Articles producció científica> Enginyeria Informàtica i Matemàtiques

Using a history-based approach to predict topology control information in mobile ad hoc networks

  • Dades identificatives

    Identificador: imarina:5657905
    Autors:
    Millán PMolina CMeseguer ROchoa SSantos R
    Resum:
    © Springer International Publishing Switzerland 2014. Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.
  • Altres:

    Autor segons l'article: Millán P; Molina C; Meseguer R; Ochoa S; Santos R
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Millán Marco, Pedro / Molina Clemente, Carlos María
    Paraules clau: Routing protocols Network topology prediction Mobile collaboration Mobile ad hoc networks History-based prediction
    Resum: © Springer International Publishing Switzerland 2014. Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.
    Àrees temàtiques: Theoretical computer science Saúde coletiva Química Psicología Planejamento urbano e regional / demografia Odontología Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Linguística e literatura Interdisciplinar Geografía Geociências General o multidisciplinar General computer science Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Educação física Educação Direito Comunicació i informació Comunicação e informação Computer science, theory & methods Computer science, artificial intelligence Computer science (miscellaneous) Computer science (all) Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Artes Arquitetura, urbanismo e design Arquitetura e urbanismo Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
    ISSN: 03029743
    Adreça de correu electrònic de l'autor: pere.millan@urv.cat carlos.molina@urv.cat
    Identificador de l'autor: 0000-0002-4132-7099 0000-0003-1955-0128
    Data d'alta del registre: 2024-06-22
    Referència a l'article segons font original: Lecture Notes In Computer Science. 8729 237-249
    Referència de l'ítem segons les normes APA: Millán P; Molina C; Meseguer R; Ochoa S; Santos R (2014). Using a history-based approach to predict topology control information in mobile ad hoc networks. Lecture Notes In Computer Science, 8729(), 237-249. DOI: 10.1007/978-3-319-11692-1_21
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI de l'article: 10.1007/978-3-319-11692-1_21
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2014
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Computer Science (Miscellaneous),Computer Science, Artificial Intelligence,Computer Science, Theory & Methods,Theoretical Computer Science
    Routing protocols
    Network topology prediction
    Mobile collaboration
    Mobile ad hoc networks
    History-based prediction
    Theoretical computer science
    Saúde coletiva
    Química
    Psicología
    Planejamento urbano e regional / demografia
    Odontología
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Linguística e literatura
    Interdisciplinar
    Geografía
    Geociências
    General o multidisciplinar
    General computer science
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Educação física
    Educação
    Direito
    Comunicació i informació
    Comunicação e informação
    Computer science, theory & methods
    Computer science, artificial intelligence
    Computer science (miscellaneous)
    Computer science (all)
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
    Artes
    Arquitetura, urbanismo e design
    Arquitetura e urbanismo
    Administração, ciências contábeis e turismo
    Administração pública e de empresas, ciências contábeis e turismo
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