Disaster Relief Management Using Reinforcement Learning-Based Routing

2021 ◽  
Vol 17 (1) ◽  
pp. 24-37
Author(s):  
Gajanan Madhavrao Walunjkar ◽  
Anne Koteswara Rao ◽  
V. Srinivasa Rao
Keyword(s):  
Reinforcement Learning ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Average Energy ◽  
High Mobility ◽  
Adaptive Routing ◽  
Mobility Model ◽  
Delivery Ratio ◽  
Disaster Area ◽  
Disaster Scenario

Effective disaster management is required for the peoples who are trapped in the disaster scenario but unfortunately when disaster situation occurs the infrastructure support is no longer available to the rescue team. Ad hoc networks which are infrastructure-less networks can easily deploy in such situation. In disaster area mobility model, disaster area is divided into different zones such as incident zone, casualty treatment zones, transport areas, hospital zones, etc. Also, in order to tackle high mobility of nodes and frequent failure of links in a network, there is a need of adaptive routing protocol. Reinforcement learning is used to design such adaptive routing protocol which shows good improvement in packet delivery ratio, delay and average energy consumed.

scholarly journals Performance Evaluation of Routing Protocols in Large Size Disaster Scenario

2019 ◽  
Vol 8 (2) ◽  
pp. 4200-4204
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Mobility Model ◽  
Delivery Ratio ◽  
Ad Hoc Routing ◽  
Large Size ◽  
Disaster Area ◽  
Demand Routing ◽  
Disaster Scenario

Peoples in the disastrous areas under collapsed buildings or landslides need to be rescued in seventy-two hours. Ad hoc networks have been proved to be suitable for various disaster scenarios since no infrastructure needs to be deployed for communication. In this paper, various ad hoc routing protocols such as destination distance vector routing protocol, dynamic source routing protocol, ad hoc on demand routing protocol etc. are discussed and analyzed in such disaster scenario using disaster area mobility model on large size. Disaster area mobility model is more desirable in such scenario. Also these protocols are compared using various performance qualitative and quantitative metrics such as packet delivery ratio, delay, throughput, control overhead and energy etc

scholarly journals A Survey on Applications of Reinforcement Learning in Flying Ad-Hoc Networks

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 449
Author(s):  
Sifat Rezwan ◽  
Wooyeol Choi
Keyword(s):  
Reinforcement Learning ◽  
Ad Hoc Networks ◽  
Wireless Ad Hoc Networks ◽  
Routing Protocol ◽  
Traffic Congestion ◽  
Ad Hoc ◽  
High Mobility ◽  
Flight Trajectory ◽  
Research Issues ◽  
Hoc Networks

Flying ad-hoc networks (FANET) are one of the most important branches of wireless ad-hoc networks, consisting of multiple unmanned air vehicles (UAVs) performing assigned tasks and communicating with each other. Nowadays FANETs are being used for commercial and civilian applications such as handling traffic congestion, remote data collection, remote sensing, network relaying, and delivering products. However, there are some major challenges, such as adaptive routing protocols, flight trajectory selection, energy limitations, charging, and autonomous deployment that need to be addressed in FANETs. Several researchers have been working for the last few years to resolve these problems. The main obstacles are the high mobility and unpredictable changes in the topology of FANETs. Hence, many researchers have introduced reinforcement learning (RL) algorithms in FANETs to overcome these shortcomings. In this study, we comprehensively surveyed and qualitatively compared the applications of RL in different scenarios of FANETs such as routing protocol, flight trajectory selection, relaying, and charging. We also discuss open research issues that can provide researchers with clear and direct insights for further research.

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.

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.

Analysis of Reinforcement Based Adaptive Routing in MANET

2016 ◽  
Vol 2 (3) ◽  
pp. 648 ◽  
Author(s):  
Rahul Desai ◽  
B P Patil
Keyword(s):  
Reinforcement Learning ◽  
Shortest Path ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Learning Algorithms ◽  
High Mobility ◽  
Delivery Ratio ◽  
Shortest Path Routing ◽  
Minimum Number ◽  
Shortest Path Algorithms

<p class="Abstract">This paper describes and evaluates the performance of various reinforcement learning algorithms with shortest path algorithms that are widely used for routing packets through the network. Shortest path routing is the simplest policy used for routing the packets along the path having minimum number of hops. In high traffic or high mobility conditions, the shortest path get flooded with huge number of packets and congestions occurs, So such shortest path does not provides the shortest path and increases delay for reaching the packets to the destination. Reinforcement learning algorithms are adaptive algorithms where the path is selected based on the traffic present on the network at real time. Thus they guarantee the least delivery time to reach the packets to the destination. Analysis done on a 6 by 6 irregular grid and sample ad hoc network shows that performance parameters used for judging the network - packet delivery ratio and delay provides optimum results using reinforcement learning algorithms. </p>

scholarly journals Confidence-based Security System for Routing Protocol in Mobile Ad-hoc Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 2212-2218
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Average Energy ◽  
Delivery Ratio ◽  
Node Mobility ◽  
On Demand ◽  
Distance Vector ◽  
Mobile Ad Hoc

A mobile ad-hoc network (MANET) is an infrastructure-less network of wireless nodes. The network topology may change quickly with respect to time, due to node mobility. The network is a disintegrated network, activities such as delivering messages by determining the topology essential to be implemented by the nodes themselves i.e., the routing activity will be unified into mobile nodes. Due to the lack of centralized administration in multihop routing and open environment, MANET’s are susceptible to attacks by compromised nodes; hence, to provide security also energy efficiency is a crucial issue. So as to decrease the hazards of malicious nodes and resolve energy consumption issues, a simple confidence-based protocol is built to evaluate neighbor’s behaviour using forwarding factors. The reactive Ad-hoc on-demand multipath distance vector routing protocol (AOMDV), is extended and confidence-based Ad-hoc on-demand distance vector (CBAOMDV) protocol, is implemented for MANET. This implemented protocol is able to find multiple routes in one route discovery. These routes are calculated by confidence values and hop counts. From there, the shortest path is selected which fulfills the requirements of data packets for reliability on confidence. Several experimentations have been directed to relate AOMDV and CBAOMDV protocols and the outcomes show that CBAOMDV advances throughput, packet delivery ratio, normalized routing load, and average energy consumption.

scholarly journals Performance Evaluation of Routing Metrics in the LOADng Routing Protocol

2017 ◽  
Vol 13 (2) ◽  
pp. 87 ◽  
Author(s):  
Jose V. V. Sobral ◽  
Joel J. P. C. Rodrigues ◽  
Neeraj Kumar ◽  
Chunsheng Zhu ◽  
Raja W. Ahmad
Keyword(s):  
Routing Protocol ◽  
Network Performance ◽  
Ad Hoc ◽  
Average Energy ◽  
Delivery Ratio ◽  
Traffic Patterns ◽  
Routing Metric ◽  
Lossy Networks ◽  
Routing Metrics ◽  
Average Latency

LOADng (Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation) is an emerging routing protocol that emerged as an alternative to RPL (IPv6 Routing Protocol for Low power and Lossy Networks). Although some work has been dedicated to study LOADng, these works do not analyze the performance of this protocol with different routing metrics. A routing metric is responsible for defining values for paths during the route creation process. Moreover, based on these metrics information a routing protocol will select the path to forward a message. Thus, this work aims to realize a performance assessment study considering different routing metrics applied to LOADng. The scenarios under study consider different traffic patterns and network sizes. The routing metrics are evaluated considering the packet delivery ratio, average energy spent per bit delivered, average latency, and number of hops. The results reveals that routing metrics used by this protocol may influence (directly) the network performance.

Adaptive Routing for an Ad Hoc Network Based on Reinforcement Learning

2015 ◽  
Vol 11 (2) ◽  
pp. 40-52
Author(s):  
Rahul Desai ◽  
B.P. Patil
Keyword(s):  
Reinforcement Learning ◽  
Shortest Path ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Learning Algorithms ◽  
High Mobility ◽  
Delivery Ratio ◽  
Shortest Path Routing ◽  
Minimum Number ◽  
Shortest Path Algorithms

This paper describes and evaluates the performance of various reinforcement learning algorithms with shortest path algorithms that are widely used for routing packets throughout the network. Shortest path routing is simplest policy used for routing the packets along the path having minimum number of hops. In high traffic or high mobility conditions, the shortest path gets flooded with huge number of packets and congestions occurs, so such shortest path does not provide the shortest path and increases delay for reaching the packets to the destination. Reinforcement learning algorithms are adaptive algorithms where the path is selected based on the traffic present on the network at real time. Thus they guarantee the least delivery time to reach the packets to the destination. Analysis is done on a 6-by-6 irregular grid and sample ad hoc network shows that performance parameters used for judging the network such as packet delivery ratio and delay provide optimum results using reinforcement learning algorithms.

scholarly journals Development of Modify Random Waypoint Mobility Model of Routing Protocol for the Mobile Ad-Hoc Network

2022 ◽  
Author(s):  
Ajay Vyas ◽  
Margam Suthar
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Performance Metrics ◽  
Mobility Model ◽  
Delivery Ratio ◽  
Mobile Ad Hoc ◽  
Random Waypoint Model ◽  
Random Waypoint

Mobility models are used to evaluated the network protocols of the ad hoc network using the simulation. The random waypoint model is a model for mobility which is usually used for performance evaluation of ad-hoc mobile network. Mobile nodes have the dynamic mobility in the ad hoc network so the mobility model plays an important role to evaluate the protocol performance.In this article, we developed modify random waypoint mobility (MRWM) model based on random waypoint for the mobile ad hoc network. In this article, the comparative analysis of modifying random waypoint mobility and random waypoint model on the ad hoc On-Demand Distance Vector (AODV) routing protocol has been done for large wireless ad hoc network (100 nodes) with the random mobile environment for the 1800s simulation time. To enhance the confidence on the protocol widespread simulations were accomplished under heavy traffic (i.e. 80 nodes) condition. The proposed model protocol has been investigated with the performance metrics: throughput; packet delivery ratio; packet dropping ratio; the end to end delay and normalized routing overhead. The obtained results revealed that proposed modify random waypoint mobility model reduces the mobility as compared to the random waypoint mobility model and it is trace is more realist.

scholarly journals Congestion Control for Improved Cluster-head Gateway Switch Routing Protocol using Modified Ad-hoc on-demand Distance Vector Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 6013-6018
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Cluster Head ◽  
Average Energy ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
On Demand ◽  
Distance Vector ◽  
Average Energy Consumption

MANETs are a trending topic in the wireless communication network. MANETs are formed automatically by an autonomous system of mobile nodes that are connected via wireless links. Cluster-head gateway switch routing protocol (CGSR) is a proactive protocol which is also called table-driven protocol. It consists of routing table information before setting up a connection. Ad-hoc on-demand distance vector protocol (AODV) is a reactive protocol, it sets path only when demanded by the network. CGSR protocol forms a group of nodes into clusters and selects a node as cluster-head based on some clustering algorithms for each cluster. In this paper, we have proposed a protocol, which combines the advantages of both CGSR and AODV to minimize traffic congestion in an ad-hoc wireless network. The performance metrics such as routing overhead, end-end delay, packet delivery ratio, throughput, and average energy consumption are enhanced and compared with other clustering protocols such as CGSR and LEACH protocols. The comparison result reveals that the routing overhead, end-end delay, and the average energy consumption is reduced and packet delivery ratio, throughput is improved.

Sign in / Sign up

Export Citation Format

Share Document