Spray and Wait Routing Based on Average Delivery Probability in Delay Tolerant Network

2009 ◽  
Author(s):  
Jingfeng Xue ◽  
Xiumei Fan ◽  
Yuanda Cao ◽  
Ji Fang ◽  
Jiansheng Li
Keyword(s):  
Delay Tolerant Network ◽  
Delivery Probability ◽  
Delay Tolerant ◽  
Spray And Wait

Validation of Fuzzy-Based Routing Algorithm for DTN

2014 ◽  
Vol 644-650 ◽  
pp. 1931-1934
Author(s):  
Fan Yang ◽  
Jia Zhe Lai ◽  
Ming Zhe Li
Keyword(s):  
Routing Algorithm ◽  
Simulation Software ◽  
Delay Tolerant Network ◽  
Research Issue ◽  
Network Environment ◽  
Opportunistic Network ◽  
Dtn Routing ◽  
Delay Tolerant ◽  
Spray And Wait

In the research of Delay Tolerant Network (DTN), DTN routing algorithm is a key research issue. The performance of a non-flooding routing algorithm is verified in our paper. The verified algorithm is an Adaptive Priority Routing Algorithm (APRA) which is based on fuzzy strategies. Firstly, we introduce the principle of APRA, then using Opportunistic Network Environment (ONE) -simulation software to compare the performance of Epidemic algorithm, Spray and Wait algorithm, PRoPHET algorithm and APRA. By comparing overhead of netword, rate of messages delivered and average dealy, it finds that the APRA performs better. At last, the weaknesses of this paper and further improvement are also discussed.

scholarly journals A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach

2020 ◽  
Vol 12 (11) ◽  
pp. 192
Author(s):  
Youcef Azzoug ◽  
Abdelmadjid Boukra ◽  
Vasco N. G. J. Soares
Keyword(s):  
Delay Tolerant Network ◽  
Relay Nodes ◽  
Hybrid Swarm ◽  
Recovery Method ◽  
Delivery Delay ◽  
Delivery Probability ◽  
Glowworm Swarm Optimization ◽  
Dtn Routing ◽  
Metaheuristic Techniques ◽  
Delay Tolerant

The probabilistic Delay Tolerant Network (DTN) routing has been adjusted for vehicular network (VANET) routing through numerous works exploiting the historic routing profile of nodes to forward bundles through better Store-Carry-and-Forward (SCF) relay nodes. In this paper, we propose a new hybrid swarm-inspired probabilistic Vehicular DTN (VDTN) router to optimize the next-SCF vehicle selection using the combination of two bio-metaheuristic techniques called the Firefly Algorithm (FA) and the Glowworm Swarm Optimization (GSO). The FA-based strategy exploits the stochastic intelligence of fireflies in moving toward better individuals, while the GSO-based strategy mimics the movement of glowworm towards better area for displacing and food foraging. Both FA and GSO are executed simultaneously on each node to track better SCF vehicles towards each bundle’s destination. A geography-based recovery method is performed in case no better SCF vehicles are found using the hybrid FA–GSO approach. The proposed FA–GSO VDTN scheme is compared to ProPHET and GeoSpray routers. The simulation results indicated optimized bundles flooding levels and higher profitability of combined delivery delay and delivery probability.

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