6G Systems are expected to support a variety of services over a common infrastructure that is efficiently shared through slicing. Novel Quality of Experience (QoE) architectural models and resource assignment schemes are needed that are able a) to differentiate Service Data Flows (SDFs) originating from the same or multiple user equipment (UE), b) react to changes of the underlying physical infrastructure and c) scale with the number of connected devices. Currently, this functionality is provided by centralized management and network orchestration platforms suffering scalability issues. Thus, future systems are expected to operate in a distributed manner allowing applications to directly intervene in the relevant control processes to guarantee the required QoE. In response to this, the present study focuses on the development of a novel flow assignment scheme supporting applications running at the UEs. The scheme is based on Evolutionary Game Theory (EGT) and allows the application functions (AFs) responsible for the control of the UE applications to take traffic routing and steering decisions in a fully distributed way minimizing charging costs and maximizing their QoE. The charging function of the EGT model relies on profiling data extracted from an open-source 5G platform deployed in a practically implemented testbed environment.

One of the fundamental challenges that needs to be addressed in 5G and beyond systems relates with delivery of demanding uninterrupted services to mobile users. In this context, this paper provides an overview of relevant architectural options taking into consideration user mobility requirements and proposes suitable resource allocation schemes to enable optimal service provisioning under mobility considerations. The proposed schemes are evaluated through a purposely developed multistage optimization framework. This evaluation framework facilitates optimal placement of network and compute resources minimizing the associated infrastructure operational costs. Our results have been produced using real user mobility statistics as well as lab based profiling measurements of the 5G infrastructure and provide a detailed trade-off analysis between latency and infrastructure related costs indicating optimal operational points for different scenarios.

The present study focuses on the development of a dynamically re-configurable Information Communication Technology (ICT) infrastructure to support the sustainable development of railway network. Once data have been collected, the extracted knowledge is used to develop a set of applications that can improve the energy efficient operation of railway systems. A typical example includes the identification of the optimal driving profiles in terms of energy consumption. In the present study, this is achieved through the adoption of an optimization framework based on Data Envelopment Analysis (DEA). The performance of the proposed scheme is evaluated based on actual data collected at an operation tramway system. Preliminary results illustrate that when the proposed method is applied, a 10% reduction in the overall power consumption can be achieved.

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 CO2emissions. 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 CO2emissions by up to 60% for different levels of demand requests. The performance of the proposed provisioning scheme is compared with traditional approaches.

This paper studies energy efficient planning of elastic cloud deploying optical network infrastructures. An MILP model employing multi-service, multi-period considerations for virtualization of the underlying physical resources is proposed and validated achieving significant energy savings.

This paper is aiming at facilitating the energy-efficient operation of an integrated optical network and IT infrastructure. In this context we propose an energy-efficient routing algorithm for provisioning of IT services that originate from specific source sites and which need to be executed by suitable IT resources (e.g. data centers). The routing approach followed is anycast, since the requirement for the IT services is the delivery of results, while the exact location of the execution of the job can be freely chosen. In this scenario, energy efficiency is achieved by identifying the least energy consuming IT and network resources required to support the services, enabling the switching off of any unused network and IT resources. Our results show significant energy savings that can reach up to 55% compared to energy-unaware schemes, depending on the granularity with which a data center is able to switch on/off servers.

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.

Energy-efficient optical networks are gaining momentum as environmental-friendly solutions with reduced operational costs. Energy-efficiency can be achieved by using devices in sleep mode, i.e., a low-power, inactive state in which devices can be suddenly waken-up upon occurrence of triggering events. This paper advocates a sleep mode option for the optical devices (e.g., amplifiers, optical switches) installed for protection purposes only. These devices can be put in sleep mode to reduce the network power consumption, but they can be promptly waken up (if necessary) upon a failure occurrence. This principle is proposed and applied in Wavelength Division Multiplexing (WDM) networks with dedicated-path protection to ensure survivability against single-link failures. The main contribution of the paper is the definition of the energy-efficient network planning problem for resilient WDM networks where optical devices can be configured in sleep mode. Optimal results of the integer linear programming (ILP) problem show savings of up to 25% in the overall power consumption.

This paper focuses on next generation ubiquitous networks supporting the Future Internet. In this context, it proposes an architecture and an integration framework of wireless and wired network technologies supporting a variety of services with differing service requirements. More specifically the i

This paper addresses the problem of survivable lightpath provisioning in wavelength division multiplexed networks taking into consideration the optical signal performance degradation triggered by the physical impairments of transparent optical networks as a routing constraint. This work proposes a resource efficient provisioning scheme that takes into consideration both working and protection traffic. In order to maximize the utilization of spare capacity the backup multiplexing technique is applied in combination with suitable wavelength assignment algorithms differentiating the two types of traffic. In addition, to provide the required quality guarantees an impairment aware routing algorithm that incorporates the main physical layer characteristics of large-scale optical networks into its path computation process is proposed. The performance of the proposed solution is investigated and compared to other conventional RWA algorithms (i.e shortest path, minimum hop and random wavelength assignment) through simulations of a typical mesh long-haul network.

Grid-GMPLS (G2MPLS) is conceived as a powerful network control plane solution that enhances the standard ASON/GMPLS architecture providing single-step resource reservation, co-allocation and maintenance of both network and Grid resources. This paper identifies and discusses the main issues and considerations that arise by network research and educational networks and network operators in order to facilitate the dissemination of G2MPLS control plane. Interoperability issues and backwards compatibility with existing network control planes centre the scope of this study, which intends to demonstrate the feasibility of adopting the proposed architectures.

This paper presents a novel hybrid optical burst/circuit switched (OBCS) ingress edge router solution towards ubiquitous photonic Grid networking. It is based on the deployment of Grid application-aware packet classification and burst aggregation algorithms as well as agile and intelligent optical resource allocation. The proposed solution utilises a generic and highly scalable multi-dimension classification mechanism able to provide wire-speed classification at high bit rates up to 40 Gbps. The mechanism is responsible for per application switching (OBS/OCS) service selection and Grid Differentiated Service (GridDiffServ) provisioning. A CoS-Traffic-Time-LEngth-Service-oriented aSembly (COST2LESS) algorithm has been proposed to smooth the incoming Grid traffic and provide some CoS differentiation and initial results are presented. An agile optical data transmission mechanism has been also implemented to map Grid traffic asynchronously into optical bursts or wavelength channels (data plane) based on user/application-specific requirements. Furthermore an optical burst Ethernet switched (OBES) transport mechanism has been implemented to transport out-of- band control plane signalling information.