scholarly journals The Impact of Radio Propagation Models on Ad Hoc Networks Performances

2012 ◽  
Vol 8 (5) ◽  
pp. 752-760 ◽  
Author(s):  
Rhattoy
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Radio Propagation ◽  
Propagation Models ◽  
Hoc Networks ◽  
The Impact

Radio Propagation Models: A Performance Analysis based Impact of Sparse and Dense Deployment of Nodes under Different Propagation Models in Mobile Ad-hoc Networks (MANETs)

2021 ◽  
Author(s):  
Altaf Hussain ◽  
Muhammad Rafiq Khan
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Signal Strength ◽  
Propagation Model ◽  
Strong Impact ◽  
Propagation Models ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
The Impact

Abstract Mobile Ad-hoc Network (MANET) is the most emerging and fast expanding technology since the last two decades. One of the major issue and challenging area in MANET is the process of routing due to dynamic topologies and high mobility of mobile nodes. The exchange of information from source to a destination is known as the process of routing. Spectacular amount of attention has been paid by researchers to reliable routing in ad-hoc networks. Efficiency and accuracy of a protocol depends on many parameters in these networks. In addition to other parameters node velocity and propagation models are among them. Calculating signal strength at receiver is the responsibility of a propagation model while mobility of nodes is responsible for topology of the network. A huge amount of loss in performance is occurred due to variation of signal strength at receiver and obstacles between transmissions. Simulation tools are developed to analyze the weakness and strength of protocols along with different parameters that may impact the performance. The choice of a propagation models have an abundant effect on performance on routing protocols in MANET. In this research, it has been analyzed to check the impact of different propagation models on the performance of Optimized Link State Routing (OLSR) in Sparse and Dense scenarios in MANET. The simulation has been carried out in NS-2 by using performance metrics as average Throughput, average packet drop and average latency. The results predicted that propagation models and mobility has a strong impact on the performance of OLSR in considered scenarios.

A Survey on Obstacle Modeling Patterns in Radio Propagation Models for Vehicular Ad Hoc Networks

2015 ◽  
Vol 40 (5) ◽  
pp. 1385-1407 ◽  
Author(s):  
Muhammad Ahsan Qureshi ◽  
Rafidah Md Noor ◽  
Shahaboddin Shamshirband ◽  
Sharmin Parveen ◽  
Muhammad Shiraz ◽  
...  
Keyword(s):  
Ad Hoc Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Radio Propagation ◽  
Propagation Models ◽  
Hoc Networks

Effects of Propagation Models on AODV in Mobile Ad-hoc Networks

2014 ◽  
Vol 79 (1) ◽  
pp. 389-403 ◽  
Author(s):  
Ashok M. Kanthe ◽  
Dina Simunic ◽  
Ramjee Prasad
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Propagation Models ◽  
Mobile Ad Hoc ◽  
Hoc Networks

scholarly journals Flying Ad Hoc Networks: A New Domain for Network Communications

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3571 ◽  
Author(s):  
Antonio Guillen-Perez ◽  
Maria-Dolores Cano
Keyword(s):  
Ad Hoc Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Added Value ◽  
Research Activities ◽  
Communication Links ◽  
Communication Devices ◽  
Hoc Networks ◽  
5 Ghz ◽  
The Impact

The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links.

The Impact of Delay in Dominating Set and Neighbor Elimination Based Broadcasting in Ad Hoc Networks

2007 ◽  
pp. 115-128
Author(s):  
Fabián García-Nocetti ◽  
Francisco Javier Ovalle-Martínez ◽  
Julio Solano-González ◽  
Ivan Stojmenović
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Dominating Set ◽  
Hoc Networks ◽  
The Impact

On the Impact of Network Dynamics on a Discovery Protocol for Ad-Hoc Networks

2010 ◽  
pp. 1595-1613
Author(s):  
Fei Liu ◽  
Geert Heijenk
Keyword(s):  
Ad Hoc Networks ◽  
Linear Relation ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Network Dynamics ◽  
Bloom Filters ◽  
Context Information ◽  
Node Density ◽  
Hoc Networks ◽  
The Impact

A very promising approach to discovering services and context information in ad-hoc networks is based on the use of Attenuated Bloom filters. In this paper we analyze the impact of changes in the connectivity of an ad-hoc network on this approach. We evaluate the performance of the discovery protocol while nodes appear, disappear, and move, through analytical and simulative analysis. The analytical results are shown to be accurate when node density is high. We show that an almost linear relation exists between the density of the network and the number of update messages to be exchanged. Further, in case of nodes moving, the number of messages exchanged does not increase with the speed of movement.

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