Modelling and evaluation of QCN using coloured petri nets

Mliki, Hela; Fourati, Lamia Chaari; Kamoun, Lotfı

doi:10.1007/s12083-017-0547-7

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Moreover, forward feedback control is applied in forward explicit CN (FECN) [26], and enhanced FECN (E-FECN) [25] to notify end stations about congestions. The study in [36,37] is carried out in order to help understand the QCN scheme and derive performance measures. BCN and QCN mechanisms can recover from congestion more quickly than FECN and E-FECN mechanisms because feedbacks are sent directly to the upstream devices in the former.…”

Section: Cn Schemesmentioning

confidence: 99%

Comparative study of congestion notification techniques for hop‐by‐hop‐based flow control in data centre Ethernet

et al. 2018

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Data centre Ethernet (DCE) is a budding research area that has received considerable attention from the ICT sector. The traditional DCEs are considered unreliable despite being widely used in modern day data centres. In Ethernet intermediate layer 2 switching devices, the outgoing traffic is faster than the incoming traffic and therefore results in packet drops. Ethernet reliability is provided by the upper layer protocols, which is outlaw to the initial concept of the network. As such, various congestion notification (CN) techniques for hop-by-hop-based flow control have been proposed for layer 2 devices to address the issue of silent packet drops. However, a simulation-based evaluation of IEEE standards that solely focus on CN techniques remains lacking. This study investigates CN techniques for layer 2 devices that employ a hop-by-hop-based flow control. It also highlights the challenges confronting CN techniques in determining the optimal buffer threshold. In addition, FCoE protocol and its relation to CN are emphasized. A simulation-based evaluation of IEEE standards (IEEE 802.3x and IEEE 802.1Qbb) is performed on a hop-by-hop-based flow control with the traditional IEEE 802.3 Ethernet under different traffic loads. The parameters, such as throughput, end-to-end delay, and buffer space utilization, are evaluated through a simulation-based comparison.

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Section: Cn Schemesmentioning

confidence: 99%

Comparative study of congestion notification techniques for hop‐by‐hop‐based flow control in data centre Ethernet

et al. 2018

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“…Previous studies explored various service selection criteria and models, primarily using quality of service (QoS) as a key criterion to optimize multiple criteria 1 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China decision models, in an approach called QoS-aware studies Mliki et al, 2018;Zheng et al, 2016). However, these studies only consider service qualities at query time, ignoring strong QoS attributes instantaneity (e.g.…”

Section: Introductionmentioning

confidence: 99%

Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences

2021

Concurrent Engineering

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Selecting the most efficient from several functionally equivalent services remains an ongoing challenge. Most manufacturing service selection methods regard static quality of service (QoS) as a major competitiveness factor. However, adaptations are difficult to achieve when variable network environment has significant impact on QoS performance stabilization in complex task processes. Therefore, dynamic temporal QoS values rather than fixed values are gaining ground for service evaluation. User preferences play an important role when service demanders select personalized services, and this aspect has been poorly investigated for temporal QoS-aware cloud manufacturing (CMfg) service selection methods. Furthermore, it is impractical to acquire all temporal QoS values, which affects evaluation validity. Therefore, this paper proposes a time-aware CMfg service selection approach to address these issues. The proposed approach first develops an unknown-QoS prediction model by utilizing similarity features from temporal QoS values. The model considers QoS attributes and service candidates integrally, helping to predict multidimensional QoS values accurately and easily. Overall QoS is then evaluated using a proposed temporal QoS measuring algorithm which can self-adapt to user preferences. Specifically, we employ the temporal QoS conflict feature to overcome one-sided user preferences, which has been largely overlooked previously. Experimental results confirmed that the proposed approach outperformed classical time series prediction methods, and can also find better service by reducing user preference misjudgments.

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Modelling and evaluation of QCN using coloured petri nets

Cited by 2 publications

References 18 publications

Comparative study of congestion notification techniques for hop‐by‐hop‐based flow control in data centre Ethernet

Comparative study of congestion notification techniques for hop‐by‐hop‐based flow control in data centre Ethernet

Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences

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