A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs

被引:1
|
作者
Galarza, Christian E. [1 ]
Palma, Jonathan M. [2 ]
Morais, Cecilia F. [3 ]
Utria, Jaime [4 ]
Carvalho, Leonardo P. [5 ,6 ]
Bustos, Daniel [7 ,8 ,9 ]
Oliveira, Ricardo C. L. F. [10 ]
机构
[1] Escuela Super Politecn Litoral ESPOL, Fac Ciencias Natu & Matemat, Via Perimetral 5, Guayaquil 090150, Ecuador
[2] Univ Talca, Fac Engn, Dept Elect Engn, Curico 3344158, Chile
[3] Pontifical Catholic Univ Campinas, Ctr Exact Environm & Technol Sci, BR-13086900 Campinas, SP, Brazil
[4] Fluminense Fed Univ UFF, Inst Math & Stat, BR-24210201 Niteroi, RJ, Brazil
[5] Univ Groningen, Discrete Technol & Prod Automat DTPA, NL-9712 CP Groningen, Netherlands
[6] Univ Sao Paulo, Polytech Sch, BR-05508900 Sao Paulo, SP, Brazil
[7] Univ Catolica Maule, Ctr Invest Estudios Avanzados Maule CIEAM, Vicerrectoria Invest & Postgrado, Talca 3460000, Chile
[8] Univ Catolica Maule, Fac Med, Lab Bioinformat Quim Comp LBQC, Talca 3460000, Chile
[9] Univ Catolica Maule, Fac Med, Escuela Bioingenieria Med, Talca 3460000, Chile
[10] Univ Campinas UNICAMP, Sch Elect & Comp Engn, BR-05508900 Campinas, SP, Brazil
关键词
multi-hop network; semi-reliable communication network; opportunistic routing network; PROTOCOL;
D O I
10.3390/s21238058
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页数:16
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