A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs
| Autor: | Daniel Bustos, Jaime Utria, Cecília Morais, Christian Galarza Morales, Leonardo De Paula Carvalho, Jonathan Matias Palma Olate, Ricardo Oliveira |
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| Přispěvatelé: | Discrete Technology and Production Automation |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
semi-reliable communication network
Chemical technology Computer Science::Networking and Internet Architecture multi-hop network opportunistic routing network TP1-1185 Electrical and Electronic Engineering Biochemistry Instrumentation Atomic and Molecular Physics and Optics Article Analytical Chemistry |
| Zdroj: | Sensors, Vol 21, Iss 8058, p 8058 (2021) Sensors (Basel, Switzerland) Sensors; Volume 21; Issue 23; Pages: 8058 Sensors, 21(23):8058. MDPI AG |
| ISSN: | 1424-8220 |
| Popis: | This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network. |
| Databáze: | OpenAIRE |
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