today’s worlds, Mobile Ad-Hoc Network (MANET) plays most important role in the field networks technology in the world. The MANET has been rapidly rising and becoming significant from the last decade. A MANET is a kind of wireless network which has been set-up without requirement of fixed infrastructure where mobile nodes are connected over wireless link. Due to moving nature of the devices, the network topology is unstable and will change dynamically. That’s why stable routing in MANET cannot work properly. In this research paper, a new routing algorithm is proposed to get better routing performance in the MANET. The proposed algorithm designed based on the number of neighbors in the network. Planned algorithm is the improvement of GBR-CNR-LN (GBR-CNR with less neighbors) by calculating the stay time between the selected neighbor nodes and the transmission nodes. If the stay time of sender node is more than the packet transmission time then the selected node is the efficient neighbor selection. The algorithm is implemented and results are analyzed. The results of this paper show the usefulness of the proposed algorithm. The Evaluation of AODV protocol was carried out using Python and outcome of this evaluation showed that proposed Algorithm gave better results than GBR-CNR with less neighbor in terms of End-to-End delay, Number of control message transferred(Routing Overhead) and Network Load. The proposed Algorithm (GC-ENS) decrease Average End-to-End delay 52.54 %, reduce Average Routing Overhead 60.54% and decline the Average load on Network 61.17%.

scholarly journals Routing Algorithm To Eliminate Stale Routes (RAESR) In Mobile Ad Hoc Networks

2019 ◽  
Vol 8 (12) ◽  
pp. 4503-4509
Keyword(s):  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Routing Algorithm ◽  
High Mobility ◽  
Propagation Delay ◽  
Link Failure ◽  
Mobile Nodes ◽  
Routing Overhead ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Mobile Ad-hoc Network (MANET) is a collection of self sustaining mobile nodes which are connected through many wi-fi links to form a temporary communication for sharing information between the users. Mobile nodes behave as a host as well as router. As nodes in MANET posse’s mobility in traits frequently leads to irregular link between the nodes. Link failure directs a significant routing overhead during high mobility and also maintaining all the information associated with nodes and routing paths are considered as an extra overhead on the table. In order to overcome these issues, the routing algorithm to eliminate stare routed in routing cache. The neighbor degree centrality table is introduced to recognize the valuable nodes, using the valuable nodes the routes are discovered and link failure information are disseminated across the network wide. The results and findings show that the elimination of stale routes leads to significant reduction in routing overhead which in turn reduces the route error propagation delay

scholarly journals ANT COLONY OPTIMIZED ROUTING FOR MOBILE ADHOC NETWORKS (MANET)

2013 ◽  
pp. 218-223
Author(s):  
DWEEPNA GARG ◽  
PARTH GOHIL
Keyword(s):  
Swarm Intelligence ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Node Mobility ◽  
Mobile Nodes ◽  
Ant Colony Algorithms ◽  
Mobile Ad Hoc ◽  
Hoc Networks

A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network without using centralized access points, infrastructure, or centralized administration. Routing means the act of moving information across an internet work from a source to a destination. The biggest challenge in this kind of networks is to find a path between the communication end points, what is aggravated through the node mobility. In this paper we present a new routing algorithm for mobile, multi-hop ad-hoc networks. The protocol is based on swarm intelligence. Ant colony algorithms are a subset of swarm intelligence and consider the ability of simple ants to solve complex problems by cooperation. The introduced routing protocol is well adaptive, efficient and scalable. The main goal in the design of the protocol is to reduce the overhead for routing. We refer to the protocol as the Ant Colony Optimization Routing (ACOR).

Research and Improvement of Clustering Routing Algorithm in Ad Hoc Network

2013 ◽  
Vol 834-836 ◽  
pp. 1087-1090
Author(s):  
Ping Zong ◽  
Jun Qin
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Ad Hoc Network ◽  
Ant Colony Algorithm ◽  
Ad Hoc ◽  
Routing Algorithm ◽  
Routing Overhead ◽  
End To End Delay ◽  
The Impact ◽  
Network Scalability

With the expansion of the network, especially in the case of the nodes frequently moving, clustering routing protocol can reduce the impact of the changed topology on routing protocols, and improve the network scalability and reduce routing overhead. Based on the analysis of the problems of CBRP clustering routing protocol, this paper presents a CRBAC clustering routing algorithm based on ant colony algorithm. The simulation results show that, in the circumstance that the algorithm doesnt significantly increase the routing overhead, improved clustering routing protocol CRBAC get better performance than CBRP. They reflect on the clusters structure more reasonable and stable, the average end-to-end delay and network lifetime significantly improved.

scholarly journals Increased Routing Algorithm for Mobile AdHoc Networks

2019 ◽  
Vol 8 (9S3) ◽  
pp. 1606-1608
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Routing Algorithm ◽  
Mobile Adhoc Networks ◽  
Adhoc Networks ◽  
Mobile Ad Hoc ◽  
End To End ◽  
Two Stages

A Mobile Ad-hoc Network (MANET) is an accumulation of portable hubs which impart over proportion. These systems have an essential preferred standpoint; they don't require any current foundation or focal organization. Portable specially appointed systems are appropriate for transitory correspondence joins. One of the significant issues in MANET is steering because of the versatility of the hubs. Directing means the demonstration of moving data over a web work from a source to a goal. The Enhanced Ant Routing Algorithm (EARA) depends on subterranean insect calculations. This calculation is enlivened from the insect states life. Forward bundles are utilized to gather data about the system and in reverse parcels are utilized to refresh the directing data in the hubs. EARA has two stages course disclosure and course support and furthermore utilities the idea of backtracking when the parcels are achieves goal hub. Re-enactment comes about accomplish better parcel conveyance proportion and lessen the normal end-to-end defer as contrast with its partner

scholarly journals Performance Analysis of DSR and TORA Model Routing Protocols In Vehicular Ad Hoc Network

2020 ◽  
Vol 3 (3) ◽  
pp. 94-99
Author(s):  
Linna Oktaviana Sari ◽  
Agusurio Azmi ◽  
Ery Safrianti ◽  
Feranita Jalil
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Routing Algorithm ◽  
Vehicular Ad Hoc Network ◽  
Delivery Ratio ◽  
Large Area ◽  
Packet Delivery ◽  
End To End Delay ◽  
End To End

Pekanbaru city is a large area, therefore traffic congestion often occurs due to the density of society’s vehicles. From this problem, it is needed a technology that can exchange information between vehicles. Information Technology that can involve many vehicles with special network types without dependence on an infrastructure is Ad Hoc Network. One type of this network is Vehicular Ad Hoc Network (VANET). VANET is a new concept in enabling communication between Vehicle to Vehicle (V2V). For efficient data packet delivery, VANET requires a routing protocol. In this research, for simulated and analyzed performance is used the Dynamic Source Routing (DSR) and Temporally Ordered Routing Algorithm (TORA) protocol. NS-2 is used to simulated a moved nodes, SUMO software is used to simulated real map of SKA Mall crossroad and parameter the quality of performance routing protocol DSR can determined by End to End Delay, Packet Delivery Ratio (PDR) and Routing Overhead (RO). This simulation uses scenario 100 nodes, 150 nodes, 200 nodes and 250 nodes. The simulation results with the scenario of changing the number of nodes, the DSR routing protocol produces better performance with an average of  End to End Delay is 0.1066 s, average of PDR is 95.45% and average of RO is 1.0076. While the TORA routing protocol has an average of End to End Delay is 0.1163s, average of PDR is 93.49% and average of RO is 1.0801. And in the scenario of node speed changes, the TORA routing protocol produces better performance with an average of End to End Delay is 0.0861 s and average of PDR 97.37%. While the DSR routing protocol is better with an average of RO is 1.0076.

scholarly journals Pencarian Rute yang Handal Berbasis Energi Menggunakan Algoritma EA-SHORT pada Protokol Routing ZRP di Jaringan MANET

2021 ◽  
Vol 3 (1) ◽  
pp. 31-42
Author(s):  
Mila Rosiana ◽  
Andy Hidayat Jatmika ◽  
Ariyan Zubaidi
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Energy Aware ◽  
Zone Routing Protocol ◽  
End To End Delay ◽  
Mobile Ad Hoc ◽  
End To End

Mobile Ad-Hoc Network (MANET) adalah jaringan wireless dari kumpulan node yang tidak memiliki router tetap. Setiap node dalam jaringan bertindak sebagai router yang bertanggung jawab untuk menemukan dan menangani rute antar node. Dalam penelitian ini, konsep energy aware menggunakan algoritma EA-SHORT diterapkan pada kerangka kerja Zone Routing Protocol (ZRP). EA-SHORT mencoba mendistribusikan beban jaringan ke semua node yang ada dengan memanfaatkan variasi jumlah energi dengan memilih node yang memiliki cukup energi yang dapat berpartisipasi dalam rute dan menghindari node yang memiliki energi rendah. Kinerja ZRP akan dibandingkan dengan EA-SHORT ZRP yang telah dimodifikasi dengan EA-SHORT yang diukur dari nilai parameter yang ditentukan. Dari simulasi, hasilnya menunjukkan, pada node 50, throughput meningkat sebesar 12,374%. Untuk 100 node, peningkatan sebesar 44.597%. Pada rata-rata average end to end delay , dengan 50 node, nilai EA-SHORT ZRP menurun sebesar 20.063%, 100 node EA-SHORT ZRP menurun sebesar 8.375%. Hasil PDR pada EA-SHORT ZRP dengan 50 node meningkat 0,545%, dan untuk EA-SHORT ZRP 100 node meningkat sebesar 21,301%

A Beaconless Minimum Interference Based Routing Protocol to Minimize End-to-End Delay per Packet for Mobile Ad hoc Networks

2010 ◽  
Vol 2 (1) ◽  
pp. 12-26 ◽  
Author(s):  
Natarajan Meghanathan ◽  
Meena Sugumar
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Network Routing ◽  
Data Packet ◽  
End To End Delay ◽  
Mobile Ad Hoc ◽  
End To End ◽  
Index Value ◽  
Minimum Interference

The authors propose a beaconless, on-demand, mobile ad hoc network routing protocol called minimum interference based routing protocol (MIF) that minimizes the end-to-end delay per data packet. During route discovery, each node inserts its identification and location information before broadcasting the Route-Request (RREQ) message in its neighborhood. The weight of a link, called the interference index, is the number of interfering links surrounding it. Two links are said to interfere with each other, if the distance between the mid points of the two links is within the interference range. The interference index of a path is the sum of the interference index values of the constituent links. The destination selects the path with the minimum interference index value and notifies the source through the Route-Reply packet. Simulation results demonstrate that MIF incurs a significant reduction in the end-to-end delay per data packet vis-à-vis the interference-aware load balancing routing protocol.

Quality of Service (QoS) Routing in Mobile Ad Hoc Networks

2010 ◽  
pp. 464-496
Author(s):  
R. Asokan ◽  
A. M. Natarajan
Keyword(s):  
Quality Of Service ◽  
Ad Hoc ◽  
Qos Routing ◽  
Qos Provisioning ◽  
Mobile Nodes ◽  
Delay Jitter ◽  
End To End Delay ◽  
Mobile Ad Hoc ◽  
End To End

A Mobile Ad hoc NETwork (MANET) consists of a collection of mobile nodes. They communicate in a multi-hop way without a formal infrastructure. Owing to the uniqueness such as easy deployment and self-organizing ability, MANET has shown great potential in several civil and military applications. As MANETs are gaining popularity day-by-day, new developments in the area of real time and multimedia applications are increasing as well. Such applications require Quality of Service (QoS) evolving with respect to bandwidth, end-to-end delay, jitter, energy etc. Consequently, it becomes necessary for MANETs to have an efficient routing and a QoS mechanism to support new applications. QoS provisioning for MANET can be achieved over different layers, starting from the physical layer up to the application layer. This chapter mainly concentrates on the problem of QoS provisioning in the perception of network layer. QoS routing aims at finding a feasible path, which satisfies QoS considering bandwidth, end-to-end delay, jitter, energy etc. This chapter provides a detailed survey of major contributions in QoS routing in MANETs. A few proposals on the QoS routing using optimization techniques and inter-layer approaches have also been addressed. Finally, it concludes with a discussion on the future directions and challenges in QoS routing support in MANETs.

Hybrid AODV: An Efficient Routing Protocol for Manet Using MFR and Firefly Optimization Technique

2021 ◽  
pp. 2150004
Author(s):  
ANKUR GOYAL ◽  
VIVEK KUMAR SHARMA ◽  
SANDEEP KUMAR ◽  
RAMESH CHANDRA POONIA
Keyword(s):  
Shortest Path ◽  
Ad Hoc ◽  
Optimization Technique ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Self Healing ◽  
Routing Overhead ◽  
Packet Delivery ◽  
End To End Delay ◽  
End To End

A MANET is a category of ad hoc protocol that could vary positions and track itself on the flutter. It utilizes wireless connections that are attached to several networks. They include wirelessly in a self-configured, self-healing network while not having permanent communication linked in a collection of mobile networks. The network topology of nodes typically varies in MANET, and nodes are free to stir errantly and independently as a router as they accelerate traffic to more nodes within the network. Ad hoc on-demand distance vector (AODV) was employed for node selection to attain the shortest path strategy in existing techniques. In the proposed system, the hybrid AODV (HAODV) technique incorporates the MFR (Most Forward within Radius) technique to detect the shortest path routing algorithm. The MFR method was deployed for selecting the neighbor node, while HAODV was deployed to find the shortest path. To find the shortest path based on the updating equation, the Firefly algorithm is also implemented into the Hybrid AODV. The proposed work’s performance is calculated by different network parameters like the end to end delay, average routing overhead, throughput, and packet delivery ratio. After comparing AODV and DSR algorithms, the proposed algorithm (HAODV) shows improvement in packet delivery ratio, end-to-end delay, Routing overhead, and throughput.

T-Whale

2018 ◽  
Vol 8 (2) ◽  
pp. 67-79 ◽  
Author(s):  
Ch.Ram Mohan ◽  
A. Venugopal Reddy
Keyword(s):  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Search Algorithm ◽  
Random Search ◽  
Routing Algorithm ◽  
Optimal Path ◽  
Data Encryption ◽  
Secure Routing ◽  
Mobile Nodes ◽  
Whale Optimization

One of the infrastructureless networks built by various independent mobile nodes is mobile ad hoc network (MANET), which is an emerging technology, requiring a secure routing protocol for data transmission. Accordingly, literature presents various secure routing protocols for MANETs by utilizing trust and data encryption. In this article, a whale optimization algorithm (WOA) is utilized for selecting the optimal secured routing path in the MANET. The WOA algorithm utilizes the trust factor and the distance between the nodes for computing the fitness for the routing path. Overall, the steps involved in the proposed routing algorithm are as follows: i) Measuring the trust and the distance-based metrics for every node; ii) Discovering k-disjoint path; and iii) Determining the optimal path based on the trust and the distance-based metrics. The performance of the trust-based WOA (T-Whale) is analyzed using the metrics, energy, throughput, and packet delivery rate. From the simulation results, it is evident that the T-Whale algorithm has the improved energy, throughput, and PDR values of 27.4520, 0.4, and 0.4, at the simulation time of 10 sec over the conventional trust random search algorithm when the node is under attack.

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