This Special Issue contains a set of remarkable papers covering various recent research advances towards resilient Communication Networks for an hyper-connected World. Papers are organized into five categories: (i) Resilient Architectures for Next-Generation Networks, (ii) Edge, IoT, and Cyber-Physical Systems, (iii) Vehicular, Mobile, and Aerial Networks, (iv) Optical, Hybrid, and Satellite-based Resilient Communications, and (v) Security, Trust, and Resilience in Services and Applications. The editorial begins with an overview of the field and proceeds with a summary of the twenty-two papers included in this Special Issue.

Most network planning problems in the literature consider metrics, such as cost, availability, and other technology-aware attributes. However, network operators now face new challenges in designing their networks to minimize their dependencies on manufacturers. A low dependency is associated with higher network robustness in case one or more manufacturers fail due to erroneous component design, geopolitical banning of manufacturers, or other reasons discussed in this work. Our work discusses network sovereignty, i.e., the ability to operate a network while minimizing the dependencies on a particular manufacturer to minimize the impact of simultaneous manufacturer failure(s). Network sovereignty is considered by solving the manufacturer assignment problem in the network such that robustness is maximized. The following three main contributions of this work are, first, the discussion of network sovereignty as a special attribute of dependability, second, the introduction of a novel metric—the path set diversity (PSD) score to measure a network's sovereignty based on the manufacturers used in the network, and, third, the introduction of Naga, an integer linear program formulation to maximize network sovereignty using the PSD score. We compare the Naga’s performance with centrality metrics-based heuristics and an availability-based optimization. Our work aims to be the foundation to guide network operators in increasing their network sovereignty.

The rising number of connected Internet of Things (IoT) devices in 5G networks and the standardization of the 3GPP reduced capability (RedCap) devices, turn the IoT energy efficiency into a topic of paramount importance for 5G. The design goals and use cases of RedCap devices highlight the need for long device battery life due to the infeasibility of replacing batteries. With the focus emerging on sustainable networks, battery lifetime prediction becomes essential. Therefore, in this paper, we propose and evaluate a Markov Chain based energy consumption model suitable for IoT devices in 5G networks, especially RedCap devices. We design a realistic model consistent with the procedures described in 3GPP standardization, mainly focused on the uplink transmission procedures. The proposed model is validated through extensive analysis with varying interarrival times (IAT) of the uplink traffic. For short IAT, the analytical results show a decrease of 33% in energy consumption and 89% in transmission latency. This demonstrates that our model can be applied to evaluate battery life for a broad range of IoT devices.

This paper aims at finding node-disjoint paths in multi-domain networks while avoiding to disclose each domain topology and minimizing routing cost. In order to maintain the privacy of the domains, the proposed solutions exploit a full mesh Topology Aggregation scheme that limits the exchanged information. Each domain provides information only on the existence and total cost of the two shortest node-disjoint paths for every pair of aggregated links. This information is then utilized on the inter-domain aggregated topology for the computation of two node-disjoint paths with minimum cost for every demand in the network. Four approaches are proposed and evaluated in terms of average cost per demand and blocking probability. Their performance is also compared to the respective approaches for link-disjoint routing. Two of the proposed node-disjoint routing schemes keep low blocking probability (with a median of 0–3 %), while incurring 5 % higher cost when compared to link-disjoint routing.

This Special Section features research contributions in the area of robust and reliable networks of the future. Modern network infrastructures must support a growing demand for intensive data processing and high-speed communication, that has led, in the last decade, to a constant evolution towards convergence of networking and computing infrastructures. This convergence was made possible by the introduction of network function virtualization and by the emergence of the Software-Defined Networking (SDN) paradigm, and has enabled new forms of cloud and edge computing to cope with the strict requirements of new services and applications, as those in the realm of the Internet of Things (IoT).

Fully disaggregated device deployments in optical networks propose to drive down network upgrade costs. These devices are managed by open-source control plane solutions for multi-vendor interoperability, which need to be tested in a simulation environment. We demonstrate a cloud-based solution which deploys 69 OpenROADM-based containerized optical networking elements, thereby simulating a nation-wide fully disaggregated optical transport network. Further, the planning, orchestration, and restoration of optical services can be decoupled from the simulated network, by using Transport Layer Security (TLS) enabled North-Bound REST APIs exposed by OpenDayLight TransportPCE, which is an open-source optical domain controller.

Software-Defined Networking (SDN) has redefined the architectural blueprint for designing networks suitable for future applications. Today, the idea of a centralized control plane managing its underlying resources is common for architectures in mobile and industrial networks. Guaranteeing resources availability for optimal operation of the control plane is of vital importance in SDN, since compromising the controller may result in an unforeseen behaviour in the data plane. This work focuses on the SDN reactive configuration mechanism, that although originally designed for the efficient handling of changing conditions in the data plane, it can be easily misused to overload the control plane. Aiming at addressing this problem, the PDP (Programmable Data Plane)-based Controller Protection Protocol (PCPP) is presented. This protocol introduces a mechanism that efficiently filters spoofed requests at the network edge. In PCPP, end-stations require to solve a challenge before sending any connection request to the controller. The challenge answer is checked at the edge switches, which only forward valid requests to the controller. PCPP is implemented using P4, a language for programming PDP-capable devices, and its evaluation is carried out using BMv2 software switches. The results demonstrate the effectiveness of PCPP at protecting bandwidth and processing resources in the control plane against spoofed requests. A comparison against an state-of-the-art alternative not only highlights the higher efficiency of PCPP, but also its application flexibility.

In the next generation of networks, the high data rate and large bandwidth offered by Light-Fidelity (LiFi) are expected to be fully exploited to satisfy the diverse Quality of Service (QoS) requirements of users. LiFi networks are expected to provide full data coverage while also satisfying illumination requirements in indoor environments. Thus, the optimized placement of LiFi Access Points (APs) is of utmost importance. Extending the commonly applied 2D placement, we include the height of the AP, which is an important factor to consider due to the short range of LiFi and limited Field of View (FoV) of the receivers. To this end, we propose a 3D LiFi Access Point placement framework that formulates the placement as a multi-objective optimization problem minimizing the number of APs and maximizing the sum rate while providing a guaranteed minimum rate and illumination level. Since the exact positions of users are unknown during network planning and change dynamically after deployment, the probability distribution of user occurrence is considered in the optimization. This results in the network performance being maximized in areas where users are likely to be present. This optimization problem is solved with the proposed multi-objective genetic algorithm. The framework is evaluated with simulations and the results show that the height of the AP greatly influences the network performance. We conclude that a free choice of the height of each AP results in an average rate that is significantly better than the rate achievable when all APs are placed at the same height.

This paper provides a techno-economical study comparing total cost of ownership (TCO) for the deployment of very dense wireless networks for new Internet of things (IoT) applications. Mobile optical wireless communication (OWC) also known as Light Fidelity (LiFi) offers unique advantages for the industrial IoT such as robustness through exclusive channel access in the unlicensed optical spectrum, lower latency, and enhanced security compared to common radio technologies like Wi-Fi or 5G. The deployment of LiFi and Wi-Fi is compared in an industrial scenario including the required fixed backbone and assuming full coverage at various wireless capacities. Six different network topologies are considered in different industrial scenarios. The comparison is performed in terms of Bill of Material, and in terms of costs. Regarding backhauling the paper shows that a fully wired topology requires higher installation costs but incurs in lower operational costs, resulting in lower total costs of ownership (TCO). Furthermore, power consumption has been identified as the cost driver for all topologies (more than 200% of the initial investments), triggering the need for power-saving techniques. Last but not least, the separation of LiFi Optical Front Ends (OFEs) and Wi-Fi access points (APs) has been identified as a critical design parameter, as shorter separation requires higher costs but reduces the cost per delivered bitrate. We discuss promising ways for the deployment of LiFi instead or in addition to Wi-Fi for very dense wireless networks demanding higher capacities than Wi-Fi can deliver in factory halls.

This Special Section (SI) features the latest research contributions regarding recent advances in the design and management of reliable communication networks. Communication networks are constantly increasing their complexity and scale to satisfy the requirements of network services. The current trend of convergence of networking and computing infrastructures (as in today’s cloud systems and softwarized networks) calls for novel advanced strategies and solutions to support reliable services, as the development of new data-driven solutions for reliable network automation and self-diagnostic tools to ensure resilient network management.

Airline companies are currently investigating means to improve in-flight services for passengers. Given emerging Air-to-Ground (A2G) communication technologies and the high desire of passengers for in-flight services, the servers providing in-flight services can be moved from the airplane to Data Centers (DCs) on the ground. In this scenario, network nodes (airplanes) demanding network services move over a ground core network. Therefore, the selection of DCs to connect to, as well as the underlying routing decisions are challenging. In particular, to keep a low-delay in-flight connection during the flight, airplanes connections can be reconfigured from a DC to another one, which comes at a delay cost. This paper presents a formal model for the in-flight service provisioning problem, also as an Integer Linear Program (ILP). We show that the problem is NP-hard and hence propose an efficient online heuristic, HOMA, which addresses the above challenges in polynomial time. HOMA models the problem as a dynamic matching with special properties, and then efficiently solves it by a transformation into the shortest-path routing problem. Our simulation results indicate that HOMA can achieve near-optimal performance and outperform the baseline and state-of-the-art algorithms by up to 15% while reducing the runtime from hours to seconds.

To provide the predictability required by emerging applications, operators typically rely on policing and/or shaping at the edge to ensure that tenants do not use excess bandwidth that was not accounted for. One of the promises of 6G is to deploy applications with strict predictability requirements across subnets and even over the Internet, where policing cannot be implemented in the end hosts. This paper presents an empirical study of the ability of modern programmable network devices to implement predictable traffic policing in the network. We find out that none of the five investigated hardware switches can provide accurate traffic policing, a key requirement for providing predictable service to applications. We observe that the switches let applications send more than what they should be allowed to, reaching up to 60% and 100% relative error for the rate and burst parameters. We further uncover the fact that switches cannot police arbitrarily low bursts, e.g., not less than 13 kilobit for one of our switches. We investigate how such limitations impact the performance of state-of-the-art solutions for predictable latency such as Chameleon. We observe that, for ensuring its predictable guarantees, Chameleon rejects around 50% of the tenants it could accommodate if switches were perfect, hence decreasing by the same ratio the revenue for the operator. Based on these observations, we discuss solutions toward more accurate and predictable policing in wide-area networks.

This special section features the latest research contributions regarding the design and management of reliable networks. Reliability of communication infrastructure is a top priority for network operators. To ensure reliable network operation, new design and management techniques for reliable communications must be constantly devised to respond to the rapid network and service evolution. As a recent and relevant example, deployments of 5G communication networks will soon enter their second phase, during which the network infrastructure will require upgrades to support new Ultra-Reliable Low-Latency Communication (URLLC) services with availabilities of up to 6 nines to be guaranteed jointly with extremely low latencies. Even in the still preliminary vision of 6G communication networks, reliability is posed as one of the most critical requirements, as 6G networks will represent the communication platform of our future hyper-connected society, supporting essential services as smart mobility, e-health, and immersive environments with application in remote education and working, just to name a few. Similarly, disaster resiliency in communication networks is now attracting the attention of media, government and industry as never before (consider, e.g., the worldwide network traffic deluge to support remote working during the current Coronavirus pandemic). Luckily, several new technical directions can be leveraged to provide new solutions for network reliability as: increased network reconfigurability enabled by Software Defined Networking (SDN); integration/convergence of multiple technologies (optical, wireless satellite, datacenter networks); enhanced forms of data/service replication, supported by, e.g., edge computing; network slicing, used to carve highly-reliable logical partitions of network, computing and storage resources. These, and many others, technological transformations can be leveraged to enable next-generation high-reliability networks.

Service function chains (SFCs) are an ordered set of virtual network functions (VNFs) which can realize a specific network service. Enabled by virtualization technologies, these VNFs are hosted on physical machines (PMs), and interconnected by network switches. In today networks, these resources are usually under-utilized and/or over-provisioned, resulting in power-inefficient deployments. To improve power-efficiency, SFCs should be deployed utilizing the minimum number of PMs and network equipment, which are not concomitant. Considering the existing PM and switch power consumption models and their resource constraints, we formulate the power-aware and delay-constrained joint VNF placement and routing (PD-VPR) problem as an Integer Linear Program (ILP). Due to the NP-completeness of the problem, we proposeHolu, a fast heuristic framework that efficiently solves the PD-VPR problem in an online manner. Specifically,Holudecomposes the PD-VPR into two sub-problems and solve them sequentially:i)aVNF placementproblem that consists of mapping the VNFs to PMs using a centrality-based ranking method, andii)aroutingproblem that efficiently splits the delay budget between consecutive VNFs of the SFC, and finds a Delay-Constrained Least-Cost (DCLC) shortest-path through the selected PMs (hosting VNFs) using the Lagrange Relaxation based Aggregated Cost (LARAC) algorithm. Our simulation results indicate thatHoluoutperforms the state-of-the-art algorithms in terms of total power consumption and acceptance rate by 24.7% and 31%, respectively.

The recent trend of network softwarization suggests a radical shift in the implementation of traditional network intelligence. In Software Defined Networking (SDN), for instance, the control plane functions of forwarding devices are outsourced to the controller. Softwarized network components are expected to provide uninterrupted service during long periods of time, which makes them prone to the effects ofsoftware aging, a phenomena that has been observed in operational software systems where the failure rate increases or the performance of the software degrades with the elapsed time since the last restart. The effects of software aging in operational networks are typically mitigated bysoftware rejuvenation, i.e., planned restarts cleaning the internal system state in order to prevent or postpone aging-related failures. This article presentsARES, a three-step methodological framework for the management of the effects of software aging in softwarized networks, applied to the case study of open source SDN orchestration platforms. Using ARES, we demonstrate that software aging is a systematic problem that cannot be neglected in network orchestration systems. It stems not only from aging-related bugs and natural aging due to fragmentation, but also from design choices, e.g., when implementing distributed systems. Measurements for Open Network Operating System (ONOS) and OpenDaylight (ODL) demonstrate how “simple” and common networking tasks let network performance degrade rapidly and even lead to crashes: for instance, adding and removing 300 intents per second in ONOS significantly increases the response time by 50% per day and depletes the memory at the rate of 18GB per day. Moreover, we demonstrate a first rejuvenation approach that can mitigate the effects of aging in ONOS.

This paper presents Chameleon, a cloud network providing both predictable latency and high utilization, typically two conflicting goals, especially in multi-tenant datacenters. Chameleon exploits routing flexibilities available in modern communication networks to dynamically adapt toward the demand, and uses network calculus principles along individual paths. More specifically, Chameleon employs source routing on the "queue-level topology", a network abstraction that accounts for the current states of the network queues and, hence, the different delays of different paths. Chameleon is based on a simple greedy algorithm and can be deployed at the edge; it does not require any modifications of network devices. We implement and evaluate Chameleon in simulations and a real testbed. Compared to state-of-the-art, we find that Chameleon can admit and embed significantly, i.e., up to 15 times more flows, improving network utilization while meeting strict latency guarantees.

Today, on-board passengers desire to have in-flight services such as Voice-over-IP (VoIP) and video streaming. These services are usually hosted by geographically distributed Data Centers (DCs) that are built/rented by the airline companies. Flights can be connected to these DCs using two types of Air-to-Ground (A2G) communication alternatives: i) satellite (SC), and ii) Direct-Air-to-Ground connections (DA2G). These two options are different in terms of propagation delay, capacity, and availability. Focusing on reducing the delay of the inflight services, each airplane should be assigned to a nearby DC. However, due to the mobility of flights, a permanent DC assignment might not lead to an acceptable service delay for the flight duration. Therefore, the flight needs to be reassigned to another DC (reconfiguration) along its route, which comes with a cost. The real challenge in this work is to find the best assignments of each airplane to DC(s) and determine the required reconfigurations such that the sum of routing and reconfiguration delay is minimized. We model this problem as a Multi-Period Generalized Assignment Problem (MPGAP) and formulate it as an Integer Linear Programming (ILP) optimization model. To overcome the scalability issues of the ILP, we propose Figo, a flight control framework that solves the MPGAP problem using deep Q-learning. Considering a realistic European-based Space-Air-Ground-Integrated Network (SAGIN) and a real set of flights, we compare the performance of Figo against the optimal. The results indicate that Figo can achieve 7% optimality gap in the worst case, while reducing the runtime from hours to seconds.

In the context of the 5G ecosystem, the integration between the terrestrial and satellite networks is envisioned as a potential approach to further enhance the network capabilities. In light of this integration, the satellite community is revisiting its role in the next generation 5G networks. Emerging technologies such as Software-Defined Networking (SDN) which rely on programmable and reconfigurable concepts, are foreseen to play a major role in this regard. Therefore, an interesting research topic is the introduction of management architecture solutions for future satellite networks driven by means of SDN. This anticipates the separation of the data layer from the control layer of the traditional satellite networks, where the control logic is placed on programmable SDN controllers within traditional satellite devices. While a centralized control layer promises delay reductions, it introduces additional overheads due to reconfiguration and migration costs. In this paper, we propose a method to quantify the overhead imposed on the network by the aforementioned parameters while investigating the use-case scenario of an SDN-enabled satellite space segment. We make use of an optimal controller placement and satellite-to-controller assignment which minimizes the average flow setup time with respect to varying traffic demands. Furthermore, we provide insights on the network performance with respect to the migration and reconfiguration cost for our proposed SDN-enabled architecture. Finally, we compare our proposed space segment SDN-enabled architecture with alternative solutions in the state-of-the-art given the aforementioned performance metrics.

In Software Defined Networking (SDN), network programmability is enabled through a logically centralized control plane. Production networks deploy multiple controllers for scalability and reliability reasons, which in turn rely on distributed consensus protocols to operate in a logically centralized manner. However, bugs in distributed control plane can have disastrous effects on the data plane, e.g., losing traffic by installing paths containing blackholes. In this paper we study the prevalence of issues in state-of-the-art distributed frameworks in SDN, by analyzing 500+ issues reported in two of the largest open source SDN controller platforms: Open Network Operating System (ONOS) and OpenDaylight (ODL), during the period between 2014-2019. We identify system vulnerabilities, localize dependability bottlenecks, and provide stochastic models for a holistic assessment of system dependability.

In order to scale web or other services, the load on single instances of the respective service has to be balanced. Many services are stateful such that packets belonging to the same connection must be delivered to the same instance. This requires stateful load balancers which are mostly implemented in software. On the one hand, modern packet processing frameworks supporting software load balancers, such as the Data Plane Development Kit (DPDK), deliver high performance compared to older approaches. On the other hand, common Network Interface Cards (NICs) provide additional matching capabilities that can be utilized for increasing the performance even further and in turn reduce the necessary server resources. In fact, offloading the packet matching to hardware can free up CPU cycles of the servers. Therefore, in this work, we propose the Hybrid NIC-offloading Load Balancer (HNLB), a high performance hybrid hardware-software load balancer, utilizing the NIC-offloading hardware matching capabilities. The results of our performance evaluations show that the throughput using NIC offloading can be increased by up to 50%, compared to a high performance software-only implementation. Furthermore, we investigated the limitations of our proposed approach, e.g., the limited number of possible concurrent connections.

People desire to be connected, no matter where they are. Recently, providing Internet access to on-board passengers has received a lot of attention from both industry and academia. However, in order to guarantee an acceptable Quality of Service (QoS) for the passenger services with low incurred cost, the path to route the services, as well as the datacenter (DC) to deploy the services should be carefully determined. This problem is challenging, due to different types of Air-to-Ground (A2G) connections, i.e., satellites and Direct Air-To-Ground (DA2G) links. These A2G connection types differ in terms of cost, bandwidth, and latency. Furthermore, due to the flights' movements, it is important to consider adapting the service location accordingly. In this work, we formulate two Mixed Integer Linear Programs (MILPs) for the problem of Joint Service Placement and Routing (JSPR): i) Static (S-JSPR), and ii) Mobility-Aware (MA-JSPR) in Space-Air-Ground Integrated Networks (SAGIN), with the objective of minimizing the total cost. We compare S-JSPR and MA-JSPR using comprehensive evaluations in a realistic European-based SAGIN. The obtained results show that the MA-JSPR model, by considering the future flight positions and using a service migration control, reduces the long-term total cost notably. Also, we show S-JSPR benefits from a low time-complexity and it achieves lower end-to-end delays comparing to MA-JSPR model.

Software Defined Networking (SDN) has been identified as a potential approach to achieve a more flexible control and management of the traditional satellite systems and enhance the opportunities for future services including the possibility of a hybrid satellite/terrestrial network. Given the renewed interest towards Low-Earth-Orbit (LEO) constellations, an interesting research topic is the design of a suitable network management model taking into account user specific metrics. In this paper, we address this issue while investigating the use-case scenario of an SDN-enabled satellite space segment. A Dynamic Controller Placement Problem (DCPP) is considered for a LEO constellation where the traffic demands change dynamically based on users' geographical position and time zone. To this end, we develop a mathematical model and formulate it as an Integer Linear Programming (ILP) guaranteeing an optimal controller placement and satellite-to-controller assignment minimizing the average flow setup time with respect to the traffic dynamics. We show results for the DCPP regarding the average flow setup time. Furthermore, a comparison with respect to the static approach is investigated and the proposed SDN-enabled LEO constellation architecture is compared with alternative architectures proposed in the state of the art.

The Network Function Virtualization (NFV) is very promising for efficient provisioning of network services and is attracting a lot of attention. NFV can be implemented in commercial off-the-shelf servers or Physical Machines (PMs), and many network services can be offered as a sequence of Virtual Network Functions (VNFs), known as VNF chains. Furthermore, many existing network devices (e.g., switches) and collocated PMs are underutilized or over-provisioned, resulting in low power-efficiency. In order to achieve more energy efficient systems, this work aims at designing the placement of VNFs such that the total power consumption in network nodes and PMs is minimized, while meeting the delay and capacity requirements of the foreseen demands. Based on existing switch and PM power models, we formulate an Integer Linear Programming (ILP) model to find the optimal solution. We also propose a heuristic based on the concept of Blocking Islands (BI), and a baseline heuristic based on the Betweenness Centrality (BC) property of the graph. Both heuristics and the ILP solutions have been compared in terms of total power consumption, delay, demands acceptance rate, and computation time. Our simulation results suggest that BI-based heuristic is superior compared with the BC-based heuristic, and very close to the optimal solution obtained from the ILP in terms of total power consumption and demands acceptance rate. Compared to the ILP, the proposed BI-based heuristic is significantly faster and results in 22% lower end-to-end delay, with a penalty of consuming 6% more power in average.

The routing algorithms used by current operators aim at coping with the demanded QoS requirements while optimizing the use of their network resources. These algorithms rely on the optimal substructure property (OSP), which states that an optimal path contains other optimal paths within it. However, we show that QoS metrics such as queuing delay and buffer consumption do not satisfy this property, which implies that the used algorithms lose their optimality and/or completeness. This negatively impacts the operator economy by causing a waste of network resources and/or violating Service Level Agreements (SLAs). In this paper, we propose a new so-called Mn taxonomy defining new metric classes. An Mn metric corresponds to a metric which requires the knowledge of the n previously traversed edges to compute its value at a given edge. Based on this taxonomy, we present three solutions for solving routing problems with the newly defined classes of metrics. We show that state-of- the-art algorithms based on the OSP indeed lose their original optimality and/or completeness properties while our proposed solutions do not, at the price of an increased computation time.

In software defined networking (SDN), critical control plane functions are offloaded to a software entity known as the SDN controller. Today's SDN controllers are complex software systems, owing to heterogeneity of networks and forwarding devices they support, and are inherently prone to bugs. Our previous work showed that software reliability growth models (SRGM) can model the stochastic nature of bug manifestation process open source SDN controllers. In this paper, we focus on different applications of our SRGM framework crucial for an efficient management of SDN-based networks. We provide guidelines for network operators to decide when the controller software is mature enough to be deployed in operational environment, based on the reliability requirements of network applications, and quantify the marginal benefits of the prolonged testing phase on the software quality. We show how the accuracy of software reliability prediction in the early phase of the software lifecycle can be improved by extrapolating the behavior of previous controller software releases. We also propose software maturity metrics that can be used by operators to discriminate between the competing SDN controller designs, i.e., ONOS and OpenDaylight, when software reliability is a major concern.

Software Defined Networking (SDN) exposes critical networking decisions, such as traffic routing or enforcement of the critical security policies, to a software entity known as the SDN controller. Controller software, as written by humans, is intrinsically prone to bugs, which may impair the network performance as a whole, if activated. Software reliability growth models (SRGM) are often used to estimate and predict the reliability of the software in the operational phase based on the fault report data during the testing phase. These models can be used to predict the number of residual bugs in the software, as well as failure intensity, software reliability and optimal software release time. In this paper we analyze ten releases of ONOS open source controller, whose uncensored fault reports are available online.

With Network Function Virtualization (NFV), network functions are deployed as modular software components on the commodity hardware, and can be further chained to provide services, offering much greater flexibility and lower cost of the service deployment for the network operators. At the same time, replacing the network functions implemented in purpose built hardware with software modules poses a great challenge for the operator to maintain the same level of performance. The grade of service promised to the end users is formalized in the Service Level Agreement (SLA) that typically contains the QoS parameters, such as minimum guaranteed data rate, maximum end to end latency, port availability and packet loss. State of the art solutions can guarantee only data rate and latency requirements, while service availability, which is an important service differentiator is mostly neglected. This paper focuses on the placement of virtualized network functions, aiming to support service differentiation between the users, while minimizing the associated service deployment cost for the operator. Two QoS-aware placement strategies are presented, an optimal solution based on the Integer Linear Programming (ILP) problem formulation and an efficient heuristic to obtain near optimal solution. Considering a national core network case study, we show the cost overhead of availability-awareness, as well as the risk of SLA violation when availability constraint is neglected. We also compare the proposed function placement heuristic to the optimal solution in terms of cost efficiency and execution time, and demonstrate that it can provide a good estimation of the deployment cost in much shorter time.

The reliance on the loss-of-signal (LOS) of upstream transmissions to indicate fiber/component failure is potentially unsuitable in networks that implement sleep/doze mode operation. In such networks, the transition into sleep/doze mode would result in no signal transmission, and when used in conjunction with conventional LOS to indicate network failure, would result in erroneous triggering of false alarm and subsequently protection switching. Recently, converged access networks using a hybrid passive optical architecture, have been favored as a low-cost and high-bandwidth solution to deliver high-bandwidth applications to both fixed access and mobile users. These networks are referred to as Hybrid PON Converged Access Networks. Protection against fiber/equipment failures in these networks is critical considering the customer base, network span, and traffic supported. This paper proposes four survivable architectures for such converged access networks. These architectures combine rapid fault detection and protection switching against high impact failures but without the need to rely on upstream transmissions for LOS detection. A comparison of the four architectures across three different area densities under three deployment scenarios, is presented. Guidance for selecting the best protection architecture to be deployed, considering area densities and deployment scenarios, is provided.

The evolution of telecommunications technology has always challenged the industry to cope with the rapid pace of innovation and demand. The actual panorama offers a view of network operators constantly pushed to minimize their expenses while keeping profitability. Due to that, a keen interest on applying business intelligence methods has appeared - an approach that encompasses the particularities of technology, thus named techno-economic analysis. Based on this framework, this work proposes a novel approach to modeling and studying a particular process, the service migration between platforms. The need for migration of telecommunication platforms stems from the constant technological progress and has become a focus of savings and new business opportunities. The proposed service migration model uses the hill climbing solution to find the best scenario for a given number of involved employees. The paper presents a collection of case studies, which cover the most important aspects of the migration process and suggest how network operators can increase their benefits. Additionally, the network dismantling - the very end of a network lifecycle - is also analyzed and simulated. Our approach aims at a deeper look into the operation of a telecommunications company, identifies the main cost drivers and extracts recommendations to an improved network management.

Increased competition in the telecommunications industry pushes network operators to rationalize their total costs. Models and simulations appear as major tools aiming at better understanding the expenditures and to allow a more realistic network planning. However, their focus was, in the past, mostly limited to infrastructure investments. Because emerging services pose special requirements towards the networks, operators have not only to extend the capacity of their transport networks, but also need to optimize the architecture for differentiated services with advanced packet switching technologies, referred to as Next Generation Networks (NGN). During network evolution with disruptive technology changes, a general problem faced by network operators is the service migration of active services from an existing platform into a newly setup platform. This work investigates strategies for service migration at minimized overall operational costs. A novel service migration cost model based on queueing theory and hill climbing optimization is provided in order to tackle the employee allocation optimization problem. Based on this framework, a thorough techno-economic analysis of costs and benefits is presented.

Fault and attack management has become a very important issue for network operators that are interested to offer a secure and resilient network capable to prevent and localize, as accurately as possible, any failure (fault or attack) that may occur. Hence, an efficient failure location method is needed. To locate failures in opaque optical networks, existing methods which allow monitoring of the optical signal at every regeneration site can be used. However, to the best of our knowledge, no method exists today that performs failure location for transparent optical networks. Such networks are more vulnerable to failures than opaque networks since failures propagate without being isolated due to optoelectronic conversions. In this paper, we present a failure location algorithm that aims to locate single and multiple failures in transparent optical networks. The failure location algorithm developed in this paper can cope with ideal scenarios (i.e., no false and/or lost alarms), as well as with nonideal scenarios having false and/or lost alarms.

The growing widespread use of advanced multimedia and interactive real-time applications is setting forth new challenges such as end-to-end quality-of-service (QoS) and broadband Internet access. The high bandwidth needs are pushing fiber closer and closer to the home, and as such WDM (wavelength division multiplexing) seems ideally suited to be used in the broadband access feeder network which interconnects the Internet core networks and the last mile networks. In the HARMONICS project (Hybrid Access Reconfigurable Multi-wavelength Optical Networks for IP-based Communication Services), a novel DWDM (dense wavelength division multiplexing) based optical access feeder network is investigated. This feeder network transports IP, guarantees QoS and can feed various last mile networks, stimulating the convergence of access networks. VDSL and Hiperlan/2 are studied within the project as last mile access networks. To support end-to-end QoS, a distributed CORBA-based generic network management framework is being developed as part of the project. This paper elaborates on the framework which is aligned with TINA, although adapted to be more consistent and applicable. End-to-end QoS is based on Differentiated Services (DiffServ) at layer 3, various QoS supporting technologies at layer 2 and QoS mappings between both layers.

Fault identification and location in optical networks is hampered by a multitude of factors: the redundancy and the lack of coordination (internetworking) of the managements at the different layers (WDM, SDH/SONET, ATM, IP); the large number of alarms a single failure can trigger; the difficulty in detecting some failures; and the resulting need to cope with missing or false alarms. Moreover, the problem of multiple fault location is NP-complete, so that the processing time may become an issue for large meshed optical networks. We propose an algorithm for locating multiple failures at the physical layer of a WDM network. They can be either hard failures, that is, unexpected events that suddenly interrupt the established channels; or soft failures, that is, events that progressively degrade the quality of transmission; or both, hard failures are detected at the WDM layer. Soft failures can sometimes be detected at the optical layer if proper testing equipment is deployed, but often require performance monitoring at a higher layer (SDH, ATM, or IP). Both types of failures, and both types of error monitoring, are incorporated in our algorithm, which is based on a classification and abstraction of the components of the optical layer and of the upper layer. Our algorithm does not rely on timestamps nor on failure probabilities, which are difficult to estimate and to use in practice. Moreover, our algorithm also handles missing and false alarms. The nonpolynomial computational complexity of the problem is pushed ahead into a precomputational phase, which is done off-line, when the optical channels are set up or cleared down. This results in fast on-line location of the failing components upon reception of the ringing alarms.