QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm

Wang, Xingwei; Cheng, Hui; Huang, Min

doi:10.1016/j.eswa.2014.01.020

Cited by 27 publications

(9 citation statements)

References 42 publications

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“…Sickel et al used DE in developing a power plant control application for a reference governor to produce an optimal group of points for controlling a power plant that was produced by [31]. Wang et al proposed a flexible QoS multicast routing algorithm for the next-generation Internet that improves the quality of service (QoS) of multicasts to manage the increasing demand of network resources [32]. With respect to the electric power systems industry, Ela et al applied DE to determine the optimal power flow [33].…”

Section: De Applicationsmentioning

confidence: 99%

Differential Evolution: A Survey and Analysis

2018

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Differential evolution (DE) has been extensively used in optimization studies since its development in 1995 because of its reputation as an effective global optimizer. DE is a population-based metaheuristic technique that develops numerical vectors to solve optimization problems. DE strategies have a significant impact on DE performance and play a vital role in achieving stochastic global optimization. However, DE is highly dependent on the control parameters involved. In practice, the fine-tuning of these parameters is not always easy. Here, we discuss the improvements and developments that have been made to DE algorithms. In particular, we present a state-of-the-art survey of the literature on DE and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques.

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Section: De Applicationsmentioning

confidence: 99%

Differential Evolution: A Survey and Analysis

2018

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“…Однак при наданні мультимедійних сервісів використання графових моделей та зазначених комбінаторних алгоритмів може призвести до зниження ефективності функціонування ТКМ через те, що вони не враховують в явному виді параметри досить інтенсивних мультимедійних потоків та пропускні здатності каналів зв'язку мережі, що може на практиці призвести до перевантаження мережі. У зв'язку з цим актуальним напрямком розвитку рішень щодо багатоадресної маршрутизації є використання саме потокових моделей і методів, розробці та вдосконаленню яких присвячені, наприклад, такі роботи [8][9][10][11][12][13][14].…”

Section: вступunclassified

“…Проте коефіцієнт завантаженості каналу E , 13 дорівнював 0,67, а каналу E , 23 -0,52, тобто вони критично не впливали на значення критерію оптимальності (11), а умови (2), (4)-(7), (9) в явному вигляді не забороняли протікання потоку в цих каналах зв'язку. Подібна ситуація не виникала при використанні математичної моделі (2)-(8), тому що всі маршрутні змінні (2) безпосередньо впливали на значення критерію оптимальності (8), тобто використання того чи іншого каналу призводило до зростання (8). Тому у запропоновану вдосконалену модель багатоадресної маршрутизації для попередження випадків неефективного використання канального ресурсу пропонується ввести ряд додаткових умов.…”

Section: дослідження вдосконаленої математичної моделі багатоадрunclassified

Improvement of the flow-based multicast routing model on the principles of Traffic Engineering technology

Nevzorova¹,

Sleiman²,

Mersni³

et al. 2019

Problemi Telekomunìkacìj

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The paper proposes to improve the mathematical model of multicast routing with balanced use of network resource in accordance with the requirements of the concept of Traffic Engineering (TE). The model is based on the optimality criterion, which quantitatively equals the minimization of the utilization rate of the most downloaded network link. A research of the proposed improved model on the number of network structures was conducted. The research found that when using the optimization criterion of minimization of the utilization rate of the most loaded network link, inappropriately loaded links occur. This is caused by the fact that utilization coefficients of these links are not the highest in the network, and they are not critical to the value of the optimality criterion, and therefore the flow of packets in those links was not prohibited. To solve this problem in the work it is proposed to introduce two additional conditions into the model, the fulfillment of the first condition implies that the flow can come from no more than one adjacent node to an arbitrary node; and the second condition is that the flow of packets on the incoming interfaces of the transit node can only appear if its outgoing interfaces are used. Using the proposed conditions, it was possible to solve the problem of misuse of the links resource without reducing the efficiency of the calculation solutions. The use of an advanced model allows balanced use of the network resource, especially for the traffic structure, which consists of a large number of multicast flows with relatively low intensity compared to the bandwidth of the links. Електронне наукове фахове виданняжурнал «Проблеми телекомунікацій» • № 2 (25) • 2019 • http://pt.nure.ua

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“…-The cooperative-competitive learning (CCL) approach, in which the chromosomes compete and cooperate simultaneously [58][59][60][61]. This can be understood in two opposite ways: the individuals could collaborate for the same purpose and thus construct the solution together, or they could compete against each other for the same resources.…”

Section: Introductionmentioning

confidence: 99%

Designing a New Framework Using Type-2 FLS and Cooperative-Competitive Genetic Algorithms for Road Detection from IKONOS Satellite Imagery

et al. 2015

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Abstract:The growing availability of high-resolution satellite imagery provides an opportunity for identifying road objects. Most studies associated with road detection are scene-related and also based on the digital number of each pixel. Because images can provide more details (including color, size, shape, and texture), object-based processing is more advantageous. Therefore, in this paper, to handle the existing uncertainty of satellite image pixel values, using type-2 fuzzy set theory in combination with object-based image analysis is proposed. Because the main challenges of the type-2 fuzzy set are parameter tuning and extensive computations, a hybrid genetic algorithm (GA) consisting of Pittsburgh and cooperative-competitive learning schemes is proposed to address these problems. The most prominent feature of our research in this work is to establish a comprehensive object-based type-2 fuzzy logic system that enables us to detect roads in high-resolution satellite images with no training data. The validation assessment of road detection results using the proposed framework for independent images demonstrates the capability and efficiency of our method in identifying road objects. For more evaluation, a type-1 fuzzy logic system with the same structure as type-2 is tuned. Evaluations show that type-1 fuzzy logic system quality in training is very similar to that of the proposed type-2 fuzzy OPEN ACCESS Remote Sens. 2015, 7 8272 framework. However, in general, its lower accuracy, as inferred by validation assessments, makes the type-1 fuzzy logic system significantly different from the proposed type-2.

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QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm

Cited by 27 publications

References 42 publications

Differential Evolution: A Survey and Analysis

Differential Evolution: A Survey and Analysis

Improvement of the flow-based multicast routing model on the principles of Traffic Engineering technology

Designing a New Framework Using Type-2 FLS and Cooperative-Competitive Genetic Algorithms for Road Detection from IKONOS Satellite Imagery

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