Q-learning Based Ad-Hoc Network Formation Strategy for Wireless Nodes with Random Mobility Models

2021 ◽  
Vol 46 (11) ◽  
pp. 1834-1845
Author(s):  
Nayoung Kim ◽  
Minhae Kwon ◽  
Hyunggon Park
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Network Formation ◽  
Mobility Models ◽  
Q Learning ◽  
Wireless Nodes

Analysis of Effective Routing Protocols for Flying Ad-Hoc Networks

2020 ◽  
Vol 3 (2) ◽  
pp. 1-18 ◽  
Author(s):  
Sudesh Kumar ◽  
Abhishek Bansal ◽  
Ram Shringar Raw
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
High Speed ◽  
Ad Hoc ◽  
Network Formation ◽  
High Mobility ◽  
Delivery Ratio ◽  
Data Packets ◽  
Hoc Networks ◽  
Networking Technology

Recently, the flying ad-hoc network (FANETs) is a popular networking technology used to create a wireless network through unmanned aerial vehicles (UAVs). In this network, the UAV nodes work as intermediate nodes that communicate with each other to transmit data packets over the network, in the absence of fixed an infrastructure. Due to high mobility degree of UAV nodes, network formation and deformation among the UAVs are very frequent. Therefore, effective routing is a more challenging issue in FANETs. This paper presents performance evaluations and comparisons of the popular topology-based routing protocol namely AODV and position-based routing protocol, namely LAR for high speed mobility as well as a verity of the density of UAV nodes in the FANETs environment through NS-2 simulator. The extensive simulation results have shown that LAR gives better performance than AODV significantly in terms of the packet delivery ratio, normalized routing overhead, end-to-end delay, and average throughput, which make it a more effective routing protocol for the highly dynamic nature of FANETs.

scholarly journals Link-state QoS routing protocol under various mobility models

2019 ◽  
Vol 16 (2) ◽  
pp. 906
Author(s):  
Safaa Laqtib ◽  
Khalid El Yassini ◽  
Moulay Lahcen Hasnaoui
Keyword(s):  
Steady State ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Mobility Model ◽  
Delivery Ratio ◽  
Mobility Models ◽  
Mobile Nodes ◽  
Link State ◽  
Random Waypoint

<p>Mobile Ad Hoc Network (MANET) consists of a group of mobile or wireless nodes that are placed randomly and dynamically that causes the continual change between nodes. A mobility model attempts to mimic the movement of real mobile nodes that change the speed and direction with time. The mobility model that accurately represents the characteristics of the mobile nodes in an ad hoc network is the key to examine whether a given protocol. The aim of this paper is to compare the performance of four different mobility models (i.e. Random Waypoint, Random Direction, Random walk, and Steady-State Random Waypoint) in MANET. These models were configured with Optimized Link State Routing (OLSR) protocol under three QoS (Quality of Service) <a title="Learn more about Metrics" href="https://www.sciencedirect.com/topics/engineering/metrics">metrics</a> such as the Packet Delivery Ratio (PDR), Throughput, End-to-End delay. The simulation results show the effectiveness of Steady-State Random Waypoint Mobility Models and encourage further investigations to extend it in order to guarantee other QoS requirements.</p>

Mobility and Traffic Model Analysis for Vehicular Ad-hoc Networks

2010 ◽  
pp. 214-232
Author(s):  
Shrirang Ambaji Kulkarni ◽  
G. Raghavendra Rao
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocol ◽  
Ad Hoc Network ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Mobility Model ◽  
Vehicular Ad Hoc Network ◽  
Traffic Model ◽  
Mobility Models ◽  
Hoc Networks

Vehicular Ad Hoc Networks represent a specialized application of Mobile Ad Hoc Networks. Here the mobile nodes move in lanes and their mobility can be modeled based on realistic traffic scenarios. To meet the above challenge the goal of defining the mobility model for vehicular ad hoc network along with a realistic traffic pattern is an important research area. Vehicular mobility is characterized by acceleration, deceleration, possibility of different lanes and intelligent driving patterns. Also a modeling of traffic is necessary to evaluate a vehicular ad hoc network in a highway environment. The traffic model has to take into account the driver behavior in order to take decisions of when to overtake, change lanes, accelerate and decelerate. To overcome the limitation of traditional mobility models and mimic traffic models, many traffic model based simulators like CORSIM, PARAMICS and MOVE have been proposed. In this chapter we provide taxonomy of mobility models and analyze their implications. To study the impact of mobility model on routing protocol for vehicular motion of nodes we analyze the performance of mobility models with suitable metrics and study their correlation with routing protocol. We also discuss the fundamentals of traffic engineering and provide an insight into traffic dynamics with the Intelligent Driver Model along with its lane changing behavior.

Performance Analysis of Traffic and Mobility Models on Mobile and Vehicular Ad Hoc Wireless Networks

2013 ◽  
pp. 305-313
Author(s):  
Lawal Bello ◽  
Panos Bakalis
Keyword(s):  
Communication Networks ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Transmission Control Protocol ◽  
Mobility Models ◽  
Bit Rate ◽  
Transmission Control ◽  
Transmission Control Protocols ◽  
Significant Performance

Advances in wireless communication technology and the proliferation of mobile devices enable the capabilities of communicating with each other even in areas with no pre-existing communication infrastructure. Traffic and mobility models play an important role in evaluating the performance of these communication networks. Despite criticism and assumption from various researches on Transmission Control Protocols (TCP), weaknesses on Mobile Ad Hoc Network (MANET), and Vehicular Ad Hoc Network (VANET). A simulation was carried out to evaluate the performance of Constant Bit Rate, Variable Bit Rate and Transmission Control Protocol on MANET and VANET using DSR routing protocol. CBR, VBR, and TCP have different manufacturer operation mechanisms and these differences lead to significant performance of CBR and VBR over TCP with better throughput and less average maximal end-to-end delay. DSR was able to respond to link failure at low mobility which led to TCP’s performance in packets delivery.

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