scholarly journals A Fuzzy-Logic-Based Double Q -Learning Routing in Delay-Tolerant Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jiagao Wu ◽  
Fan Yuan ◽  
Yahang Guo ◽  
Hongyu Zhou ◽  
Linfeng Liu
Keyword(s):  
Fuzzy Logic ◽  
Mobile Networks ◽  
Learning Algorithm ◽  
Buffer Management ◽  
Delay Tolerant Networks ◽  
Movement Speed ◽  
Delivery Ratio ◽  
Node Activity ◽  
Intermittent Connectivity ◽  
Delay Tolerant

Delay-tolerant networks (DTNs) are wireless mobile networks, which suffer from frequent disruption, high latency, and lack of a complete path from source to destination. The intermittent connectivity in DTNs makes it difficult to efficiently deliver messages. Research results have shown that the routing protocol based on reinforcement learning can achieve a reasonable balance between routing performance and cost. However, due to the complexity, dynamics, and uncertainty of the characteristics of nodes in DTNs, providing a reliable multihop routing in DTNs is still a particular challenge. In this paper, we propose a Fuzzy-logic-based Double Q -Learning Routing (FDQLR) protocol that can learn the optimal route by combining fuzzy logic with the Double Q -Learning algorithm. In this protocol, a fuzzy dynamic reward mechanism is proposed, and it uses fuzzy logic to comprehensively evaluate the characteristics of nodes including node activity, contact interval, and movement speed. Furthermore, a hot zone drop mechanism and a drop mechanism are proposed, which can improve the efficiency of message forwarding and buffer management of the node. The simulation results show that the fuzzy logic can improve the performance of the FDQLR protocol in terms of delivery ratio, delivery delay, and overhead. In particular, compared with other related routing protocols of DTNs, the FDQLR protocol can achieve the highest delivery ratio and the lowest overhead.

scholarly journals Feature Extraction of Real-World Traces Using K Means Clustering In OppNet

2021 ◽  
Author(s):  
Rahul Johari ◽  
Tanvi Gautam
Keyword(s):  
Network Topology ◽  
Real World ◽  
Network Performance ◽  
Performance Metrics ◽  
Learning Algorithm ◽  
Dynamic Network ◽  
Delivery Ratio ◽  
Communication Link ◽  
Alternative Measure ◽  
Intermittent Connectivity

Abstract Natural calamities leave people helpless by arising several situations such as network breakdown, zero communication, intermittent connectivity, dynamic network topology. In such situation an application of dynamic and intermittent routing scheme is essential to make further communication possible during likewise scenarios. An application of TCP/IP becomes futile in mentioned circumstances as it best works for static nodes and pre-defined network topology wherein source and destination nodes are first establishing the communication link with each other. An alternative measure of such hitches is to encounter an application of DTN protocol which possess all characteristics to withstand in such scenarios such as; dynamic network topology, intermittent connectivity, frequent path breaks, store – carry – forward fashion. In this paper we did thorough investigation of forest fire dataset (Uttarakhand) after exploring its implementation in ONE with Epidemic, Prophet, Spray and Wait, HBPR, GAER respectively. An extensive and thorough investigation for real world traces implementation has been done with OppNet routing protocols against mobility models namely; Shortest path map – based, Random Direction, Random Walk, Random Waypoint, Cluster Movement respectively for network performance metrics namely packet delivery ratio, packet overhead ratio and average latency ratio respectively with the application of K means clustering machine learning algorithm. With the help of this analysis, we explore the real-world traces characteristics and study the areas on which network performance can be improved.

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