Modifikasi Route Discovery pada Ad-hoc On Demand Distance Vector (AODV) Berdasarkan Level Konektivitas One-Hop Node di VANETs

The unstable areas caused by radio interference or rapidly change of nodes' location always emerge inevitably and unpredictably in the WSN (Wireless Sensor Network) of large scale. They may seriously hinder the route discovery procedures in the network. An improved routing strategy named AONDVjr (Ad hoc On-demand Navigated Distance Vector Junior) which keeps monitoring and exploiting unstable areas in ZigBee networks is proposed in this paper. This scheme selects navigation nodes at the borders of unstable areas by comparing and analyzing the parameters including area stability and node’s depth. The navigation nodes will provide source nodes with latest and short routes through unstable areas and forward data packets to sink node.

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Enhanced Route Discovery Mechanism of Ad-Hoc On Demand Distance Vector for MANET

International Journal of Computer Networks And Applications ◽

10.22247/ijcna/2016/48904 ◽

2016 ◽

Vol 3 (6) ◽

pp. 1

Author(s):

May Sayed A. Nouh ◽

Salwa H. El-ramly ◽

M. Zaki ◽

Husein A. A. Elsayed

Keyword(s):

Ad Hoc ◽

Route Discovery ◽

On Demand ◽

Distance Vector

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A novel routing protocol considering the boundary effects for ad hoc networks

International Journal of Distributed Sensor Networks ◽

10.1177/1550147720903635 ◽

2020 ◽

Vol 16 (1) ◽

pp. 155014772090363

Author(s):

Qingwen Wang ◽

Haitao Yu

Keyword(s):

Ad Hoc Networks ◽

Routing Protocol ◽

Ad Hoc ◽

Boundary Effects ◽

Node Degree ◽

Route Discovery ◽

Discovery Process ◽

On Demand ◽

Distance Vector ◽

Hoc Networks

To alleviate the broadcast storm problem in the route discovery process, this article proposes a novel routing protocol considering the boundary effects for ad hoc networks, named NRP. The novelty of NRP lies in the following: first, NRP defines a forwarding area criterion considering the effects of the node transmission area boundary to reduce the broken links due to the mobility of nodes; second, NRP adopts the idea of a piecewise function to estimate the node degree when the nodes are in the center, borderline, and corner areas, respectively, which considers the effects of both network boundaries and node communication boundaries without broadcasting Hello messages periodically; third, NRP applies the static game forwarding strategy to calculate the forwarding probability during the route discovery process. NRP reduces the redundant retransmissions and collision probability among neighboring nodes, thus improving the forwarding efficiency. The extensive simulation results by NS-2 simulator have shown that NRP performs better than AODV + FDG, AODV + Hello, ad hoc on-demand distance vector, ad hoc on-demand multipath distance vector, and energy-efficient ant-based routing in terms of packet delivery ratio, routing overhead, normalized medium access control load, throughput, and network lifetime.

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Improving Quality of Service Provisioning of Optimised Cuckoo Search Ad Hoc on-demand Distance Vector Routing Scheme for Cognitive Radio Ad Hoc Networks.

10.21203/rs.3.rs-952534/v1 ◽

2021 ◽

Author(s):

Ramahlapane Lerato Moila ◽

Mthulisi velempini

Keyword(s):

Cognitive Radio ◽

Ad Hoc ◽

Large Data ◽

Cuckoo Search ◽

Route Discovery ◽

Routing Problem ◽

On Demand ◽

Free Spectrum ◽

Spectrum Mobility ◽

Distance Vector

Abstract Spectrum mobility, cloud computing and the Internet of Things (IoTs) create large data sets, while the demand for more spectrum is increasing. Unfortunately, the spectrum is a scarce resource which is being underutilized by licensed users. The cognitive radio network, also known as intelligent radio, is a network that can adjust to environment changes and, detect available channels. It has emerged as a promising solution for the underutilization of the licensed spectrum and overcrowded free spectrum. Furthermore, given spectrum mobility, frequent link breakages impact negatively on the delivery of packets and the performance of the network. Hence there is need to address the routing problem. We therefore investigated which control methods can be utilized to improve the QoS provisioning in CRAHNs to minimize the signal overhead and to increase the achievable throughput.The study integrated the QoS requirements with optimized cuckoo search (OCS) algorithm to enhance the ad hoc on-demand distance vector (AODV) algorithm to establish a scheme we refer to as OCS-AODV. NS 2 simulation were run on Linux operating system. The comparative results show that the proposed scheme performed well in terms of end-to-end delay and throughput. However, the scheme does not backup alternative paths which can be used in the event of link breakages. The route discovery has to be re-initiated again. Though the route discovery process is faster because of the capability of the CS technique, it still degrades the performance of the scheme.

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