The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans le système de communication sans fil hétérogène actuel, la forte augmentation de la consommation d’énergie et l’émergence de nouveaux types de services posent de grands défis aux algorithmes actuels de sélection des réseaux d’accès radio qui ne prennent pas en compte ces nouvelles tendances. Ainsi, l'algorithme de sélection de réseau d'accès hétérogène multiservices basé sur l'efficacité énergétique proposé - ESRS (Energy Saving Radio access network Selection) est destiné à réduire la consommation d'énergie causée par le trafic dans le système de réseau mobile composé de stations de base (BS) et de points d'accès. (AP). Cet algorithme modélise le problème de sélection du réseau d'accès comme un problème de prise de décision à attributs multiples (MADM). Pour résoudre ce problème, de nombreuses méthodes sont combinées, notamment le processus de hiérarchie analytique (AHP), l'analyse relationnelle grise pondérée (GRA), la théorie de l'entropie, la pondération additive simple (SAW) et la théorie de la fonction d'utilité. Il y a deux étapes principales dans cet algorithme. Dans un premier temps, l'algorithme proposé obtient le résultat de la QoS utilisateur de chaque réseau en traitant les paramètres de QoS associés, dans lesquels la théorie de l'entropie et l'AHP sont utilisés pour déterminer le poids global de la QoS, et le SAW est utilisé pour obtenir la QoS de chaque réseau. En plus de la QoS utilisateur, des paramètres tels que le débit utilisateur, l'utilité de la consommation d'énergie et l'utilité du coût sont également calculés au cours de cette étape. Dans la deuxième étape, la théorie floue est utilisée pour définir le poids des attributs de décision, et l'analyse relationnelle grise pondérée (GRA) est utilisée pour calculer le score du réseau, qui détermine le choix final. Parce que le poids flou a une préférence pour la faible consommation d'énergie, la consommation d'énergie du trafic sera économisée en choisissant autant que possible le réseau ayant la moindre consommation d'énergie. Les parties simulation ont comparé les performances des algorithmes ESRS, ABE et MSNS. Les résultats numériques montrent que l'algorithme ESRS peut sélectionner le réseau approprié en fonction des demandes de service et des paramètres du réseau. En outre, il peut réduire efficacement la consommation d'énergie et le coût global du système tout en conservant une valeur globale de QoS élevée et un débit système élevé, par rapport aux deux autres algorithmes.
Meng-Yuan HE
Nanjing University of Posts and Telecommunications
Ling-Yun JIANG
Nanjing University of Posts and Telecommunications
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Meng-Yuan HE, Ling-Yun JIANG, "Energy Efficiency Based Multi Service Heterogeneous Access Network Selection Algorithm" in IEICE TRANSACTIONS on Communications,
vol. E106-B, no. 10, pp. 881-890, October 2023, doi: 10.1587/transcom.2022EBP3196.
Abstract: In the current heterogeneous wireless communication system, the sharp rise in energy consumption and the emergence of new service types pose great challenges to nowadays radio access network selection algorithms which do not take care of these new trends. So the proposed energy efficiency based multi-service heterogeneous access network selection algorithm-ESRS (Energy Saving Radio access network Selection) is intended to reduce the energy consumption caused by the traffic in the mobile network system composed of Base Stations (BSs) and Access Points (APs). This algorithm models the access network selection problem as a Multiple-Attribute Decision-Making (MADM) problem. To solve this problem, lots of methods are combined, including analytic Hierarchy Process (AHP), weighted grey relational analysis (GRA), entropy theory, simple additive weight (SAW), and utility function theory. There are two main steps in this algorithm. At first, the proposed algorithm gets the result of the user QoS of each network by dealing with the related QoS parameters, in which entropy theory and AHP are used to determine the QoS comprehensive weight, and the SAW is used to get each network's QoS. In addition to user QoS, parameters including user throughput, energy consumption utility and cost utility are also calculated in this step. In the second step, the fuzzy theory is used to define the weight of decision attributes, and weighted grey relational analysis (GRA) is used to calculate the network score, which determines the final choice. Because the fuzzy weight has a preference for the low energy consumption, the energy consumption of the traffic will be saved by choosing the network with the least energy consumption as much as possible. The simulation parts compared the performance of ESRS, ABE and MSNS algorithms. The numerical results show that ESRS algorithm can select the appropriate network based on the service demands and network parameters. Besides, it can effectively reduce the system energy consumption and overall cost while still maintaining a high overall QoS value and a high system throughput, when compared with the other two algorithms.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2022EBP3196/_p
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@ARTICLE{e106-b_10_881,
author={Meng-Yuan HE, Ling-Yun JIANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Energy Efficiency Based Multi Service Heterogeneous Access Network Selection Algorithm},
year={2023},
volume={E106-B},
number={10},
pages={881-890},
abstract={In the current heterogeneous wireless communication system, the sharp rise in energy consumption and the emergence of new service types pose great challenges to nowadays radio access network selection algorithms which do not take care of these new trends. So the proposed energy efficiency based multi-service heterogeneous access network selection algorithm-ESRS (Energy Saving Radio access network Selection) is intended to reduce the energy consumption caused by the traffic in the mobile network system composed of Base Stations (BSs) and Access Points (APs). This algorithm models the access network selection problem as a Multiple-Attribute Decision-Making (MADM) problem. To solve this problem, lots of methods are combined, including analytic Hierarchy Process (AHP), weighted grey relational analysis (GRA), entropy theory, simple additive weight (SAW), and utility function theory. There are two main steps in this algorithm. At first, the proposed algorithm gets the result of the user QoS of each network by dealing with the related QoS parameters, in which entropy theory and AHP are used to determine the QoS comprehensive weight, and the SAW is used to get each network's QoS. In addition to user QoS, parameters including user throughput, energy consumption utility and cost utility are also calculated in this step. In the second step, the fuzzy theory is used to define the weight of decision attributes, and weighted grey relational analysis (GRA) is used to calculate the network score, which determines the final choice. Because the fuzzy weight has a preference for the low energy consumption, the energy consumption of the traffic will be saved by choosing the network with the least energy consumption as much as possible. The simulation parts compared the performance of ESRS, ABE and MSNS algorithms. The numerical results show that ESRS algorithm can select the appropriate network based on the service demands and network parameters. Besides, it can effectively reduce the system energy consumption and overall cost while still maintaining a high overall QoS value and a high system throughput, when compared with the other two algorithms.},
keywords={},
doi={10.1587/transcom.2022EBP3196},
ISSN={1745-1345},
month={October},}
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TY - JOUR
TI - Energy Efficiency Based Multi Service Heterogeneous Access Network Selection Algorithm
T2 - IEICE TRANSACTIONS on Communications
SP - 881
EP - 890
AU - Meng-Yuan HE
AU - Ling-Yun JIANG
PY - 2023
DO - 10.1587/transcom.2022EBP3196
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E106-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2023
AB - In the current heterogeneous wireless communication system, the sharp rise in energy consumption and the emergence of new service types pose great challenges to nowadays radio access network selection algorithms which do not take care of these new trends. So the proposed energy efficiency based multi-service heterogeneous access network selection algorithm-ESRS (Energy Saving Radio access network Selection) is intended to reduce the energy consumption caused by the traffic in the mobile network system composed of Base Stations (BSs) and Access Points (APs). This algorithm models the access network selection problem as a Multiple-Attribute Decision-Making (MADM) problem. To solve this problem, lots of methods are combined, including analytic Hierarchy Process (AHP), weighted grey relational analysis (GRA), entropy theory, simple additive weight (SAW), and utility function theory. There are two main steps in this algorithm. At first, the proposed algorithm gets the result of the user QoS of each network by dealing with the related QoS parameters, in which entropy theory and AHP are used to determine the QoS comprehensive weight, and the SAW is used to get each network's QoS. In addition to user QoS, parameters including user throughput, energy consumption utility and cost utility are also calculated in this step. In the second step, the fuzzy theory is used to define the weight of decision attributes, and weighted grey relational analysis (GRA) is used to calculate the network score, which determines the final choice. Because the fuzzy weight has a preference for the low energy consumption, the energy consumption of the traffic will be saved by choosing the network with the least energy consumption as much as possible. The simulation parts compared the performance of ESRS, ABE and MSNS algorithms. The numerical results show that ESRS algorithm can select the appropriate network based on the service demands and network parameters. Besides, it can effectively reduce the system energy consumption and overall cost while still maintaining a high overall QoS value and a high system throughput, when compared with the other two algorithms.
ER -