Energy-efficient traffic engineering

The energy consumption in telecommunication networks is expected to grow considerably, especially in core networks. In this chapter, optimization of energy consumption is approached from two directions. In a first study, multilayer traffic engineering (MLTE) is used to assign energy-efficient paths and logical topology to IP traffic. The relation with traditional capacity optimization is explained, and the MLTE strategy is applied for daily traffic variations. A second study considers the core network below the IP layer, giving a detailed power consumption model. Optical bypass is evaluated as a technique to achieve considerable power savings over per-hop opticalelectronicoptical regeneration. Document type: Part of book or chapter of boo

Online regenerator placement

Connections between nodes in optical networks are realized by lightpaths. Due to the decay of the signal, a regenerator has to be placed on every lightpath after at most d hops, for some given positive integer d. A regenerator can serve only one lightpath. The placement of regenerators has become an active area of research during recent years, and various optimization problems have been studied. The first such problem is the Regeneration Location Problem (Rlp), where the goal is to place the regenerators so as to minimize the total number of nodes containing them. We consider two extreme cases of online Rlp regarding the value of d and the number k of regenerators that can be used in any single node. (1) d is arbitrary and k unbounded. In this case a feasible solution always exists. We show an O(log|X|⋅ logd)-competitive randomized algorithm for any network topology, where X is the set of paths of length d. The algorithm can be made deterministic in some cases. We show a deterministic lower bound of Ω( log(|E|/d)⋅logd log(log(|E|/d)⋅logd) ), where E is the edge set. (2) d = 2 and k = 1. In this case there is not necessarily a solution for a given input. We distinguish between feasible inputs (for which there is a solution) and infeasible ones. In the latter case, the objective is to satisfy the maximum number of lightpaths. For a path topology we show a lower bound of √ l /2 for the competitive ratio (where l is the number of internal nodes of the longest lightpath) on infeasible inputs, and a tight bound of 3 for the competitive ratio on feasible inputs

Design cost and spectrum efficiency comparison of fixed-grid and flex-grid optical networks with grooming

This paper deals with the design of optical networks aiming to minimize the design cost and the spectrum usage. We present an optimization method that is able to find the optimal solutions of relevant sized instances. We apply the method to realistic case studies. With the obtained solutions, we make a cost and spectrum efficiency comparison analysis between fixed-grid and flex-grid optical networks. The results show that flex-grid gains are significant over the fixed-grid alternatives only after the introduction of 400 Gbps line rates and marginal gains are obtained without this line rate

Cross-layer modeling and optimization of next-generation internet networks

Scaling traditional telecommunication networks so that they are able to cope with the volume of future traffic demands and the stringent European Commission (EC) regulations on emissions would entail unaffordable investments. For this very reason, the design of an innovative ultra-high bandwidth power-efficient network architecture is nowadays a bold topic within the research community. So far, the independent evolution of network layers has resulted in isolated, and hence, far-from-optimal contributions, which have eventually led to the issues today's networks are facing such as inefficient energy strategy, limited network scalability and flexibility, reduced network manageability and increased overall network and customer services costs. Consequently, there is currently large consensus among network operators and the research community that cross-layer interaction and coordination is fundamental for the proper architectural design of next-generation Internet networks. This thesis actively contributes to the this goal by addressing the modeling, optimization and performance analysis of a set of potential technologies to be deployed in future cross-layer network architectures. By applying a transversal design approach (i.e., joint consideration of several network layers), we aim for achieving the maximization of the integration of the different network layers involved in each specific problem. To this end, Part I provides a comprehensive evaluation of optical transport networks (OTNs) based on layer 2 (L2) sub-wavelength switching (SWS) technologies, also taking into consideration the impact of physical layer impairments (PLIs) (L0 phenomena). Indeed, the recent and relevant advances in optical technologies have dramatically increased the impact that PLIs have on the optical signal quality, particularly in the context of SWS networks. Then, in Part II of the thesis, we present a set of case studies where it is shown that the application of operations research (OR) methodologies in the desing/planning stage of future cross-layer Internet network architectures leads to the successful joint optimization of key network performance indicators (KPIs) such as cost (i.e., CAPEX/OPEX), resources usage and energy consumption. OR can definitely play an important role by allowing network designers/architects to obtain good near-optimal solutions to real-sized problems within practical running times

Multi-Band Optical Networks Capacity, Energy, and Techno-Economic Assessment

L'abstract è presente nell'allegato / the abstract is in the attachmen

Green Saudi National Fibre Network (SNFN)

In 2015, there were more than 21 Million active users of the Internet in Saudi Arabia. In the present paper, we consider minimizing the power consumption of the Saudi National Fibre Network (SNFN) by formulating the problem as a mixed integer linear programming (MILP) model. Firstly, we optimize the location of single or multiple data centres in the SNFN under a traffic profile based on a gravity model where the production rate and attractiveness of each node is proportional to the population of that node. We evaluate the network power consumption considering three scenarios of data centre locations. The MILP model results show that identifying the optimum data centre locations can save up to 53% of the network power consumption compared to the random data centre locations. Secondly, we optimize the SNFN physical topology considering different data centers locations. Moreover, the model results show that optimizing the network physical topology can save up to 76% of the total power consumption compared to the current topology

Optimizing busy time on parallel machines

We consider the following fundamental scheduling problem in which the input consists of n jobs to be scheduled on a set of identical machines of bounded capacity g (which is the maximal number of jobs that can be processed simultaneously by a single machine). Each job is associated with a start time and a completion time, it is supposed to be processed from the start time to the completion time (and in one of our extensions it has to be scheduled also in a continuous number of days, this corresponds to a two-dimensional version of the problem). We consider two versions of the problem. In the scheduling minimization version the goal is to minimize the total busy time of machines used to schedule all jobs. In the resource allocation maximization version the goal is to maximize the number of jobs that are scheduled for processing under a budget constraint given in terms of busy time. This is the first study of the maximization version of the problem. The minimization problem is known to be NP-Hard, thus the maximization problem is also NP-Hard. We consider various special cases, identify cases where an optimal solution can be computed in polynomial time, and mainly provide constant factor approximation algorithms for both minimization and maximization problems. Some of our results improve upon the best known results for this job scheduling problem. Our study has applications in power consumption, cloud computing and optimizing switching cost of optical networks

Evaluation of the impact of resource disaggregation in future optical transport networks

The communications industry is experiencing constant transformation. Telecom operators consider Network Disaggregation a potential approach to redesign their current network architecture in order to thrive. It focuses on decoupling the optical transport hardware into independent functional blocks, combined with open-source orchestration systems, to abstract the control layer from the physical layer, acquiring software-based control and automation features. The key perceived benefits include reducing vendor lock-in, drive innovation and evolution, and offer flexibility to deploy the best-in-class equipment that fits the network needs, regardless of the supplier. However, there is uncertainty regarding the performance of a disaggregated system, with the introduction of interoperable open nodes to the network, a demerit on the reach of the propagated optical signals is expected compared to a traditional single-vendor system. In this regard, this thesis evaluates the impact of disaggregation on the network performance, specifically, considering several levels of lightpaths' reach reduction, the average number of connections which are denied service is estimated. Since signal regeneration emerges as the straight answer to overcome the reach limitations, its influence on the behavior of the network is analyzed as well. Moreover, the traffic grooming concept is introduced as an alternative to improve the network performance. The idea is to take benefit of the additional optical to electrical conversions performed for signal regeneration and groom low rate traffic streams in the already established lightpaths, looking to increase the capacity of the network. To this end, a network simulator was developed to test a disaggregated system under several conditions as varying the number of regenerators available in the network, allowing or not traffic grooming, and applying different modulation formats or connections' traffic profiles, all of them are compared to the behavior of a traditional integrated system. Overall the simulation results demonstrate an important demerit of the performance of the network as a function of the transmission reach reduction, forcing the use of additional regenerator nodes. Nevertheless, when implementing traffic grooming with a limited number of regenerators, a significant decrease of the network blocking probability is achieved. Thus, network operators must analyze if this benefit plus the advantages of an open model prevails to the cost generated by the additional OEO nodes

Regenerator placement and fault management in multi-wavelength optical networks.

Shen, Dong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 98-106).Abstracts in English and Chinese.Abstract --- p.i摘要 --- p.ivAcknowledgements --- p.vTable of Contents --- p.viChapter Chapter 1 --- Background --- p.1Chapter 1.1 --- Translucent Optical Networks --- p.1Chapter 1.1.1 --- The Way Towards Translucent --- p.1Chapter 1.1.2 --- Translucent Optical Network Architecture Design and Planning --- p.3Chapter 1.1.3 --- Other Research Topics in Translucent Optical Networks --- p.6Chapter 1.2 --- Fault Monitoring in All-Optical Networks --- p.12Chapter 1.2.1 --- Fault Monitoring in Network Layer's Perspective --- p.12Chapter 1.2.2 --- Passive Optical Monitoring --- p.14Chapter 1.2.3 --- Proactive Optical Monitoring --- p.16Chapter 1.3 --- Contributions --- p.17Chapter 1.3.1 --- Translucent Optical Network Planning with Heterogeneous Modulation Formats --- p.17Chapter 1.3.2 --- Multiplexing Optimization in Translucent Optical Networks --- p.19Chapter 1.3.3 --- An Efficient Regenerator Placement and Wavelength Assignment Scheme in Translucent Optical Networks --- p.20Chapter 1.3.4 --- Adaptive Fault Monitoring in All-Optical Networks Utilizing Real-Time Data Traffic --- p.20Chapter 1.4 --- Organization of Thesis --- p.22Chapter Chapter 2 --- Regenerator Placement and Resource Allocation Optimization in Translucent Optical Networks --- p.23Chapter 2.1 --- Introduction --- p.23Chapter 2.2 --- Translucent Optical Network Planning with Heterogeneous Modulation Formats --- p.25Chapter 2.2.1 --- Motivation and Problem Statements --- p.25Chapter 2.2.2 --- A Two-Step Planning Algorithm Using Two Modulation Formats to Realize Any-to-Any Topology Connectivity --- p.28Chapter 2.2.3 --- Illustrative Examples --- p.30Chapter 2.2.3 --- ILP Formulation of Minimizing Translucent Optical Network Cost with Two Modulation Formats under Static Traffic Demands --- p.34Chapter 2.2.4 --- Illustrative Numeric Examples --- p.42Chapter 2.3 --- Resource Allocation Optimization in Translucent Optical Networks --- p.45Chapter 2.3.1 --- Multiplexing Optimization with Auxiliary Graph --- p.45Chapter 2.3.2 --- Simulation Study of Proposed Algorithm --- p.51Chapter 2.3.3 --- An Efficient Regenerator Placement and Wavelength Assignment Solution --- p.55Chapter 2.3.4 --- Simulation Study of Proposed Algorithm --- p.60Chapter 2.4 --- Summary --- p.64Chapter Chapter 3 --- Adaptive Fault Monitoring in All-Optical Networks Utilizing Real-Time Data Traffic --- p.65Chapter 3.1 --- Introduction --- p.65Chapter 3.2 --- Adaptive Fault Monitoring --- p.68Chapter 3.2.1 --- System Framework --- p.68Chapter 3.2.2 --- Phase 1: Passive Monitoring --- p.70Chapter 3.2.3 --- Phase 2: Proactive Probing --- p.71Chapter 3.2.4 --- Control Plane Design and Analysis --- p.80Chapter 3.2.5 --- Physical Layer Implementation and Suggestions --- p.83Chapter 3.3 --- Placement of Label Monitors --- p.83Chapter 3.3.1 --- ILP Formulation --- p.84Chapter 3.3.2 --- Simulation Studies --- p.86Chapter 3.3.3 --- Discussion of Topology Evolution Adaptiveness --- p.93Chapter 3.4 --- Summary --- p.95Chapter Chapter 4 --- Conclusions and Future Work --- p.95Chapter 4.1 --- Conclusions --- p.96Chapter 4.2 --- Future Work --- p.97Bibliography --- p.98Publications during M.Phil Study --- p.10