1,082 research outputs found

    Video Streaming in Evolving Networks under Fuzzy Logic Control

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    Power Management Strategies for Wired Communication Networks.

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    With the exponential traffic growth and the rapid expansion of communication infrastructures worldwide, energy expenditure of the Internet has become a major concern in IT-reliant society. This energy problem has motivated the urgent demands of new strategies to reduce the consumption of telecommunication networks, with a particular focus on IP networks. In addition to the development of a new generation of energy-efficient network equipment, a significant body of research has concentrated on incorporating power/energy-awareness into network control and management, which aims at reducing the network power/energy consumption by either dynamically scaling speeds of each active network component to make it capable of adapting to its current load or putting to sleep the lightly loaded network elements and reconfiguring the network. However, the fundamental challenge of greening the Internet is to achieve a balance between the power/energy saving and the demands of quality-of-service (QoS) performance, which is an issue that has received less attention but is becoming a major problem in future green network designs. In this dissertation, we study how energy consumption can be reduced through different power/energy- and QoS-aware strategies for wired communication networks. To sufficiently reduce energy consumption while meeting the desire QoS requirements, we introduce several different schemes combing power management techniques with different scheduling strategies, which can be classified into experimental power management (EPM) and algorithmic power management (APM). In these proposed schemes, the power management techniques that we focus on are speed scaling and sleep mode. When the network processor is active, its speed and supply voltage can be decreased to reduce the energy consumption (speed scaling), while when the processor is idle, it can be put in a low power mode to save the energy consumption (sleep mode). The resulting problem is to determine how and when to adjust speeds for the processors, and/or to put a device into sleep mode. In this dissertation, we first discuss three families of dynamic voltage/frequency scaling (DVFS) based, QoS-aware EPM schemes, which aim to reduce the energy consumption in network equipment by using different packet scheduling strategies, while adhering to QoS requirements of supported applications. Then, we explore the problem of energy minimization under QoS constraints through a mathematical programming model, which is a DVFS-based, delay-aware APM scheme combing the speed scaling technique with the existing rate monotonic scheduling policy. Among these speed scaling based schemes, up to 26.76% dynamic power saving of the total power consumption can be achieved. In addition to speed scaling approaches, we further propose a sleep-based, traffic-aware EPM scheme, which is used to reduce power consumption by greening routing light load and putting the related network equipment into sleep mode according to twelve flow traffic density changes in 24-hour of an arbitrarily selected day. Meanwhile, a speed scaling technique without violating network QoS performance is also considered in this scheme when the traffic is rerouted. Applying this sleep-based strategy can lead to power savings of up to 62.58% of the total power consumption

    Investigation of the tolerance of wavelength-routed optical networks to traffic load variations.

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    This thesis focuses on the performance of circuit-switched wavelength-routed optical network with unpredictable traffic pattern variations. This characteristic of optical networks is termed traffic forecast tolerance. First, the increasing volume and heterogeneous nature of data and voice traffic is discussed. The challenges in designing robust optical networks to handle unpredictable traffic statistics are described. Other work relating to the same research issues are discussed. A general methodology to quantify the traffic forecast tolerance of optical networks is presented. A traffic model is proposed to simulate dynamic, non-uniform loads, and used to test wavelength-routed optical networks considering numerous network topologies. The number of wavelengths required and the effect of the routing and wavelength allocation algorithm are investigated. A new method of quantifying the network tolerance is proposed, based on the calculation of the increase in the standard deviation of the blocking probabilities with increasing traffic load non-uniformity. The performance of different networks are calculated and compared. The relationship between physical features of the network topology and traffic forecast tolerance is investigated. A large number of randomly connected networks with different sizes were assessed. It is shown that the average lightpath length and the number of wavelengths required for full interconnection of the nodes in static operation both exhibit a strong correlation with the network tolerance, regardless of the degree of load non-uniformity. Finally, the impact of wavelength conversion on network tolerance is investigated. Wavelength conversion significantly increases the robustness of optical networks to unpredictable traffic variations. In particular, two sparse wavelength conversion schemes are compared and discussed: distributed wavelength conversion and localized wavelength conversion. It is found that the distributed wavelength conversion scheme outperforms localized wavelength conversion scheme, both with uniform loading and in terms of the network tolerance. The results described in this thesis can be used for the analysis and design of reliable WDM optical networks that are robust to future traffic demand variations

    Cost functions in optical burst-switched networks

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    Optical Burst Switching (OBS) is a new paradigm for an all-optical Internet. It combines the best features of Optical Circuit Switching (OCS) and Optical Packet Switching (OPS) while avoidmg the mam problems associated with those networks .Namely, it offers good granularity, but its hardware requirements are lower than those of OPS. In a backbone network, low loss ratio is of particular importance. Also, to meet varying user requirements, it should support multiple classes of service. In Optical Burst-Switched networks both these goals are closely related to the way bursts are arranged in channels. Unlike the case of circuit switching, scheduling decisions affect the loss probability of future burst This thesis proposes the idea of a cost function. The cost function is used to judge the quality of a burst arrangement and estimate the probability that this burst will interfere with future bursts. Two applications of the cost functio n are proposed. A scheduling algorithm uses the value of the cost function to optimize the alignment of the new burst with other bursts in a channel, thus minimising the loss ratio. A cost-based burst droppmg algorithm, that can be used as a part of a Quality of Service scheme, drops only those bursts, for which the cost function value indicates that are most likely to cause a contention. Simulation results, performed using a custom-made OBS extension to the ns-2 simulator, show that the cost-based algorithms improve network performanc

    Resource allocation and scalability in dynamic wavelength-routed optical networks.

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    This thesis investigates the potential benefits of dynamic operation of wavelength-routed optical networks (WRONs) compared to the static approach. It is widely believed that dynamic operation of WRONs would overcome the inefficiencies of the static allocation in improving resource use. By rapidly allocating resources only when and where required, dynamic networks could potentially provide the same service that static networks but at decreased cost, very attractive to network operators. This hypothesis, however, has not been verified. It is therefore the focus of this thesis to investigate whether dynamic operation of WRONs can save significant number of wavelengths compared to the static approach whilst maintaining acceptable levels of delay and scalability. Firstly, the wavelength-routed optical-burst-switching (WR-OBS) network architecture is selected as the dynamic architecture to be studied, due to its feasibility of implementation and its improved network performance. Then, the wavelength requirements of dynamic WR-OBS are evaluated by means of novel analysis and simulation and compared to that of static networks for uniform and non-uniform traffic demand. It is shown that dynamic WR-OBS saves wavelengths with respect to the static approach only at low loads and especially for sparsely connected networks and that wavelength conversion is a key capability to significantly increase the benefits of dynamic operation. The mean delay introduced by dynamic operation of WR-OBS is then assessed. The results show that the extra delay is not significant as to violate end-to-end limits of time-sensitive applications. Finally, the limiting scalability of WR-OBS as a function of the lightpath allocation algorithm computational complexity is studied. The trade-off between the request processing time and blocking probability is investigated and a new low-blocking and scalable lightpath allocation algorithm which improves the mentioned trade-off is proposed. The presented algorithms and results can be used in the analysis and design of dynamic WRONs
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