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5G networks will comprise multiple, versatile infrastructures at finest granularity consisting of multiple disaggregated pools of network, compute and storage resources. To support the 5G network architectures and satisfy the access network demanding performance requirements, transport networks consisting of various converging technologies shall provide mechanisms to support deployment flexibility and scalability. The various deployment alternatives of transport network technologies and topologies in real network deployments shall take into account various factors such as area specifics, technologies' deployment feasibility, traffic/usage forecasts considering long-term services roadmaps and certainly, the implicated costs. Thus, transport network planning and dimensioning shall be tightly accompanied by the techno-economic analysis of the various deployment alternatives. This paper provides insights of 5G transport network technologies and deployments as retrieved through macroscopic and microscopic technoeconomic analyses and demonstrates their applicability on the architectural concepts of 5G-PICTURE 5G-PPP project. [ABSTRACT FROM AUTHOR]

To address the limitations of current radio access networks (RANs), centralized RANs adopting the concept of flexible splits of the BBU functions between radio units (RUs) and the central unit have been proposed. This concept can be implemented combining both the Mobile Edge Computing model and relatively large-scale centralized Data Centers. This architecture requires high-bandwidth/low-latency optical transport networks interconnecting RUs and compute resources adopting SDN control. This paper proposes a novel mathematical model based on Evolutionary Game Theory that allows to dynamically identify the optimal split option with the objective to unilaterally minimize the infrastructure operational costs in terms of power consumption. Optimal placement of the SDN controllers is determined by a heuristic algorithm in such a way that guarantees the stability of the whole system. Finally, multi-agent learning methods were investigated in order to expand the model to more sophisticated scenarios where many RUs with limited information are interacting. [ABSTRACT FROM AUTHOR]

This paper focuses on a Centralized Radio Access Network solution adopting the concept of resource disaggregation. In this context, it proposes a heuristic suitable to optimally assign Base Band Unit processing functions in softwarized Radio Access Networks to different servers, taking into consideration their processing requirements with the aim to minimize the overall energy consumption. It also proposes the adoption of live migration of virtualized resources, in order to dynamically reallocate these functions to different servers that better match the continuously changing characteristics of 5G services, for increased energy efficiency purposes. The benefits associated with live migration are quantified through a series of experiments. Our results show a reduction of the number of switched-on servers through live migration that leads to a notable improvement in terms of resource and energy efficiency. [ABSTRACT FROM AUTHOR]

The time shared optical network (TSON) has been proposed as a dynamic optical transport network solution to provide high bandwidth and low latency connectivity in support of 5G technology and beyond. This work reviews the TSON evolution stages developed in the framework of the U.K. national project Towards Ultimate Convergence of All Networks (TOUCAN). The details of the TSON architecture and its various development phases are discussed, and the performance of its latest implementation is evaluated through relevant demonstration activities across the Smart Internet Lab's 5G (5GUK) test network. [ABSTRACT FROM AUTHOR]

This paper focuses on a Mobile Edge Cloud (MEC)-assisted 5G network architecture in which an optical transport network is used to interconnect MEC servers processing low layer functions and Central Cloud servers processing upper layer functions of the LTE protocol stack. Traditionally, the problem of Based Band Unit (BBU) function assignment in cloud environments has been addressed through Integer Linear Programming (ILP) formulations having the disadvantage of increased computational complexity. To address this issue, we initially propose a relaxation framework that reduces computational complexity. To further accelerate convergence, the proposed relaxation algorithm is coupled with Hierarchical Random Graph (HRG) theory. Taking advantage of the hierarchical structure of the 5G communication and compute infrastructure, HRG theory can be employed to generate simple tree topologies that reflect the statistical properties of the originally complex 5G infrastructure. Numerical results indicate that the proposed approach outperforms traditional centralized C-RAN schemes with much faster convergence times. [ABSTRACT FROM AUTHOR]

The increased carrier bandwidth and the number of antenna elements expected in 5G networks require a redesign of the traditional IP-based backhaul and CPRI-based fronthaul interfaces used in 4G networks. We envision future mobile networks to encompass these legacy interfaces together with novel 5G RAN functional splits. In this scenario, a consistent transport network architecture able to jointly support backhaul and 4G/5G fronthaul interfaces is of paramount importance. In this article we present 5G-XHaul, a novel transport network architecture featuring wireless and optical technologies and a multi-technology software defined control plane, which is able to jointly support backhaul and fronthaul services. We have deployed and validated the 5G-XHaul architecture in a city-wide testbed in Bristol. [ABSTRACT FROM AUTHOR]

This paper focuses on converged access/metro infrastructures for 5G services, proposing a common transport network integrating wireless and optical network segments with compute/storage domains. To identify the optimal mix of transport network technologies (optical/ wireless) and processing modules that are required to support 5G services in a cost- and energy-efficient manner, a two-stage optimization framework is proposed. In the first stage, a multi-objective optimization scheme, focusing on the transport network segment, tries to jointly minimize the capital expenditure of the converged 5G network. This is performed through the identification of the optimal mix of wireless and optical transport network technologies. The second stage focuses on the compute network segment and aims at identifying suitable processing modules to which operational 5G services need to be allocated. The performance of the proposed approach is examined using realistic traffic statistics for various network technology choices including mmWave and passive optical networks (PONs) for transport, fixed, and elastic grid optical networks across a city-wide topology in Bristol, UK. [ABSTRACT FROM AUTHOR]

This article presents a converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul. The 5G-XHaul infrastructure adopts a common fronthaul/backhaul network solution, deploying a wealth of wireless technologies and a hybrid active/passive optical transport, supporting flexible fronthaul split options. This infrastructure is evaluated through a novel modeling. Numerical results indicate significant energy savings at the expense of increased end-user service delay. [ABSTRACT FROM AUTHOR]

This paper focuses on the design of cloud service provisioning schemes over converged optical network and computing infrastructures. A major issue linked with the operation of these infrastructures is their sustainability in terms of energy consumption and CO2 emissions. Given that most of the power consumption of the converged infrastructures is attributed to the operation of computing resources, the concept of powering-up computing resources with renewable energy sources is becoming a promising solution. However, the time variability and uncertainty of cloud services as well as the stochastic nature of renewable energy sources makes the evaluation and exploitation of such systems challenging. To address this challenge, we propose a novel service provisioning scheme based on stochastic linear programming (SLP). To cope with the increasing computational complexity inherent in SLP formulations, dimensionality reduction techniques, such as the sample average approximation and Lagrangian relaxation, are adopted. Based on measurements from the National Solar Radiation Data Base, traffic statistics from the Internet2 measurement archive, and experimentations with real network configurations, it is proven that the proposed scheme is stable and achieves fast convergence to the optimal solution, while at the same time reduces the overall CO2 emissions by up to 60% for different levels of demand requests. The performance of the proposed provisioning scheme is compared with traditional approaches. [ABSTRACT FROM PUBLISHER]

This paper focuses on the design of service provisioning schemes suitable for mega data center (DC) infrastructures. A major issue linked with the operation of these infrastructures is scalability caused by the increased number of resources available in megasize highly dense DCs and the associated requirements for control and management information. To address this scalability issue, we propose for the first time to monitor and optimize the operation of mega DCs adopting graph factorization combined with compressive sensing theories. This approach takes advantage of the spatial and temporal correlation of compute, and network resource requests, to monitor and optimize metrics, such as delay and energy with reduced control and management information. Our modeling results indicate drastically reduced volume of traffic transferred from the data to control plane and number of optimization process variables. [ABSTRACT FROM PUBLISHER]

To support the current trends in cloud, Internet of Things, 5G, etc., massive amounts of data need to be processed and stored with very different performance requirements in terms of capacity, granularity, delay, etc. These requirements drive the need for both mega-size data centers (DCs) and distributed micro DCs interconnected with high-speed communication links. This special issue focuses on the key role of optical networking in meeting these requirements through high-capacity, energy-efficient, and flexible connectivity, and presents recent advancements in DC architectures, network solutions, and optical technologies needed to interconnect computing and storage resources within and between DCs. [ABSTRACT FROM AUTHOR]

Future networks are set to provide a wide range of services over a multitude of technologies carrying a broad range of traffic profiles. The emerging mobile cloud computing applications are imposing numerous challenges on network operators to enable ubiquitous and on-demand service provisioning. To cope with the rising demands wired and wireless networks, together with IT infrastructures, need to be part of a converged platform. They should allow end-to-end network and cloud composition and visualization, which are required for ubiquitous and distributed access. Flexible and programmable optical networks can integrate and merge IT and wireless technologies effectively and efficiently. In view of this, we propose the use of a time shared optical network (TSON) for the interconnection of wireless access networks and IT resources and expand its functionality and dynamicity for integration in a converged yet heterogeneous environment. TSON is also extended to facilitate a virtualization-enabled multi-technology echo system. The extensions aim at facilitating hardware virtualization of the TSON technology and include support of higher rates, flexible subwavelength or wavelength modes of operation, and dynamic memory allocation facilitating infrastructure virtualization and re-programming. An experimental implementation evaluates the impact of TSONs variable aggregation buffer memory requirements on different frame sizes and its effect on network bandwidth and latency. Using experimental data, simulation studies introduce and investigate large-scale scenarios of hardware virtualization and investigate the resource efficiency advantages enabled by the proposed solution. A theoretical evaluation of the network performance of the proposed TSON solution is also provided, and results on the delay performance of the converged infrastructure and the associated trade-offs are presented. [ABSTRACT FROM PUBLISHER]

Motivated by the diffusion of cloud-based services and the need for high-performance flexible networks to support interconnection of geographically dispersed data centers, this letter focuses on the deployment of correlated cloud services over optical networks. A stochastic optimization model that aims at minimizing the total service deployment cost has been developed. Service correlation is modeled as a stationary stochastic process and the sample average approximation method is used to solve the relevant problems. The results quantify the impact of service correlation and the benefits of applying stochastic optimization when planning suitable infrastructures. [ABSTRACT FROM PUBLISHER]

This article focuses on planning and replanning of virtual infrastructures over optical cloud infrastructures comprising integrated optical network and IT resources. This concept has been developed in the context of the European project GEYSERS. GEYSERS has proposed a novel multi-layer architecture, described in detail, that employs optical networking capable of provisioning optical network and IT resources for end-to-end cloud service delivery. The procedures required to perform virtual infrastructure planning and replanning at the different architecture layers are also detailed. An optimization scheme suitable to dynamically plan and replan virtual infrastructures is presented and compared to conventional approaches, and the benefits of dynamic replanning are discussed and quantified. The final project demonstration, focusing on planning, replanning, and dynamically establishing virtual infrastructures over the physical resources, is presented, while some emulation results are provided to further evaluate the performance of the GEYSERS solution. [ABSTRACT FROM AUTHOR]

This paper focuses on the concept of dynamic virtual optical networks (VONs) as a key enabling technology to support the requirements of the future Internet. To address the unpredictable nature of services and their characteristics, dynamic and on-demand planning and replanning of VONs is required. This paper proposes the use of novel modeling approaches to specifically consider the uncertain nature of traffic requests. In addition, it studies mechanisms to evaluate and minimize the impact of this uncertainty on the availability and efficiency of the virtual resources, considering at the same time requirements such as service resilience and security. The effect of periodic VON replanning is investigated and the relevant trade-offs are identified. Our modeling results show that taking into consideration the dynamic and uncertain nature of services provides significant benefits regarding the ability of the infrastructure to support these services and the associated resource efficiency. [ABSTRACT FROM PUBLISHER]

This paper focuses on the design of multiple dependable virtual infrastructures (VIs) over converged optical network and IT resources supporting uncertain elastic cloud services. VI dependability is defined as the VI ability to offer resilience in the case of IT resource failures and security guarantees in terms of isolation of VIs that share a common physical infrastructure. The VI planning optimization objective is to minimize the overall energy consumption. To address these issues together with the time variability and uncertainty of elastic cloud services, a novel VI planning scheme based on stochastic linear programming (SLP) is proposed. To cope with the increasing computational complexity inherently imposed in SLP formulations, the sample average approximation technique and Lagrangian relaxation are used to solve the SLP problem in an efficient manner. Our modeling results illustrate interesting trade-offs between the overall energy consumption of the VIs and the dependability impact on the energy consumption and the utilization of the infrastructure resources. [ABSTRACT FROM PUBLISHER]

Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a routing and scheduling algorithm for a cloud architecture that targets minimal total energy consumption by enabling switching off unused network and/or information technology (IT) resources, exploiting the cloud-specific anycast principle. A detailed energy model for the entire cloud infrastructure comprising a wide-area optical network and IT resources is provided. This model is used to make a single-step decision on which IT end points to use for a given request, including the routing of the network connection toward these end points. Our simulations quantitatively assess the EE algorithm's potential energy savings but also assess the influence this may have on traditional quality-of-service parameters such as service blocking. Furthermore, we compare the one-step scheduling with traditional scheduling and routing schemes, which calculate the resource provisioning in a two-step approach (selecting first the destination IT end point and subsequently using unicast routing toward it). We show that depending on the offered infrastructure load, our proposed one-step calculation considerably lowers the total energy consumption (reduction up to 50%) compared to the traditional iterative scheduling and routing, especially in low- to medium-load scenarios, without any significant increase in the service blocking. [ABSTRACT FROM PUBLISHER]

This paper presents a detailed study of planning virtual infrastructures (VIs) over a physical infrastructure comprising integrated optical network and data center resources with the aim of enabling sharing of physical resources among several virtual operators and services. Through the planning process, the VI topology and virtual resources are identified and mapped to the physical resources. Our study assumes a practical VI demand model without any in advance global knowledge of the VI requests that are handled sequentially. Through detailed integer linear program modeling, two objective functions — one that minimizes the overall power consumption of the infrastructure and one that minimizes the wavelength utilization — are compared. Both are evaluated for the virtual wavelength path and wavelength path optical network architectures. The first objective results in power consumption savings and the two optical network architectures provide similar performances. However, the trend changes for higher load values, due to the inefficient wavelength utilization that the first objective leads to. Finally, we compare the virtual infrastructures created by the two objectives through online traffic provisioning simulations. The objective minimizing wavelength utilization results in VIs suffering higher request blocking compared to the VIs created by the objective minimizing the overall power consumption. [ABSTRACT FROM PUBLISHER]

Although the problem of dimensioning an optical transport network is not new, the consideration of signal quality degradation caused by the optical medium calls for revisiting the problem in the context of dimensioning optical wavelength division multiplexing (WDM) networks. This paper addresses the issue of minimum-cost planning of long-reach WDM networks in combination with optoelectronic signal regeneration as a countermeasure for sanitizing the signal quality of lightpaths that are found to be impaired. The commonly used method of placing regenerators proportionally to the physical distance covered by a lightpath is evaluated in a realistic dimensioning scenario and for various heterogeneity degrees of optical equipment, showing that it is plagued with a serious tradeoff between efficacy and cost of regeneration. As a remedy, we propose a novel method for design/dimensioning and regeneration placement for WDM networks that employs impairment-awareness. Through experimentation with real optical network configurations and for varying heterogeneity of optical equipment, the proposed method is shown to break the aforementioned tradeoff, resulting in significant reduction in regeneration effort compared to distance-based regeneration. This is achieved without compromising the signal quality of any of the lightpaths selected by the dimensioning process and with increased cost efficiency. [ABSTRACT FROM PUBLISHER]

We demonstrate the use of impairment constraint routing for performance engineering of transparent metropolitan area optical networks. Our results show the relationship between blocking probability and different network characteristics such as span length, amplifier noise figure, and bit rate,and provide information on the system specifications required to achieve acceptable network performance. [ABSTRACT FROM AUTHOR]