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We demonstrate eavesdrop detection based on polarization signatures by analyzing polarization state changes at the receiver. We identify changes related to the normal operation and the ones caused by eavesdropping.

The article analyzes the total cost of ownership (TCO) of 5G fronthauling solutions based on analog and digital radio-over-fiber (RoF) architectures in cloud radio access networks (C-RANs). The capital and operational expenditures (CAPEX, OPEX) are assessed, for a 10-year period, considering three different RoF techniques: intermediate frequency analog RoF (IF-A-RoF), digital signal processing (DSP) assisted analog RoF (DSP-A-RoF), and digital RoF (D-RoF) based on the common public radio interface (CPRI) specifications. The greenfield deployment scenario under exam includes both fiber trenching (FT) and fiber leasing (FL) options. The TCO is assessed while varying (i) the number of aggregated subcarriers, (ii) the number of three-sector antennas located at the base station, and (iii) the mean fiber-hop length. The comparison highlights the significance that subcarrier aggregation has on the cost efficiency of the analog RoF solutions. In addition, the analysis details the contribution of each cost category to the overall CAPEX and OPEX values. The obtained results indicate that subcarrier aggregation via DSP results in high cost efficiency for a mobile fronthaul network, while a CPRI-based architecture together with FL brings the highest OPEX value.

The operation and management of software-based communication systems and services is a big challenge for infrastructure and service providers. The challenge is mainly associated with the more significant number of configurable elements and the higher dynamicity in the software-based systems than the classical ones. On the other hand, the modularity and programmability in software-based networks enabled by technologies like Software-Defined Networking (SDN) and Network Function Virtualization (NFV) provide new opportunities for operators to realize advanced network and service management strategies beyond the classical techniques. In our work, we elaborate on these new opportunities and propose a novel strategy for the management of survivable cloud services. In particular, we leverage the flexibility of SDN and NFV to combine proactive protection and reactive restoration mechanisms, and we put forward a novel strategy for enhancing the survivability of cloud services. Through comprehensive evaluations, we demonstrate that the proposed strategy offers significant benefits in terms of availability and restorability of services while reducing, at the same time, the overhead caused by the relocation of cloud services in case of failures.

We propose a novel algorithm to dimension the backup elements in an optical metro network, by considering the adoption of Unmanned Aerial Vehicles (UAVs) and wireless interfaces to realize backup wireless links. Our key idea is to efficiently find the set of node pairs that have to be connected by means of multi-hop UAV-based wireless links, which are selected based on the simulation of multiple disaster events. Results, obtained over a set of meaningful scenarios, demonstrate that our solution can greatly reduce the total installation costs compared to a naive approach, which is instead solely tailored to the restoration of the disrupted links in a given disaster scenario.

Reinforcement Learning (RL) is leading to important breakthroughs in several areas (e.g., self-driving vehicles, robotics, and network automation). Part of its success is due to the existence of toolkits (e.g., OpenAI Gym) to implement standard RL tasks. On the one hand, they allow for the quick implementation and testing of new ideas. On the other, these toolkits ensure easy reproducibility via quick and fair benchmarking. RL is also gaining traction in the optical networks research community, showing promising results while solving several use cases. However, there are many scenarios where the benefits of RL-based solutions remain still unclear. A possible reason for this is the steep learning curve required to tailor RL-based frameworks to each specific use case. This, in turn, might delay or even prevent the development of new ideas. This paper introduces the Optical Network Reinforcement-Learning-Gym (Optical RL-Gym)11The toolkit presented in this paper is available at: https://github.com/carlosnatalino/optical-rl-gym., an open-source toolkit that can be used to apply RL to problems related to optical networks. The Optical RL-Gym follows the principles established by the OpenAI Gym, the de-facto standard for RL environments. Optical RL-Gym allows for the quick integration with existing RL agents, as well as the possibility to build upon several already available environments to implement and solve more elaborated use cases related to the optical networks research area. The capabilities and the benefits of the proposed toolkit are illustrated by using the Optical RL-Gym to solve two different service provisioning problems.

Network slicing is a technique widely used in 5G networks where multiple logical networks (i.e., slices) run over a single shared physical infrastructure. Each slice may realize one or multiple services, whose specific requirements are negotiated beforehand and regulated through Service Level Agreements (SLAs). In Beyond 5G (B5G) networks it is envisioned that slices should be created, deployed, and managed in an automated fashion (i.e., without human intervention) irrespective of the technological and administrative domains over which a slice may span. Achieving this vision requires a combination of novel physical layer technologies, artificial intelligence tools, standard interfaces, network function virtualization, and software-defined networking principles. This paper provides an overview of the challenges facing network slicing automation with a focus on transport networks. Results from a selected group of use cases show the benefits of applying conventional optimization tools and machine-learning-based techniques while addressing some slicing design and provisioning problems.

The dynamic provisioning of Service Function Chain (SFC) using Virtual Network Functions (VNFs) is a challenging problem, especially for availability-constrained services. The provisioning of backup resources is often used to ensure that availability requirements are fulfilled. However, the assignment of backup resources should be carefully designed to avoid resource inefficiencies as much as possible.This paper proposes the Optional Backup with Shared Path and Shared Function (OBSPSF) strategy, which aims at improving resource efficiency while fulfilling the availability requirements of SFC requests. The strategy uses optional backup provisioning to ensure that backup resources are assigned only when strictly needed (i.e., when the SFC alone does not meet the availability constraint). Moreover, OBSPSF encourages backup sharing (among both connectivity and backup VNFs) to reduce the backup resource overhead. Results show that the strategy can accommodate orders-of-magnitude more services than benchmark heuristics from the literature.

One key challenge in 5G networks is to guarantee the survivability of services in the event of failures. This paper focuses on the hybrid cloud radio access network (H-CRAN) architecture. The proposed strategy guarantees survivability in the presence of failures affecting nodes/links in the midhaul segment (i.e., connecting the radio aggregation unit (RAU) nodes to their respective radio cloud center (RCC) nodes) as well as compute resources (i.e., servers) in the RCC nodes. In the envisioned strategy each RAU node is connected to a primary and a backup RCC node (i.e., with backup compute resources) via two node disjoint connectivity paths in the midhaul. The proposed strategy, called Shared-Path Shared-Compute Planning (SPSCP), lowers the overall design cost by trying to share as much as possible backup connectivity and compute resources among RAU nodes. This is made possible by introducing a shareability metric early into the RCC node selection process so that the chance of sharing backup resources is maximized. Simulation results show that the SPSCP strategy can lead to up to 28% cost savings when compared to conventional resilient design strategies

The paper discusses how the slice admission problem can be aided by machine learning strategies. Results show that both supervised and reinforcement learning might lead to profit maximization while containing losses due to performance degradation.

We propose a transceiver architecture for 5G fronthaul that adapts the modulation format according to the channel quality. The proposed solution operates in dual-mode using digital signal processing (DSP)-assisted analog radio-over-fiber (A-RoF) and digital radio-over-fiber (D-RoF) with multiple modulation orders. The system performance is assessed through Monte-Carlo simulations of the optical fiber link conveying wireless waveforms that utilize the filter bank multicarrier (FBMC) and orthogonal frequency-division multiplexing (OFDM) formats. The simulation results highlight the benefits of having both digital and DSP-assisted analog transmission capabilities to optimize the reach versus spectral efficiency trade-off in optical fronthaul.

We present a slice admission policy based on reinforcement learning able to maximize the profit of an infrastructure provider. Results show that when tenants request slices with different latency requirements, the proposed policy outperforms benchmark heuristics by up to 54.5%.

We present a proof-of-concept demonstration of an SDN/NFV-based orchestrator for sharing infrastructure resources among different tenants. The designed orchestrator maximizes the profit of an infrastructure provider by using a dynamic slicing approach based on big data analytics.

We present an orchestration policy based on big data analytics (BDA) to maximize the profit of infrastructure providers which dynamically slice their resources among different tenants. Results show that BDA can help to increase the profit by more than 49%.

This paper provides an assessment of the total cost of ownership (TCO) of a number of 5G fronthauling solutions based on digital and analog radio-over-fiber (RoF) architectures in cloud radio access network (C-RAN). We computed the capital and operational expenditures (CAPEX, OPEX) in the case of an optical fiber aggregation network based on a ring topology. Three different RoF architectures were considered: intermediate frequency analog RoF (IF-A-RoF), digital signal processing assisted analog RoF (DSP-A-RoF), and digital RoF (D-RoF) based on the common public radio interface (CPRI). A greenfield scenario considering both fiber deployment and fiber leasing was analyzed. The results presented in the paper show how the TCO changes with the number of aggregated carriers for the considered RoF architectures and fiber deployment strategy. They also reveal the impact that each cost category has on the overall CAPEX and OPEX value.

Failure prediction based on the anomaly detection/forecasting is becoming a reality thanks to the introduction of machine learning techniques. The orchestration layer can leverage on this new feature to proactively reconfigure cloud services that might find themselves traversing an element that is about to fail. As a result, the number of cloud service interruptions can be reduced with beneficial effects in terms of cloud service availability.Based on the above intuition, this paper presents an orchestration strategy for optical cloud networks able to reconfigure vulnerable cloud services (i.e., the ones that would be disrupted if a predicted failure happens) before an actual failure takes place. Simulation results demonstrate that, with a single link failure scenario, proactive restoration can lead to up to 97% less cloud services having to be relocated. This result brings considerable benefits in terms of cloud service availability, especially in low load conditions. It is also shown that these improvements come with almost no increase in the cloud service blocking probability performance, i.e., resource efficiency is not impacted.

Software Defined Networking enables the efficient sharing of a network infrastructure among different tenants, a concept known as network slicing. The paper presents a slicing strategy based on reinforcement learning able to efficiently orchestrate services requested by mobile and cloud tenants.

In this paper, we propose a new restoration algorithm for disaster recovery in Elastic Optical Networks (EONs). The algorithm considers the different requirements on restoration delay and bandwidth degradation while restoring over multiple routes. Furthermore, the algorithm is able to adapt the connection recover process to the post-disaster network conditions and, consequently, increase the number of restored connections. Results indicate that the proposed strategy is able to improve connections restorability and decrease bandwidth blocking probability when compared to restoration approach based on bandwidth degradation and multipath recovery.

5G is anticipated to be a significant leap in the evolution of mobile communication. Being designed to facilitate 10 to 100 times more capacity than 4G, 5G is considered to be the most cost-efficient solution to provide Fixed Wireless Access (FWA) to households on a large scale where providing last mile access using wired solution might not be economically viable. With a range of promises to deliver user experience improvements, facilitating cost-efficient data transportation between FWA users and network core still remains an unsolved issue, given the enormous volume of data that will be traversing the superior 5G network. This work addresses this compelling problem by formulating a joint-optimization framework to plan and analyze the optimal deployment of diverse optical x-haul strategies that can be used in 5G-based FWA networks. The work provides a cornerstone for deployment strategies that will be imperative to realize future-proof FWA network.

Supporting end-to-end network slices and services across operators has become an important use case of study for 5G networks as can be seen by 5G use cases published in 3GPP, ETSI as well as NGMN. This paper presents the in-depth architecture, implementation and experiment on a multi­domain orchestration framework that is able to deploy such multi-operator service as well as monitor the service for SLA compliance. Our implemented architecture allows operators to abstract their sensitive details while exposing the relevant amount of information to support inter-operator slice creation. Our experiment shows that the implemented framework is capable of creating services across operators while fulfilling the respective service requirements.

In recent years a new kind of threat, known as Hardware Trojan, is affecting the Integrated Circuit industry. Un-trusted parties in the supply chain may take advantage of the segmentation in the production to inject malicious hardware components that became active under specific circumstances. As it is impractical to identify such malicious hardware with in-lab testing, most countermeasures are based on hardware alterations, with the drawback of increasing production costs, area, and energy consumption of the final product. In this paper, on the contrary, we propose a software-based, cost-effective solution that minimizes the chance of activation of a multi-stage trigger Hardware Trojan. The approach relies on a pure-software obfuscation mechanism, which exploits an evolutionary algorithm to modify an executable program without affecting its functionalities. Such obfuscation can be used to protect critical infrastructures and operations with a reduced and predictable loss of performances. The proposed technique has been evaluated against a well-known real-world hardware attack, getting positive and promising results concerning its effectiveness.

High reliability performance of network is essential to minimize the possible network service interruption time, particularly in optical backbone networks where a large amount of data can be affected by a single failure. The existing studies on improvement of network reliability performance assume that failures of network devices are not related to the traffic load, which on the other hand, is not always true. For example, the lifetime of erbium doped fiber amplifier (EDFA) depends on the number of amplified lightpaths passing through. Encouraged by this observation, in this paper, we investigate the impact of used routing and wavelength assignment (RWA) algorithm on the number of failures in the network, and as a consequence on the network operational cost related to the failure reparation. We propose and evaluate a novel RWA approach, referred to as reliability performance aware RWA (RA-RWA), taking into account particular EDFA reliability performance characteristics with the goal of reducing the number of EDFA failures. The assessment results show that the operational cost related to EDFA failure reparation is impacted by the chosen RWA. The proposed RA-RWA provides 6% reduction, while other analyzed RWA algorithm, i.e., least loaded path (LLP), causes significant rise (up to 27%) of EDFA related failure reparation cost compared to the classical shortest path (SP) approach. In addition, RA-RWA offers further benefits in terms of reduced blocking probability compared to the SP. Concluding, we show that considering device reliability performance characteristics in RWA is important for the optical network operators as it can impact the network operational cost related to EDFA failure reparation.

Base station (BS) densification is increasingly adopted by mobile operators in order to support increasing traffic demand. However, a large number of BSs requires many backhaul connections, which may be very expensive. For this reason, provisioning high speed backhaul connections to BSs in a cost-effective way is challenging, and it is important to efficiently utilize an existing fixed network infrastructure if possible. This paper proposes two optimized infrastructure-aware planning strategies for small cells and fiber backhaul. The first strategy is referred to as joint design (JD) and is based on the joint cost minimization of small cells and fiber backhaul. The JD strategy is compared to a traditional design (TD) solution based on a two-step optimization approach. In the latter a cost-optimal small cells placement is identified first, then the corresponding minimum cost fiber backhaul deployment is determined accordingly. A comparison between these two approaches in dense 5G urban scenarios shows that the relative performance of JD and TD largely depends on the expected traffic demand and on the existing infrastructure. In dense urban areas with the average traffic levels expected for the year 2020 and beyond, JD returns up to 50% lower deployment cost in a greenfield scenario, and up to 70% lower deployment cost in a brownfield scenario. Only in areas with extremely high traffic demand (e.g., open-air festivals and stadiums) JD returns deployment costs very similar to TD.

Current trends in telecommunication networks foresee the adoption of the,fifth generation (5G) of wireless networks in the near fixture. However; a large number of people are living without coverage and connectivity. To face this issue, we consider the possibility of deploying 5G networks in rural and low-income zones. After detailing the current state-of-the-art, we consider the main challenges that need to be faced. Moreover; we define the main pillars to follow in order to deploy 5G networks in such zones, as well as a proposal of a future network architecture.

This paper proposes two wavelength overprovisioning strategies that can be used to improve the performance of path restoration in optical core networks under dynamic traffic conditions while considering single fiber link failure scenarios. The study presented in the paper shows that with the two proposed schemes it is possible to achieve nearly the same level of average connection availability and restorability typical of dedicated path protection schemes (i.e., 100%) with, on the other hand, better blocking probability performance.

The present paper aims to show and discuss the long term and continuous recordings of both meteorological and hydrodynamic data collected in a semi enclosed sea. The site in question is composed by the Mar Grande and Mar Piccolo basins (Southern Italy), which are mutually connected. In turn, the Mar Grande is joined to the Ionian Sea by means of two openings. Therefore, the system shows features typical of a lagunar environment, which is also affected by coastal heavy industry and anthropic pressure, thus being highly vulnerable. A monitoring of its hydrodynamics could be useful, allowing both to check the real-time status of the basin and promptly intervene when accidents occur and to create a dataset necessary to calibrate and validate modelling systems providing forecasts. To this, in the framework of the Italian flagship Project RITMARE, a meteo-oceanographic station, a wave-current meter and a tide gauge have been installed in the area, since December 2013. In detail, measurements of wind, waves, tides and current profiles, are acquired on site with different sampling frequencies and are transmitted on a web cloud by a router 3G, where they are stored, thus being available for download by remote users. The data acquisition and processing is managed by the research group of the Department of Civil, Environmental, Building, Engineering and Chemistry (Technical University of Bari). All the acquired data are archived in monthly time-series, examined and discussed. The analysis of currents is made in two different measuring stations for the whole year 2015, as well as the analysis of wave data. On the contrary, tide data have been assessing only recently, since August 2015. Comparisons with available recordings of the year 2014 are examined. Also spatial and temporal correlations of both waves and currents are discussed. Finally, tidal trends are shown, consistent with current inversions.

In this paper relative dispersion of satellite-tracked GPS-equipped drifters of the GLAD campaign in the Gulf of Mexico was investigated. Relative dispersion and relative velocity variance were computed pointing out different growth regimes. An exponential growth of the dispersion was detected and confirmed on the initial phase of deployment. The influence of the GPS-position error, in relation with sampling frequency, was evaluated. The presence of inertial oscillations was observed as well as their contribution to dispersion phenomena.

Each mobile network architecture able to meet the traffic requirements of future 5G services comes with its own set of benefits vs. requirements for the radio and the transport segments. This paper focuses on the energy performance of four mobile network architectures, each one with different splitting options for the baseband processing functions. The radio segment under exam is based on a new radio access technology referred to as 5G-NX, while the transport segment is based on wavelength division multiplexing (WDM). The energy consumption of each mobile network architecture is weighted against (i) the benefits for the radio segment as a function of the level of centralization of the baseband processing resources and (ii) the required transport capacity and consequently the power consumption levels needed to accommodate the backhaul, midhaul, and/or fronthaul traffic generated at each base station. Our results show that a fully centralized radio access network (C-RAN) with centralization of all the baseband functions is not a practical approach for 5G mobile networks, while a partially centralized C-RAN architecture in which the physical layer baseband processing is performed at the base station site represents a promising solution.

Presents information on the 2016 IEEE OnlineGreenComm conference. From November 14-17, 2016, the IEEE Communications Society (ComSoc) hosted the annual IEEE Online Conference on Green Communications (IEEE Online- GreenComm’16). This sixth IEEE OnlieGreenComm conference served as forum for presenting and discussing novel research and technological developments in the area of green communications, networking, and computing. By keeping the online concept of previous events, IEEE OnlineGreenComm'16 continued in spirit of "energy efficient discussion about energy-efficiency," through the conference virtual communication platform, which offers a unique and unsurpassed networking and interaction experience. With the international webcasting of the complete conference program, IEEE OnlineGreenComm’16 attendees from industry and academia participated in conference events from the comfort of their own work and/or home environments. This ecological conferencing approach of IEEE OnlineGreen- Comm'16 contributes to the reduction of greenhouse gas emissions and costs by eliminating the need for conference travel, while providing the participants with time-flexible access to live or recorded OnlineGreenComm'16 events. In this way, the conference format of IEEE OnlineGreenComm'16 offers to presenters a truly worldwide audience, with the ability to answer questions in real time through interaction with session chairs and with the aid of webcast managers.

Long-reach passive optical networks (LR-PONs) are able to effectively support the growing demand of traffic originating from residential and business customers. Failures of metro/core (M/C) nodes serving the traffic to/from the access networks covered by LR-PONs, may potentially affect hundreds or thousands of customers. One way of guaranteeing 100% survivability from single-node failures is to apply dual-homing, where each LR-PON is connected to two M/C nodes, and combine it with node-disjoint dedicated-path protection (DPP). In this paper, we present a new approach to provide network survivability against single M/C node failures. Instead of applying dedicated path protection (DPP) strategy, which can require huge amount of extra resources, we combine an unprotected network design with a dynamic multilayer restoration algorithm. Our aim is to determine a suitable amount of resource overbuild (in terms of extra transponders) needed to provide average connection availability close to that guaranteed by DPP. Preliminary results show that dimensioning for the worst-case scenario among a set of predefined M/C node failures, i.e., the one disrupting the highest number of connections, yields to a cost-effective strategy requiring up to 35% less transponders than DPP, while offering the same average connection availability.

We present the LIFETEL project, whose aim is trying to increase the device lifetime in telecommunication networks by exploiting energy-efficient techniques. In particular, we show that the lifetime of a device might increase when it is put in sleep mode. However, the device lifetime might decrease when power state variations (from sleep mode to full power) occur very frequently. Thus, there is a trade-off between the duration of sleep mode and its frequency. Moreover, we report a lifetime analysis for cellular and backbone devices, showing that the electricity saving may be exceeded by the costs due to the fact that Devices fail more frequently compared to the situation in which they are always powered on. Thus, we claim that energy-aware network algorithms should be redesigned in order not to impact and to increase (when possible) the lifetime of network devices.

Optical clouds allow for an integrated management of optical transport and cloud resources (e.g., storage and computing resources running on datacenters). In this paradigm the concept of service re ...

Wireless heterogeneous networks (HetNets) based on small cells are a cost and energy efficient alternative to provide high capacity to the end users. On the other hand, the cost and energy consumpt ...

5G mobile communications is seen as the enabler for the networked society where connectivity will be available anywhere and anytime to anyone and anything. The details of 5G are the subject to ongoing research and debate, mostly focused on understanding radio technologies that can enable the 5G vision. So far, less work has been dedicated to the challenges that 5G will pose to the transport network. This paper provides a first analysis of the key challenges to 5G transport in terms of capacity, flexibility and costs, for example. Different use cases are discussed as well as technology options and control plane concepts.

Heterogeneous network (HetNet) deployment strategies have the potential to improve the energy efficiency of mobile access networks. One key aspect to consider in HetNets is the impact of the power consumption of the backhaul, i.e., the overall energy efficiency of a HetNet deployment is affected by the backhaul technology and architecture. This paper presents a preliminary assessment of the design challenges of a future green backhaul segment for a HetNet deployment. The study is based on the analysis of the medium term future outlook (i.e., between now and the year 2025) of the main technologies used in todays'* backhaul networks (i.e., fiber, microwave and copper). It can be concluded that, even if there arc no doubts that both microwave and fiber will be predominately used in the future, the possible migration paths leading to such fiber- and microwave-dominated scenarios might be different, depending on factors such as spectrum and license costs, time to deployment, availability of equipment, and required Quality of Service (QoS) levels.

Energy and resource efficiency are two contrasting objectives to optimize in dynamic and survivable optical networks. Known solutions for improving the energy efficiency include the use of the shared path-protection (SPP) mechanism and of a low power consuming mode (i.e., sleep) for protection resources. On the other hand, resource efficiency can be improved by introducing the concept of Differentiated Reliability (DiR) which can be combined with SPP in order to match the level of provisioned protection resources to the reliability requirements for each specific demand. This paper assesses the energy efficiency of the DiR concept combined with SPP and sleep mode support. A multi-objective optimization algorithm is proposed with the intent of jointly optimizing the energy and resource efficiency when dynamically establishing lightpaths with specific reliability levels. Simulation results show that when the proposed multi-objective cost function is properly tuned, not only the SPP-based DiR approach reduces the blocking probability but it is also able to save power for any network load. By enabling sleep mode additional power savings can be achieved at low loads, leading to an overall saving of up to 25%.

Mobile communication networks account for 0.5% of the global energy consumption, a value that is expected to double within the next five years. For this reason, means of reducing the energy consumption in cellular mobile radio networks has recently gained great interest within the research community. In mobile networks the backhaul contribution to the total power consumption is usually neglected because of its limited impact compared to that of the radio base stations. However, meeting the almost exponential increase in mobile data traffic requires a large number of (mainly small) base stations. This means that backhaul networks will take a significant share of the cost and the energy consumption in future systems. Their actual contribution to the energy consumption will depend on the radio base station deployment scenario as well as on the technology and topology choices for the backhaul itself. This paper presents an initial assessment of the power consumption of two established backhaul technologies, i.e., fiber and microwave. For the microwave case, three backhaul topologies are considered, i.e., tree, ring and star, while for the fiber case only one topology is analysed, i.e., a dedicated point-to-point star. The presented results, assuming off-the-shelf products and based on todays network capacity levels, confirm the importance of considering the backhaul when minimizing the total power consumption in heterogeneous network scenarios. They also show the impact of the basic technology and topology choices of the backhaul for minimizing total power consumption.

Emerging, on-demand applications (e.g., Interactive video, ultra-high definition TV, backup storage and grid computing) are gaining momentum and are becoming increasingly important. Given the high bandwidth required by these applications, Wavelength Division Multiplexing (WDM) networks are seen as the natural choice for their transport technology. Among the various on-line strategies proposed to provision such services, the ones based on service level agreement (SLA) metrics such as setup delay tolerance and connection holding-time awareness showed a good potential in improving the overall network blocking performance. However, in a scenario where connection requests are grouped in different service classes, the provisioning success rate might be unbalanced towards those connection requests with less stringent requirements, i.e., not all the connection requests are treated in a fair way. This paper addresses the problem of how to guarantee the signal quality and the fair provisioning of different service classes, where each class corresponds to a specified target of quality of transmission (QoT). With this objective in mind three fair scheduling algorithms are proposed in a dynamic traffic scenario, each one combining in a different way the concept of both set-up delay tolerance and connection holding-time awareness. Proposed solutions are specifically taylored to facilitate the provisioning of the most stringent service class so as to balance the success rate among the different classes. Simulation results confirm that the proposed approaches are able to guarantee a fair treatment reaching up to 99% in terms of Jain's fairness index, considering the per-class success ratio, without compromising the improvements in terms of overall network blocking probability.

Energy efficiency in cellular mobile radio networks has recently gained great interest in the research community. The development of more energy efficient hardware and software components aside, effect of different deployment strategies on energy efficiency are also studied in the literature. The latter mainly consist of optimizing the number and the location of different types of base stations in order to minimize the total power consumption. Usually, in the literature, the total network power consumption is restricted to the sum of the power consumption of all base stations. However, the choice of a specific deployment also affects the exact implementation of the backhaul network, and consequently its power consumption, which should therefore be taken into account when devising energy efficient deployment. In this paper, we propose a new power consumption model for a mobile radio network considering backhaul. We then handle a case study and perform a comparison of the power consumption of three different heterogeneous network deployments, and show how backhaul has a non-negligible impact on total power consumption, which differs for different deployments. An energy efficiency analysis is also carried out for different area throughput targets.

The interest in the energy consumption of communication networks has risen in the recent years. In an effort to tackle this problem, several approaches have been presented to reduce the power consumed by the entire network infrastructure, including optical transport. Most of the solutions studied and proposed in the literature, however, pay little or no attention to the power consumed to ensure the resiliency of the overall network.

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.

The growing demand for online media content delivery and multi-player gaming is expected to increase the amount of multicast service requests in both public and private networks. Careful traffic engineering of multicast service requests is becoming increasingly essential, as establishing the lowest cost tree, e.g., shortest path tree, in the network for every individual multicast request does not always ensure a global optimization.

The traffic volume that needs to be handled by communication networks is growing very fast due to the continuously increasing number of end-users and to the new and emerging services that can be accessed on the Internet. This reflects into a need for increased network capacity, which in turn introduces higher energy consumption of the network infrastructure. In view of the scale of the network of the future, it becomes evident that investigation of technologies, methodologies and approaches that can offer energy savings are of the utmost importance. It is widely accepted that optical network technologies will have a central role in the formation and the support of the network of the future. Therefore, it is important to explore novel solutions with respect to their energy efficiency. Several attempts to reduce power consumption in optical networks can be found in the literature [1-5]. However, so far, no attention is paid to the impact of resilience in the overall network power consumption. On the other hand, wavelength division multiplexing (WDM) networks consist of very high capacity links and nodes where a single failure may disrupt an enormous number of services. Therefore, backup resources need to be provided for the purpose of survivability. Regardless of the network status, optical amplifiers and switching nodes along the backup paths are always active (i.e. switched on). Moreover, backup paths are typically longer than their respective primary paths, and therefore the total energy consumed by the spare resources in the network may be relatively high. This paper proposes a novel approach to save energy in survivable optical networks. The approach is based on appropriately handling protection resources, where a trade-off between recovery time and energy consumption is exploited. The proposed idea has been tested through simulations using a Pan-European (COST 239) and Pan-American (NSFNet) network topology. For benchmarking purposes, results for the proposed energy-aware approach are compared against a conventional one, based on shortest path routing. With the proposed approach, more than 40% energy saving has been observed in case of the COST 239 network and more than 30% in the NSFNet. To further increase the energy savings in the network, a routing algorithm (specifically tailored for the proposed energy-aware approach) is also presented, showing that an additional 20% in energy reduction is achievable.

In those networking scenarios (e.g., the stationary/mobile wireless paradigm) where limited energy storagecapabilities is a limiting factor, power efficiency has been studied extensively for a long time. In the last fewyears, the steadily growing power consumption figures of ICT [1][2] along with a recent public awareness of thepossible environmental effects, broadened the focus of the research efforts towards more power conscioussolutions also for wired networks. One promising solution going in this direction is represented by transparentwavelength division multiplexing (WDM) networks, where all-optical circuits (or lightpaths) carry the networktraffic from the source to the destination node in the optical domain, i.e. without any optical-to-electrical(O-E-O) conversion. To further improve network power efficiency, several approaches have been proposed inthe literature attempting to reduce the power consumption in transparent WDM networks [3][4]. Among them,power aware (PA) routing and wavelength assignment (RWA) algorithms are receiving a lot of attention. Onepossible solution for the PA-RWA problem is to limit the number of devices in the network that need to bepowered-on to support the lightpath requests [5]. These methods, however, have an adverse impact on the lengthof the provisioned lightpaths. In order to efficiently use as much powered-on network resources as possible, thepath length is, on average, longer than the one found with traditional (and less power efficient) shortest pathsolutions. This is in contradiction with the goal of classical RWA algorithms that tend to minimize the resourceusage (i.e., wavelengths and fibers) within the network, in order to minimize the blocking probability. Whenavailability of network resources becomes something that cannot be overlooked, a trade off needs to be assessedbetween power savings and blocking probability.In this talk, a non-conventional solution to the PA-RWA problem is presented. It is based on the intuitionthat, in some cases, relaxing the power minimization constraint can have beneficial effects on the overallnetwork performance, i.e., it can contribute to the reduction of resource fragmentation in the network and, in thisway, lower the blocking probability. The proposed algorithm leverages on a cost function that considers both thepower status of network elements (in this particular case the in-line optical amplifiers on fiber links only) and theinformation about wavelength usage. The algorithm has been tested using a Pan-European core network (i.e.,COST 239). Performance results confirm the presence of a trade-off between energy saving and blockingprobability. They also suggest that a “binary” approach using only the powered-on/powered-off informationmight not always be the best choice. © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20120202

A careful wavelength assignment (WA) to lambda services must be performed to reduce the total number of wavelength converters (WCs) that are required when the wavelength continuity constraint cannot be met in wavelength division multiplexing (WDM) networks. With the successful introduction of reconfigurable optical add-drop multiplexers (ROADMs), WDM networks are now growing in size, both in the number of optical nodes and the number of wavelengths supported. Fast and memory efficient WA algorithms are required to design cost effective large WDM networks. This paper presents a scalable and efficient WA heuristic algorithm aimed at reducing the total number of WCs that are required in (large) WDM networks bearing static lambda services. The WA algorithm is applied to both unprotected and (dedicated) protected lambda services. In the latter case, the wavelength continuity constraint between the working and protection path of a lambda service is taken into consideration when non-tunable optical transceivers are employed.

With the successful introduction of reconfigurable optical add-drop multiplexers (ROADMs) and related technologies, WDM networks are now growing in the number of optical nodes, wavelengths, and lambda services supported. In addition, shared path protection mechanisms — whereby lambda services are allowed to share protection wavelength channels — are possible at the optical (WDM) layer. Efficient strategies must be devised to both determine the set of services that must share a common protection wavelength channel and assign wavelengths to every service. One objective of these strategies is to minimize the total number of wavelength converters (WCs), which are required every time the wavelength continuity constraint cannot be met. This paper presents a scalable and efficient heuristic, whose goal is to minimize the number of WCs in resilient WDM networks supporting static sets of shared path protection lambda services. The heuristic comprises a set of polynomial algorithms that are executed sequentially to obtain a sub-optimal solution. In small size instances of the problem, the heuristic is compared against the optimal solution obtained from ILP formulation. For large size instances — tens of thousands of lambda services and hundreds of nodes — the heuristic yields an average number of WCs that is close to be linear in the number of services, despite the fact that the wavelength sharing factor increases.