2017
P.G. Sarigiannidis; G. Papadimitriou; P. Nicopolitidis; E. Varvarigos
Towards power consumption in optical networks: a cognitive prediction-based technique Journal Article
In: International Journal of Communication Systems, vol. 30, no. 7, 2017.
Περίληψη | BibTeX | Ετικέτες: backbone networks, energy efficiency, optical networks, power consumption, prediction | Σύνδεσμοι:
@article{Sarigiannidis2017d,
title = {Towards power consumption in optical networks: a cognitive prediction-based technique},
author = { P.G. Sarigiannidis and G. Papadimitriou and P. Nicopolitidis and E. Varvarigos},
url = {https://www.researchgate.net/publication/276509099_Towards_power_consumption_in_optical_networks_A_cognitive_prediction-based_technique},
doi = {10.1002/dac.2981},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Communication Systems},
volume = {30},
number = {7},
abstract = {Modern backbone, optical networks have developed into large, massive networks, which consist of numerous intermediate and terminal nodes as well as final users. These networks serve uninterruptedly multitude of users at the expense of considerable power consumption. Many research efforts are aimed at reducing energy consumption in large-scale optical networks, however, this objective is deemed laborious: the operation of such networks has to continuously remain in good levels without disruptions. One of the most compelling techniques to remedy this situation is to switch off redundant links and devices at specific (short) periods. These links and devices remain idle as long as the network can cope with the underlying traffic demands. Hence, a power mechanism is required to manage how and when underutilized network elements may be silent during network operation. Nevertheless, this management entails fast processing and efficient decision making. While many research efforts neglect this serious factor, the problem of reducing the power consumption still threats the development of today's backbone network. In this work, an effective, cognitive power management technique is proposed by enhancing the decision making with traffic prediction. Traffic capacity is estimated in each link within the network supporting, thus, more efficient decisions on switching off underutilized or even idle network elements a priori. The technique introduced succeeds high accuracy levels, while it offers energy savings up to 30% lower than other energy-aware schemes. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.},
keywords = {backbone networks, energy efficiency, optical networks, power consumption, prediction},
pubstate = {published},
tppubtype = {article}
}
Modern backbone, optical networks have developed into large, massive networks, which consist of numerous intermediate and terminal nodes as well as final users. These networks serve uninterruptedly multitude of users at the expense of considerable power consumption. Many research efforts are aimed at reducing energy consumption in large-scale optical networks, however, this objective is deemed laborious: the operation of such networks has to continuously remain in good levels without disruptions. One of the most compelling techniques to remedy this situation is to switch off redundant links and devices at specific (short) periods. These links and devices remain idle as long as the network can cope with the underlying traffic demands. Hence, a power mechanism is required to manage how and when underutilized network elements may be silent during network operation. Nevertheless, this management entails fast processing and efficient decision making. While many research efforts neglect this serious factor, the problem of reducing the power consumption still threats the development of today's backbone network. In this work, an effective, cognitive power management technique is proposed by enhancing the decision making with traffic prediction. Traffic capacity is estimated in each link within the network supporting, thus, more efficient decisions on switching off underutilized or even idle network elements a priori. The technique introduced succeeds high accuracy levels, while it offers energy savings up to 30% lower than other energy-aware schemes. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
2015
P. Sarigiannidis; M. Louta; G. Papadimitriou; I. Moscholios; A. Boucouvalas; D. Kleftouris
2015.
Περίληψη | BibTeX | Ετικέτες: bandwidth allocation, FiWi, hidden Markov chains, prediction | Σύνδεσμοι:
@conference{Sarigiannidis201545,
title = {Alleviating the high propagation delays in FiWi networks: A prediction-based DBA scheme for 10G-EPON-WiMAX systems},
author = { P. Sarigiannidis and M. Louta and G. Papadimitriou and I. Moscholios and A. Boucouvalas and D. Kleftouris},
url = {https://www.researchgate.net/publication/308463668_Alleviating_the_high_propagation_delays_in_FiWi_networks_a_prediction-based_DBA_scheme_for_10G-EPON-WiMAX_systems},
doi = {10.1109/FOAN.2015.7320478},
year = {2015},
date = {2015-01-01},
journal = {2015 International Workshop on Fiber Optics in Access Network, FOAN 2015},
pages = {45-50},
abstract = {Fiber Wireless (FiWi) networks constitute a very promising, cost-effective solution to cope with modern demanding services and applications in access networks. One of the most challenging objective lies in the design of a robust, efficient and effective bandwidth allocation. The design of such a Dynamic Bandwidth Allocation (DBA) scheme should take into account the large propagation delays between mobile users and the Central Office (CO). In this work, we endeavor to address this challenge by proposing a prediction-aware DBA scheme for FiWi networks, where the optical domain is implemented by a 10Gbps Ethernet PON (10G-EPON) and the wireless domain is supported by WiMAX access stations. In order to ensure an effective DBA scheme a hidden Markov chain model is devised for estimating the surplus traffic requests of each mobile user during the coordination message exchange between the optical and the wireless domains. In addition, a fair bandwidth distribution is applied based on the results of the prediction module. Based on the obtained simulation results the proposed scheme presents a good network performance in terms of prediction accuracy and packet delay. © 2015 IEEE.},
keywords = {bandwidth allocation, FiWi, hidden Markov chains, prediction},
pubstate = {published},
tppubtype = {conference}
}
Fiber Wireless (FiWi) networks constitute a very promising, cost-effective solution to cope with modern demanding services and applications in access networks. One of the most challenging objective lies in the design of a robust, efficient and effective bandwidth allocation. The design of such a Dynamic Bandwidth Allocation (DBA) scheme should take into account the large propagation delays between mobile users and the Central Office (CO). In this work, we endeavor to address this challenge by proposing a prediction-aware DBA scheme for FiWi networks, where the optical domain is implemented by a 10Gbps Ethernet PON (10G-EPON) and the wireless domain is supported by WiMAX access stations. In order to ensure an effective DBA scheme a hidden Markov chain model is devised for estimating the surplus traffic requests of each mobile user during the coordination message exchange between the optical and the wireless domains. In addition, a fair bandwidth distribution is applied based on the results of the prediction module. Based on the obtained simulation results the proposed scheme presents a good network performance in terms of prediction accuracy and packet delay. © 2015 IEEE.
2014
P. Sarigiannidis; K. Aproikidis; M. Louta; P. Angelidis; T. Lagkas
Predicting multimedia traffic in wireless networks: A performance evaluation of cognitive techniques Conference
2014.
Περίληψη | BibTeX | Ετικέτες: automata, extrapolation, markov chains, prediction, wireless networks | Σύνδεσμοι:
@conference{Sarigiannidis2014341,
title = {Predicting multimedia traffic in wireless networks: A performance evaluation of cognitive techniques},
author = { P. Sarigiannidis and K. Aproikidis and M. Louta and P. Angelidis and T. Lagkas},
url = {https://www.researchgate.net/publication/267210651_Predicting_Multimedia_Traffic_in_Wireless_Networks_A_Performance_Evaluation_of_Cognitive_Techniques},
doi = {10.1109/IISA.2014.6878802},
year = {2014},
date = {2014-01-01},
journal = {IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications},
pages = {341-346},
abstract = {Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy. © 2014 IEEE.},
keywords = {automata, extrapolation, markov chains, prediction, wireless networks},
pubstate = {published},
tppubtype = {conference}
}
Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy. © 2014 IEEE.
2010
P.G. Sarigiannidis; G.I. Papadimitriou; P. Nicopolitidis; M.S. Obaidat; A.S. Pomportsis
A novel adaptive mapping scheme for IEEE 802.16 mobile downlink framing Conference
2010.
Περίληψη | BibTeX | Ετικέτες: Downlink mapping, IEEE 802.16, OFDMA, prediction | Σύνδεσμοι:
@conference{Sarigiannidis2010c,
title = {A novel adaptive mapping scheme for IEEE 802.16 mobile downlink framing},
author = { P.G. Sarigiannidis and G.I. Papadimitriou and P. Nicopolitidis and M.S. Obaidat and A.S. Pomportsis},
url = {https://www.researchgate.net/publication/221288841_A_Novel_Adaptive_Mapping_Scheme_for_IEEE_80216_Mobile_Downlink_Framing},
doi = {10.1109/GLOCOM.2010.5683645},
year = {2010},
date = {2010-01-01},
journal = {GLOBECOM - IEEE Global Telecommunications Conference},
abstract = {IEEE 802.16 (WiMAX) constitutes one of the most promising broadband access technologies for high-capacity and high-distance wireless access networks, supporting user mobility. The contribution of this paper is twofold. Firstly, a novel mapping scheme for IEEE 802.16 Mobile standard is introduced, applying horizon mapping. Secondly, an efficient adaptive prediction-based scheme is devised, which is able to adjust the downlink sub-frame capacity, accordingly to the traffic load, since the standard allows the downlink-to-uplink subframe ratio to be changeable from 3:1 to 1:1. The novel adaptive horizon burst mapping (AHBM) scheme is evaluated by simulation experiments, which indicate that the proposed scheme operates effectively and efficiently, by reducing the number of unserved users, the number of unserved traffic requests, and the portion of wasted bandwidth. ©2010 IEEE.},
keywords = {Downlink mapping, IEEE 802.16, OFDMA, prediction},
pubstate = {published},
tppubtype = {conference}
}
IEEE 802.16 (WiMAX) constitutes one of the most promising broadband access technologies for high-capacity and high-distance wireless access networks, supporting user mobility. The contribution of this paper is twofold. Firstly, a novel mapping scheme for IEEE 802.16 Mobile standard is introduced, applying horizon mapping. Secondly, an efficient adaptive prediction-based scheme is devised, which is able to adjust the downlink sub-frame capacity, accordingly to the traffic load, since the standard allows the downlink-to-uplink subframe ratio to be changeable from 3:1 to 1:1. The novel adaptive horizon burst mapping (AHBM) scheme is evaluated by simulation experiments, which indicate that the proposed scheme operates effectively and efficiently, by reducing the number of unserved users, the number of unserved traffic requests, and the portion of wasted bandwidth. ©2010 IEEE.
2008
S.G. Petridou; P.G. Sarigiannidis; G.I. Papadimitriou; A.S. Pomportsis
Clustering-based scheduling: A new class of scheduling algorithms for single-hop lightwave networks Journal Article
In: International Journal of Communication Systems, vol. 21, no. 8, pp. 863-887, 2008.
Περίληψη | BibTeX | Ετικέτες: Clustering, prediction, Reservation, Scheduling, WDM star networks | Σύνδεσμοι:
@article{Petridou2008863,
title = {Clustering-based scheduling: A new class of scheduling algorithms for single-hop lightwave networks},
author = { S.G. Petridou and P.G. Sarigiannidis and G.I. Papadimitriou and A.S. Pomportsis},
url = {https://www.researchgate.net/publication/220548025_Clustering-based_scheduling_A_new_class_of_scheduling_algorithms_for_single-hop_lightwave_networks},
doi = {10.1002/dac.929},
year = {2008},
date = {2008-01-01},
journal = {International Journal of Communication Systems},
volume = {21},
number = {8},
pages = {863-887},
abstract = {In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering-Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput-delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering-based approach can be the base of a new generation of high-performance scheduling algorithms for WDM star networks.},
keywords = {Clustering, prediction, Reservation, Scheduling, WDM star networks},
pubstate = {published},
tppubtype = {article}
}
In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering-Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput-delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering-based approach can be the base of a new generation of high-performance scheduling algorithms for WDM star networks.
Διεύθυνση
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Πληροφορίες Επικοινωνίας
tel: +30 2461 056527
Email: ithaca@uowm.gr
