Wafer-scale multi-GPU systems have been proposed as powerful accelerators, with Photonic Network-on-Wafer (PNoW) architectures offering clear advantages over electrical interconnects in area, bandwidth, and energy efficiency. Designing a circuit-switched photonic network that can dynamically adapt to inter-GPU traffic patterns that vary over time and in space however is an open challenge. In this paper, we propose DyPNet-MSC, a Dynamic Photonic Network-on-Wafer with Minimal Static Connectivity. DyPNetMSC provides minimal static all-to-all connectivity through dedicated waveguides while dynamically re-allocating the remaining PNoW bandwidth to cater to inter-GPU traffic demand changes during run time. For the latter, a key design choice emerges between fine-grained but costly wavelength-selective (WS) switches, versus low-overhead but coarse-grained wavelength-non-selective (WNS) switches. Our evaluation shows that DyPNet-MSC achieves the best of both worlds: DyPNet-MSC with WNS switches offers performance comparable to WS switches (within approximately 0.5%) while incurring significantly lower overhead. Furthermore, with 2 TB/s bandwidth per GPU, DyPNet-MSC improves average performance by 27% over a uniform-static $2 \mathrm{~TB} / \mathrm{s}$ photonic network, reaching a performance level surpassing a uniformstatic $4 \mathrm{~TB} / \mathrm{s}$ network by 5 percentage points. For workloads with imbalanced spatial traffic demands, DyPNet-MSC delivers up to 90% higher performance than a uniform-static $2 \mathrm{~TB} / \mathrm{s}$ network while outperforming a $4 \mathrm{~TB} / \mathrm{s}$ uniform-static network by $\mathbf{5 5}$ percentage points. Overall, this work provides new insight into designing photonic interconnection networks for next-generation wafer-scale multi-GPU systems.

ABSTRACT Vizing's generalized theorem states that any multigraph with maximum degree and maximum multiplicity has an edge coloring with at most colors. The runtime of Vizing's algorithm, which can find such a coloring, scales quadratically with . This is an important drawback for multigraphs arising from applications like photonic networks, where edge degrees and multiplicities can be very high. In this work, we propose a new edge coloring algorithm for multigraphs, which scales linearly with . To the best of our knowledge, no existing edge coloring algorithm, using so few colors, scales less than quadratically with . We describe one algorithm that finds a near‐optimal coloring and another algorithm that finds an optimal coloring with and worst‐case time complexity, respectively. We verify the working mechanisms as well as the performance of these algorithms, both for purely random test inputs and for synthetic test inputs whose structure is based on real applications.

Deterministic networks (DetNets) demand precise delay modeling to meet quality-of-service (QoS) requirements for time-sensitive applications. Queueing delay plays the most critical role among all contributors to end-to-end latency. Existing Time-Sensitive Networking (TSN) standards, such as Time-Aware Shaping (TAS) and Cyclic Queueing and Forwarding (CQF), rely on high-precision time synchronization to effectively manage queueing delays. Larger-scale DetNets suffer from less accurate time synchronization, resulting in alternative data plane approaches. The approach followed in this paper uses strict priority queueing (SPQ), network calculus (NC), and pre-configured queueing delay budgets to bound queueing delays and improve routing flexibility and simplicity. While it has been shown that queueing delay budget configurations affect routing efficiency, there are no studies on deriving optimal budgets. This paper addresses this gap by introducing a novel optimization model that jointly determines optimal flow routes and queueing delay budgets while leveraging NC to ensure delay compliance. The model is evaluated in an industrial setting, demonstrating its utility as a benchmark for routing solutions, and as a tool to identify scenarios in which SPQ can be beneficial and to derive queueing delay budget configurations for specific use cases. Moreover, the analysis highlights the differences between priorities and the importance of considering traffic demands, network topology, and capacity when fine-tuning the DetNet.

Distributed computer vision deployment frameworks aim to reduce end-to-end latency and backbone traffic by distributing computation across edge and cloud tiers. In typical architectures, nodes can process a portion of incoming image streams locally or in an edge server and offload the remainder to the cloud. However, runtime decisions about task scheduling and offloading often impose a significant computational burden on nodes, leading to unnecessary runtime overhead and underutilization of hardware resources for deployed applications. To address these challenges, we propose an offline mixed-integer optimisation framework that partitions workloads into local edge processing and deterministic offloading to the cloud tier. Each edge node handles multiple image streams by deploying parallel processing pipelines. Our framework enforces quality-of-service (QoS) constraints while maximising the proportion of computation performed at the edge. By precomputing an optimal configuration, the edge node can meet latency and resource requirements without incurring the overhead of on-the-fly optimisation. We evaluate our approach against several standard image stream processing approaches and demonstrate that our method satisfies QoS targets with lower processing delay and higher resource utilisation. We demonstrate that as the number of sensors increases, our framework can adjust the deployed configuration to enhance on-edge processing.

The necessity of processing real-time data at the network edge is growing. Low-power AI accelerators, especially edge GPUs, help meet this demand by mitigating cloud-related latency and bandwidth issues. However, GPUs remain underutilised, even in heavy workloads, due to a limited understanding of resource sharing in edge computing. This work analyses key GPU metrics: utilisation, memory, streaming multiprocessors (SMs), and tensorcores on NVIDIA Jetson devices under concurrent vision-inference workloads. Our findings show that while GPU utilisation can reach 100 % with optimisations, SMs and tensor cores often run at only 15-30 % capacity.

In the era of 5G and the upcoming 6G, current software stacks are ineffective when it comes to intelligent and fast decision-making, which necessitates the need for sustainable yet performant and scalable solutions. A significant amount of research has been done in this area, but an end-to-end solution was lacking. In this scope, we identify that we need a novel software stack which can handle the growing need for a vast amount of data generation with the help of the cloud-edge continuum, swarm programmability, along with secure deployments of applications. In this context, we propose OASEES, an architectural framework for a decentralised AI/ML computing stack that unifies diverse computing resources, peer-to-peer coordination protocols, and secure middleware. Our design outlines modular different compute infrastructures(CPUs, GPUs, TPUs and custom ASICs) orchestrated by a lightweight containerbased runtime and governed by a blockchain-enabled tamperproof data storage, decentralised coordination (decentralised autonomous organisation, voting, etc) to facilitate transparent discovery, allocation, and incentivization. We also propose a detailed performance and scalability metrics framework covering latency, throughput, resource utilisation, and cost-per-inference, intended as the foundation of subsequent evaluations.

High-Performance Computing (HPC) is indispensable in the current technological era. To preserve the development of innovative ideas and technologies, supercomputers must continue to grow in size. Consequently, the importance of the interconnection network that connects the computing resources, increases. The communication demands of today’s workloads can cause bottlenecks in the supercomputer’s network, resulting in the utilization of only 3% of their available computing power. This inefficiency presents an opportunity to enhance system efficiency through network-oriented resource management.In this paper, we outline the limitations of state-of-the-art resource management strategies and identify the challenges associated with solving the underutilization in large-scale HPC systems. We advocate that flexibility and direct control over resources are the fundamental principles for overcoming these challenges. To this end, we present our research strategy focussing on designing closed-loop resource allocation strategies. Opposed to existing strategies, our approach adaptively reacts to the dynamic behavior of the system through elastic allocation, ensuring optimal resource allocation.

Next-generation Internet will require strict end-to-end delay guarantees to support upcoming latency-sensitive applications. The IEEE 802.1 Time-Sensitive Networking (TSN) standard has become the de-facto solution for Ethernet-based L2 networks to support applications with strict latency, jitter and packet loss requirements. The IETF DetNet Working Group tries to expand on TSN to support real-time applications over larger-scale L3 networks. This paper proposes control and routing strategies that provide latency guarantees in L3 networks without requiring time synchronization among nodes. The proposed strategies include a link-state routing protocol and several exploration-based protocols that exploit queue-level information and network calculus to provide latency guarantees. Additionally, the use of queueing delay budgets enables independence among flows, while enabling fine-grained routing. This allows to make better routing decisions and to support applications with diverse latency requirements. Moreover, traffic shaping is only required at the network ingress. The strategies are evaluated extensively and compared in a simulation environment in multiple large-scale scenarios, considering acceptance rate, network utilization, path dissemination time, control overhead, and memory consumption, as well as how these metrics evolve w.r.t. different network scales. Experimental results demonstrate that representative delay-constrained traffic demands can be accommodated adequately by queue-level link-state routing protocols only in smaller-scale networks. In larger-scale network scenarios, breadth-first exploration-based protocols are required to provide stable performance w.r.t. acceptance rate and path dissemination times at the cost of only linearly increasing control overhead and memory footprint.

Time-Sensitive Networking (TSN) is a set of standards currently being defined by the IEEE 802.1 Time-Sensitive Networking Task Group [1] for Real-Time behavior in the network. Software-Defined Networking (SDN) provides a good solution for implementing TSN networks due to its characteristics such as run-time flexibility, benefits in management, cost efficiency, and performance. For achieving Real-Time behavior in TSN networks, the high-priority traffic should be scheduled precisely to fulfill its timing requirements. For this purpose, in SDN-based implementation, the control plane must have a good knowledge of the network topology and the delay in the network to be able to schedule the traffic. In this paper, we propose a topology discovery mechanism for the Central Network Controller (CNC) in TSNs based on the Link Layer Discovery Protocol (LLDP) able to discover accurate link latency characteristics as required for time-aware scheduling without relying on external time synchronization protocols such as PTP. We evaluate its feasibility and assess its performance in terms of required bandwidth and achieved accuracy.

Electromagnetic nano-communication has increasing attention in recent years. Several developments have been achieved in the fabrication, communication and management of various nano-network devices serving potential applications ranging from software-defined metamaterials, wireless robotic materials and body-centric communication. Such applications need uplink and downlink communication between the deployed nano-network and the external macro-world or the Internet through nano-interfaces. As a result, heterogeneous nano-network devices and their interoperability in different Internet of nano-things applications become new challenges for nano-network communication. In this regard, dynamic, flexible and distributed micro/nano-gateways can accommodate such sustainable issues and make the nano-network fully operational, regardless of the adopted application domain or the protocols used in communication. Network functions virtualization and software-defined networking technologies altogether can overcome these challenges. This article proposes SDN-based architecture and software module for the micro/nano-gateway. The proposed software module converts data formats and protocols between nano-network and traditional network domains allowing the nano-devices to be linked to the Internet. A prototype of the module is built, and the performance of the proposed algorithm is evaluated based on two communication scenarios; single tenant and multitenant. The result shows the effect of the total number of connected nano-devices and the number of packets sent by each device on the total average round-trip processing delay and the overall throughput of the micro/nano-gateway.

As Cooperative Intelligent Transportation Systems (C-ITS) hold many promises in reducing societal costs of traffic, the European Commission aspires to move to more C-ITS deployments in the coming years. Despite the promise of socioeconomic benefits, C-ITS deployments require substantial investments from European Member States in roadside infrastructure and in central traffic management systems. These investment costs currently outweigh the expected benefits, due to limited expected uptake of C-ITS in European passenger cars. However, since traffic volumes and the associated societal costs are not uniformly distributed along highways, investments in specific Road-Side Units (RSUs) locations might be viable, despite an overall RSU investment appraisal seeming unfeasible. Therefore, in this work, a greedy techno-economic selection algorithm for RSU deployment locations is presented. It was found that, for Flanders, a subset of potential RSU locations resulted in a positive business case from societal point of view, whereas the initial overall investment case resulted in a negative assessment conclusion.

Recent developments in nanotechnology herald nanometer-sized devices expected to bring light to a number of groundbreaking applications. Communication with and among nanodevices will be needed for unlocking the full potential of such applications. As the traditional communication approaches cannot be directly applied in nanocommunication, several alternative paradigms have emerged. Among them, electromagnetic nanocommunication in the terahertz (THz) frequency band is particularly promising, mainly due to the breakthrough of novel materials such as graphene. For this reason, numerous research efforts are nowadays targeting THz band nanocommunication and consequently nanonetworking. As it is expected that these trends will continue in the future, we see it beneficial to summarize the current status in these research domains. In this survey, we therefore aim to provide an overview of the current THz nanocommunication and nanonetworking research. Specifically, we discuss the applications envisioned to be supported by nanonetworks operating in the THz band, together with the requirements such applications pose on the underlying nanonetworks. Subsequently, we provide an overview of the current contributions on the different layers of the protocol stack, as well as the available channel models and experimentation tools. Finally, we identify a number of open research challenges and outline several future research directions.

Optical attocell networks based on visible light communication (VLC) are cost-efficient solutions which complement the spectrum shortage of radio-frequency(RF)-based indoor wireless networks. However, communication using visible light is vulnerable to shadowing effect caused by random pedestrians as visible light cannot penetrate opaque objects. A cross-layer resilience scheme RASP (routing, load assignment, subcarrier selection, power allocation) is proposed to address the shadowing effect. Network performance using different combinations of cross-layer control policies, i.e., algorithms and allocation methods, is evaluated and compared by RASP. An optimization algorithm is used to find the optimal/near-optimal combination of RASP control policies. In order to find the proper optimization algorithm for RASP, we investigate and compare the performance of different algorithms, including partial enumeration and neighbor-searching algorithms like hill-climbing and Tabu-search. An improved Tabu-search algorithm is proposed to reduce the time-complexity.

OpenFlow provides a protocol to control a network from an external server called controller. Moreover, RouteFlow presents a framework to run Internet routing protocols in OpenFlow networks by running them in virtual machines or containers. The problem is that OpenFlow networks running RouteFlow do not recover fast from a port failure (e.g., port down event). The failure recovery time is dependent on user configurable parameters and is in seconds. To overcome this problem, we implement a solution in which a port failure of a physical OpenFlow node is detected immediately in its corresponding virtual machine and an immediate action is taken by the routing protocol. Therefore, once a routing protocol running on the corresponding virtual machine detects this failure, it broadcasts the failure in the network and a new failure free path is immediately configured over the OpenFlow network. We implement the proposed solution in an OpenFlow controller and test it over single autonomous and multiple autonomous system scenarios (including OpenFlow and non-Openflow scenarios) of the Internet emulated on the virtual wall testbed of the Fed4Fire facility in Europe. The results show that an OpenFlow network can recover from a failure in a short time interval using the proposed solution.

The ever-increasing customer demand for emerging applications and services poses new technological as well as business challenges for the new 5G networks. To meet user' expectations, satellite communication can complement terrestrial deployments, in some specific use cases. Though, integrating satellite and 5G needs close collaboration between different network operators, that have different backgrounds, which poses business and technical challenges. This paper aims to assess, from a business-model perspective, the role of a radio-resource broker in the satellite-5G network integration case. The paper concludes that efficiency gains can be result from using a broker, if specific technical challenges are overcome and if it is managed by a regulatory body. The broker analysis showed that three different business models of the broker can be realized, depending on which level the satellite operator could allow the broker to manage its network resources.

Many media services undergo a varying workload, showing periodic usage patterns or unexpected traffic surges. As cloud and NFV services are increasingly softwarized, they enable a fully dynamic deployment and scaling behaviour. At the same time, there is an increasing need for fast and efficient mechanisms to allocate sufficient resources with the same elasticity, only when they are needed. This requires adequate performance models of the involved services, as well as awareness of those models in the involved orchestration machinery. In this paper we present how a scalable content delivery service can be deployed in a resource- and time-efficient manner, using adaptive machine learning models for performance profiling. We include orchestration mechanisms which are able to act upon the profiled knowledge in a dynamic manner. Using an offline profiled performance model of the service, we are able to optimize the online service orchestration, requiring fewer scaling iterations.

In this demonstration, we present dynamic allocation of accelerator resources to SSH tunnels in an NFV environment. In order to accelerate a VNF, its compute-intensive operations are offloaded to hardware cores running on an FPGA. The CPU utilization information of VNFs is continuously processed by a service management component to dynamically decide the suitable target to run VNF's crypto-operations. We also demonstrate switching between the non-accelerated and hardware-accelerated SSH-tunnels triggered by a change in the nature of the data traffic flowing through the tunnel and indicate throughput gains obtainable in dynamically switching contexts.

BACKGROUND: Graphlets are useful for bioinformatics network analysis. Based on the structure of Hočevar and Demšar's ORCA algorithm, we have created an orbit counting algorithm, named Jesse. This algorithm, like ORCA, uses equations to count the orbits, but unlike ORCA it can count graphlets of any order. To do so, it generates the required internal structures and equations automatically. Many more redundant equations are generated, however, and Jesse's running time is highly dependent on which of these equations are used. Therefore, this paper aims to investigate which equations are most efficient, and which factors have an effect on this efficiency. RESULTS: With appropriate equation selection, Jesse's running time may be reduced by a factor of up to 2 in the best case, compared to using randomly selected equations. Which equations are most efficient depends on the density of the graph, but barely on the graph type. At low graph density, equations with terms in their right-hand side with few arguments are more efficient, whereas at high density, equations with terms with many arguments in the right-hand side are most efficient. At a density between 0.6 and 0.7, both types of equations are about equally efficient. CONCLUSIONS: Our Jesse algorithm became up to a factor 2 more efficient, by automatically selecting the best equations based on graph density. It was adapted into a Cytoscape App that is freely available from the Cytoscape App Store to ease application by bioinformaticians.

The virtualization of compute and network resources enables an unseen flexibility for deploying network services. A wide spectrum of emerging technologies allows an ever-growing range of orchestration possibilities in cloud-based environments. But in this context it remains challenging to rhyme dynamic cloud configurations with deterministic performance. The service operator must somehow map the performance specification in the Service Level Agreement (SLA) to an adequate resource allocation in the virtualized infrastructure. We propose the use of a VNF profile to alleviate this process. This is illustrated by profiling the performance of four example network functions (a virtual router, switch, firewall and cache server) under varying workloads and resource configurations. We then compare several methods to derive a model from the profiled datasets. We select the most accurate method to further train a model which predicts the services' performance, in function of incoming workload and allocated resources. Our presented method can offer the service operator a recommended resource allocation for the targeted service, in function of the targeted performance and maximum workload specified in the SLA. This helps to deploy the softwarized service with an optimal amount of resources to meet the SLA requirements, thereby avoiding unnecessary scaling steps.

Motivation: Graphlets are a useful tool to determine a graph's small-scale structure. Finding them is exponentially hard with respect to the number of nodes in each graphlet. Therefore, equations can be used to reduce the size of graphlets that need to be enumerated to calculate the number of each graphlet touching each node. Hočevar and Demšar first introduced such equations, which were derived manually, and an algorithm that uses them, but only graphlets with four or five nodes can be counted this way. Results: We present a new algorithm for orbit counting, which is applicable to graphlets of any order. This algorithm uses a tree structure to simplify finding orbits, and stabilizers and symmetry-breaking constraints to ensure correctness. This method gives a significant speedup compared to a brute force counting method and can count orbits beyond the capacity of other available tools. Availability and implementation: An implementation of the algorithm can be found at https://github.com/biointec/jesse. Contact: [email protected].

In this paper, we propose an OpenFlow enabled Internet infrastructure, using virtual path slicing in an end-to-end path, so that any user connected to an OpenFlow network is dynamically allocated a corresponding right of way. This approach allows an interference-free path, from other traffic, between any two endpoints, on multiple autonomous systems, for a given application flow (e.g., WebHD Video Streaming). Additionally, we propose and implement an end-to-end quality of service framework for the Future Internet and extend the virtual path slice engine to support future Internet technologies such as OpenFlow. The proposed framework is evaluated in distinct multiple autonomous scenarios for a city with a population of 1 million inhabitants, emulating xDSL (Digital Subscriber Line), LTE (Long-Term Evolution) and Fibre networking scenarios. The obtained results confirm the suitability of the proposed architecture between multiple autonomous systems, considering both data and control traffic scalability, as well as resilience and failure recovery. Furthermore, challenges and solutions for experimentation in a large-scale testbed are described.

Network slicing is the emerging paradigm in which operators use their resources to provide multiple logical networks and associated resources, with varying configurations and at the same time. More and more vertical industries need their machines and devices connected in networks with specific requirements. In order to provide networks fitted to these usecases, and not require that they adapt to the one-size-fits-all network as is currently the case with the mobile Internet, the telecom community vowed to include network slicing functionality within its next generation of mobile networking, 5G, as an end-to-end network solution. As the concept is new and still not fully grasped, we develop and refine the concept of a network slice both from a business and a technological point of view. We investigate how network slicing in the context of a vehicular network could be implemented and how it advances the state of the art. This involves a detailed study of the involved technologies across a range of infrastructures and network segments, as well as the resulting gaps in the existing technology landscape. Based on the lessons learned in this concrete usecase, network slicing is considered in a broader 5G landscape. We capture the main challenges and potential directions in order to make network slicing a true enabler of 5G-driven vertical industries.

The growing demand for flexibility and cost reduction in the telecommunication landscape directs the focus of service development heavily to programmability and softwarization. In the domain of Network Function Virtualization (NFV), one of the goals is to replace dedicated hardware devices (such as switches, routers, firewalls) with software-based network functionalities, showing comparable performance when deployed on common servers. In this paper, we discuss how current VNF implementation and deployment strategies impact the efficient monitoring of their resources. In a multi-tenant, NFV-based ecosystem, different Service Providers deploy VNFs on a shared infrastructure, where the Infrastructure Provider exposes only VNF specific metrics and little information about the physical hosts where the VNFs are eventually orchestrated. Especially in the situation where datacenters are overcommitted, detecting the risk of e.g. CPU starvation is not straight-forward, when no information from the physical host is available. A new monitoring technique is introduced, based on the skewness of the measured probability distribution of the VNF resource consumption. Our measurements show that this metric is a good indicator for the (un)availability of the required CPU resources in the datacenter.

Summary: We present a Cytoscape app for the ISMAGS algorithm, which can enumerate all instances of a motif in a graph, making optimal use of the motif’s symmetries to make the search more efficient. The Cytoscape app provides a handy interface for this algorithm, which allows more efficient network analysis. Availability and Implementation: The Cytoscape app for ISMAGS can be freely downloaded from the Cytoscape App store http://apps.cytoscape.org/apps/ismags. Source code and documentation for ISMAGS are available at https://github.com/biointec/ismags. Source code and documentation for the Cytoscape app are available at https://gitlab.psb.ugent.be/thpar/ISMAGS_Cytoscape. Contacts: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

Resource abstraction aims at enabling flexible allocation of capacity to serve demands by aggregating physical resources taken out of distributed resource pools accessible via dedicated gateways. This paradigm sits at the heart of many networking models including resource virtualization and other cloud computing. In this paper, we show this generic problem can be modeled by combining and extending the Hub Location with the Location Routing Problem, referred to as the Hub-Location Routing Problem (HLRP). A mixed- integer program for the HLRP is proposed and evaluated using representative settings. We compare the results with those obtained when modeling the initial problem as an Location Routing Problem only; hence, obtain a quantitative assessment of the performance tradeoffs between resource abstraction, (al)location and routing.

eHealth, mHealth and eCare services are growing in numbers at a fast pace. This is mainly driven by technology and the societal challenges of an aging and more chronically burdened population while pressure on both human and financial resources increases. Though the adoption of these digital health services is challenging and experience difficulties. This work focusses on the main barriers that cause a `gap' in the value network. Via case research following barriers are identified: 1) low willingness to pay, 2) unbalanced cost/benefit ratios of the actors or unfair cost allocation and 3) negative impacted business models. Furthermore the several roles of the government within the value network of digital health services are discussed and reflections and guidelines for digital health service developers are foreseen.

A variety of dynamic bandwidth allocation (DBA) algorithms have been proposed to foster the performance of Ethernet passive optical networks (EPONs). These DBA algorithms use packet delay as an important quality of service (QoS) metric. This has led to a significant interest in developing mathematical models for analyzing the delay. These delay models often provide valuable qualitative results and worthwhile insights in understanding the mechanism of the delay and the manner in which it depends upon algorithm characteristics. Up to now, the delay models have been developed under some approximations, e.g., fixed packet sizes, negligible distances between a server and its users, a gated bandwidth assignment method, and Poisson traffic. In this paper, we develop the delay models for more realistic scenarios than the current state-of-the-art, including gated and limited bandwidth assignment methods, Poisson and Pareto traffic, and long-reach PONs in which the distance between the server and the users is significant and hence not negligible. We model different DBA paradigms, such as REPORT after data, REPORT before data, and multi-thread polling. The results from simulation experiments confirm the accuracy of the delay models.

Although geometric routing is proposed as a memory-efficient alternative to traditional lookup-based routing and forwarding algorithms, it still lacks: (i) adequate mechanisms to trade stretch against load balancing, and (ii) robustness to cope with network topology change. The main contribution of this paper involves the proposal of a family of routing schemes, called Forest Routing. These are based on the principles of geometric routing, adding flexibility in its load balancing characteristics. This is achieved by using an aggregation of greedy embeddings along with a configurable distance function. Incorporating link load information in the forwarding layer enables load balancing behavior while still attaining low path stretch. In addition, the proposed schemes are validated regarding their resilience towards network failures.

Network Service Chaining (NSC) is a service concept which promises increased flexibility and cost-efficiency for future carrier networks. The two recent developments, Network Function Virtualization (NFV) and Software-Defined Networking (SDN), are opportunities for service providers to simplify the service chaining and provisioning process and reduce the cost (in CAPEX and OPEX) while introducing new services as well. One of the challenging tasks regarding NFV-based services is to efficiently map them to the components of a physical network based on the services specifications/constraints. In this paper, we propose an efficient cost-effective algorithm to map NSCs composed of Network Functions (NF) to the network infrastructure while taking possible decompositions of NFs into account. NF decomposition refers to converting an abstract NF to more refined NFs interconnected in form of a graph with the same external interfaces as the higher-level NF. The proposed algorithm tries to minimize the cost of the mapping based on the NSCs requirements and infrastructure capabilities by making a reasonable selection of the NFs decompositions. Our experimental evaluations show that the proposed scheme increases the acceptance ratio significantly while decreasing the mapping cost in the long run, compared to schemes in which NF decompositions are selected randomly.

Geometric routing is an alternative to traditional routing algorithms in which traffic is no longer forwarded using lookup tables, but using coordinates in an embedding of the underlying network. A major downside of current geometric routing algorithms is their inability to handle network failures in a graceful manner. Moreover, they cannot deal with dynamic graph topologies. This article presents a geometric routing scheme that uses an embedding based on a spanning forest. Allowing nodes to select the optimal spanning tree leads to both shorter paths and natural traffic redirection in case of network failures. By constructing the forest in such a way that its disconnected components have low redundancy, their coverage is maximized. Results show that this system is able to operate gracefully in severe failure scenarios, without any form of path protection or restoration. By means of an embedding regeneration procedure, the routing scheme is able to continuously adapt to an altering network topology. This geometric routing algorithm effectively combines two key objectives, namely low path stretch and high robustness. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 320–334 2015

The Recursive InterNetwork Architecture (RINA) is a recently proposed network architecture based on first principles, which promises to solve a number of issues present in the current Internet such as the lack of inherent security. In this paper, we present the experimental evaluation of the first performance-oriented implementation of RINA, the IRATI stack. Our open source stack is designed for GNU/Linux Operating Systems, with key components developed in kernel space for optimal performance. After briefly introducing the architecture, we present the main features of the stack, give some details about the implementation and discuss some trade-offs that had to be taken into account. We present use case scenarios for the evaluation, which were implemented in a test environment, and present the performance, achieving a goodput close to line rate on a GbE link, even when multiple Distributed Inter Process Communication Facilities (DIFs) are stacked.

Current nurse call systems hinder the efficiency of nurses as the systems are not aware of the type of requested help and the context in which their help is required. To tackle these issues, we have developed an ontology-based nurse call system that automatically takes the patients' and caregivers' profiles and context into account when assigning calls to nurses by modelling this information in an ontology, i.e., a formal domain model. For example, current tasks of the nurses and trust relationship with patients are considered while allocating calls to caregivers. Focus is not only on creating a higher quality patient care, but also on distributing the workload more evenly over all caregivers. However, not in all hospital departments such a smart nurse call system will have a significant impact, e.g., geriatric versus emergency care. To gain insights into the total impact of a smart nurse call system, a dedicated discrete event simulation (DES) model is presented that tests its performance. Based on realistic nurse call logs and information gathered at representative hospital departments through interviews and observations, the simulation model allows optimizing decisions, modelled as rules based on the information captured in the ontology, to allocate calls to the best suited nurse. Several scenarios with a varying number of calls, staff members, etc. are tested to be able to define the effectiveness and the (dis)advantages of the ontology-based system with respect to the current one. In conclusion, recommendations are made towards improving the currently employed nurse call systems in hospitals.

Information-centric networking has been proposed to achieve efficient and reliable distribution of content. We propose a model to assign content locators to content names. Information routing decision is made based on geometric routing using the assigned locators. We consider a geometric routing scheme known as geodesic geometric routing. We demonstrate on the iLab.t virtual wall the successful operation of the proposed scheme and the gain of using content locators on capacity utilization by means of caching.

The healthcare sector is an incredibly complex system with many public and private actors and a wide diversity of services. Because of the aging society and the growing evolution of health expenditures, pressure on available resources (time, people, budget, etc.) is increasing. Innovative ICT supported eCare and eCure services are expected to increase efficiency, coordination and organization of care. Currently many initiatives already introduced ICT-supported eCare services into the current healthcare ecosystem. However, it's quite a challenge to estimate the impact and expected uptake of these new eCare services. It's no surprise that only few services commercially succeeded. This paper presents a methodology that identifies and evaluates the PEST factors (political, economical, social and technological aspects) that impact the involved care actors when introducing eCare services. The model takes into account the overall socio-economic aspects of the service, but also the subjective importance that an individual actor can ascribe to a particular eCare service. Combining the impact of these PEST factors leads to an expected adoption rate. Both new services and existing initiatives can be compared to one another and the impact of economies of scale can be investigated. In case a negative impact on some actors is observed, the model proposes cost allocation or service offer alternatives to ameliorate the business case for a particular service. Finally, a sensitivity analysis helps to indicate the most significant parameters that drive the business case.

OpenFlow decouples the control plane functionality from switches, and embeds it into one or more servers called controllers. One of the challenges of OpenFlow is to deploy a network where control and data traffic are transmitted on the same channel (in-band mode). Implementing such an in-band mode is complex, since switches have to search and establish a path to the controller (bootstrapping) through the other switches in the network. In this paper, we propose a method that facilitates this automatic bootstrapping of switches. In this method, the controller establishes its own control network through the neighbor switches that are connected to it by the OpenFlow protocol. We measure suitability of the proposed method by performing bootstrapping experiments in different types of topologies: linear, ring, star and mesh topologies. The experimental results show that the proposed method allows bootstrapping in a minimal time, which makes it suitable even for a large network.

RouteFlow provides a way to run routing control platforms (e.g. Quagga) in OpenFlow networks. One of the issues of RouteFlow is that an administrator needs to devote a lot of time (typically 7 hours for 28 switches) in manual configurations. We propose and demonstrate a framework that can automatically configure RouteFlow. For this demonstration, we use an emulated pan-European topology of 28 switches. In the demonstration, we stream a video clip from a server to a remote client, and show that the video clip reaches at the remote client within 4 minutes (including the configuration time). In addition, we show automatic configuration of RouteFlow using a GUI (Graphical User Interface).

Hybrid WDM/TDM Passive Optical Network (PON) is a promising candidate for next-generation optical access (NGOA) solutions as it is able to offer a high splitting ratio and consequently achieves a relatively low cost and power consumption on a per-user basis compared with other NGOA architectures. On the other hand, the end users require a certain level of connection availability while the operators need to reduce the failure impact (i.e. to avoid a huge number of end users being affected by any single failure). Therefore, by evaluating the connection availability and failure impact robustness we identify the most efficient parts to provide resilience in a hybrid WDM/TDM PON from an operator and an end-user perspective. Then, we select the appropriate protection schemes to construct some novel reliable architectures and analyze their reliability performance in urban and rural scenarios. In this way, this paper provides a comprehensive insight into the most relevant protection mechanisms for hybrid WDM/TDM PONs.

The evolution toward grid and cloud computing as observed for over a decennium illustrates the crucial role played by (optical) networks in supporting today's applications. In this paper, we start from an overview of the challenging applications in both academic (further referred to as scientific), enterprise (business) and nonprofessional user (consumer) domains. They pose novel challenges, calling for efficient interworking of IT resources, for both processing and storage, as well as the network that interconnects them and provides access to their users. We outline those novel applications' requirements, including sheer performance attributes (which will determine the quality as perceived by end users of the cloud applications), as well as the ability to adapt to changing demands (usually referred to as elasticity) and possible failures (i.e., resilience). In outlining the foundational concepts that provide the building blocks for grid/cloud solutions that meet the stringent application requirements we highlight, a prominent role is played by optical networking. The pieces of the solution studied in this respect span the optical transport layer as well as mechanisms located in higher layers (e.g., anycast routing, virtualization) and their interworking (e.g., through appropriate control plane extensions and middleware). Based on this study, we conclude by identifying challenges and research opportunities that can enable future-proof optical cloud systems (e.g., pushing the virtualization paradigms to optical networks).

Software Defined Networking is a networking paradigm which allows network operators to manage networking elements using software running on an external server. This is accomplished by a split in the architecture between the forwarding element and the control element. Two technologies which allow this split for packet networks are For CES and Openflow. We present energy efficiency and resilience aspects of carrier grade networks which can be met by Openflow. We implement flow restoration and run extensive experiments in an emulated carrier grade network. We show that Openflow can restore traffic quite fast, but its dependency on a centralized controller means that it will be hard to achieve 50 ms restoration in large networks serving many flows. In order to achieve 50 ms recovery, protection will be required in carrier grade networks.

We demonstrate machine learning augmented Open Shortest Path First (OSPF) routing which infers Shared Risk Groups (SRG) from link failure history. For an initial link failure matching an SRG, it predicts subsequent link state advertisements corresponding with that SRG, improving convergence and recovery times during multiple network failures.

In this paper we propose a new random channel access protocol to reduce the channel access delay in a multichannel orthogonal frequency division multiple access (OFDMA) wireless networks. In particular, we propose a two dimensional random walk through time and frequency domain slots simultaneously to reduce the random channel access delay for the IEEE 802.16e-2005 based WiMAX media access control (MAC) protocol. We prove through simulation that our proposed scheme improves upon the existing random channel access mechanism with truncated binary back-off, currently implemented in WiMAX. We demonstrated that with our proposed channel access mechanism, a mobile node with real time traffic requirements will have minimum service disruption due to the reduced delay in the initial ranging and the bandwidth request phase while changing rooms.

In this paper, we use machine learning technique at the routers to study the link state protocol data to predict the existence of shared risk link groups (SRLG) in the network. In particular, we use the correlation between different link state updates (LSUs) issued by different network nodes (routers) upon failure. The concerned network router then runs a novel Bayesian network based statistical learning process to learn about the possible existence of SRLGs. The decision of this online learning is transferred to the routing information base (RIB) so that it can accordingly modify the routing table for the entire SRLG upon failure detection of one of the candidate node of that particular SRLG and hence reduce the protection switching time.

This paper presents a programmable multi-granular optical cross connect (MG-OXC) and network architecture deployable in multi-service and multi-provider networks. The concept of programmable MG-OXC is introduced to provide a way of utilizing multiple switching/transport granularities to efficiently

Nowadays, many telecom operators are reluctant to roll out a new fiber to the home (FTTH) infrastructure, as they are put off by the high investment costs. Inspired by several local FTTH initiatives, especially in Western Europe, this paper considers an FTTH rollout by a local community. We show that clearly different economics play a part in case a community would roll out the FTTH infrastructure, and we give also an indication of some required conditions to obtain a feasible FTTH rollout. To get realistic results, the techno-economic study has been applied on a municipality network in the city of Ghent, located in Belgium. We have performed a cost/benefit analysis, and different rollout schemes are compared to each other. As the introduction of a new technology involves a lot of uncertainties, it is of great importance to determine the most influencing parameters. For that purpose, we have executed a detailed sensitivity analysis, which also provide us with a general forecast of the outcome of the considered case study.

All-optical label swapping (AOLS) forms a key technology towards the implementation of all-optical packet switching nodes (AOPS) for the future optical Internet. The capital expenditures of the deployment of AOLS increases with the size of the label spaces (i.e. the number of used labels), since a special optical device is needed for each recognized label on every node. Label space sizes are affected by the way in which demands are routed. For instance, while shortest-path routing leads to the usage of fewer labels but high link utilization, minimum interference routing leads to the opposite. This paper studies all-optical label stacking (AOLStack), which is an extension of the AOLS architecture. AOLStack aims at reducing label spaces while easing the compromise with link utilization. In this paper, an integer lineal program is proposed with the objective of analyzing the softening of the aforementioned trade-off due to AOLStack. Furthermore, a heuristic aiming at finding good solutions in polynomial-time is proposed as well. Simulation results show that AOLStack either a) reduces the label spaces with a low increase in the link utilization or, similarly, b) uses better the residual bandwidth to decrease the number of labels even more.

This paper describes extensive research in the field of the Multipoint Control Protocol (MPCP) for the Ethernet Passive Optical Network (EPON). More in particular the dynamic bandwidth allocation (DBA) algorithm IPACT (Interleaved Polling with Adaptive Cycle Time) is analytically modeled. The main focus has been on analyzing cycle times and packet delay in detail. The analysis starts from a simple traffic model with Poisson arrival rates, symmetric load and fixed packet size. Based on the obtained insights, more general cases with asymmetric traffic load, packet size distribution, self-similar traffic and differentiated services are further elaborated.

We present a detailed performance evaluation of a hybrid optical switching architecture called Overspill Routing in Optical Networks (ORION). The ORION architecture combines wavelength and (electronic) packet switching, so as to obtain the advantages of both switching paradigms. We have developed an extensive network simulator where the basic features of the ORION architecture were modeled, including suitable load-varying sources and edge/core node architectures. Various aspects of the ORION architecture were studied including the routing policies used (i.e. once ORION always ORION and lightpath reentry) and the various options available for the buffer architecture. The complete network study shows that ORION can absorb temporary traffic overloads, as intended, provided sufficient buffering is present.

Recent advances in optical networking technology have moved the state-of-the-art from manually installed fiber connections to fully automatic switched lightpaths. Multilayer Traffic Engineering (MTE) in an IP-over-Optical network allows to leverage rapid lightpath setup/teardown as a cross-layer traffic engineering technique. It enables on-the-fly reconfiguration of the IP layer logical topology and up/downgrade of the capacity of IP links. Together with classical IP layer routing techniques, MTE intelligently solves problems such as IP layer congestion and packet loss and it may optimize optical layer capacity usage and total network throughput. In this, the rate at which MTE can make adjustments to the network is limited by technology and stability concerns. We present some example MTE techniques and discuss how the timing parameters of these mechanisms impact perceived network performance.

When we examine today's internet architecture, we notice that the IP layer network is divided into multiple domains, managed by different service providers, operating different architectures, providing different services, handling different business strategies. In order to provide survivable inter-domain connections, to ensure connectivity in case of the most prevalent failures, different strategies can be followed. In this paper, we present some multidomain resilience schemes for a single optical backbone network interconnecting different IP domains. We then present a quantitative study of the network capacity required, in a specific pan-European backbone network.

Today, the Belgian research network GIGANET, managed by BELNET, consists of two star-shaped structures, centralized in Brussels, from where data transmission lines depart to national PoPs (point-of-presence), which are located all over the country. Local universities, colleges and other research institutions connect to their nearest PoP. Current capacity is way below predictions for the near future, thus the network needs to be scaled up dramatically. Also, there is a new demand for securely connecting distant institutions, due to several associations between them. We studied the optimal design of the future next-generation network GIGANET2, choosing a new topology, predicting future capacity demands and taking into account real pricing information obtained from telecom companies and optical hardware vendors. The study consisted of involved optimization efforts, and large-scale comparisons of optical hardware and available fiber infrastructure. This work resulted in the design of a physical optical ring topology, together with three network scenarios which are subject to different bandwidth, reliability and cost considerations, closely matching the institutions' requirements. This paper presents the final results of the study.

To efficiently support the highly dynamic traffic patterns of the current Internet in large-scale switches, we propose a new hybrid optical network design: Overspill Routing In Optical Networks (ORION). By taking advantage of the reduced (electronic) processing requirements of all-optical wavelength switching, the electronic bottleneck is relieved. At the same time, ORION achieves a level of statistical multiplexing comparable to the more traditional point to point WDM solutions, circumventing the bandwidth inefficiencies of all-optical wavelength switched networks, caused by dynamic traffic patterns. The result is a true hybrid optical network design, forming a bridge between these two switching concepts. In this paper the generic concept of ORION is described. An example node design, based on current advanced optical technologies, is described in detail. The ORION concept is also evaluated, comparing it with its two composing technologies, optical wavelength switching and point to point WDM, as well as a third, more trivial, hybrid one, through several case studies

New networking paradigms try to combine packet switching and circuit switching, keeping the best of both worlds and getting rid of the drawbacks. One promising technology is overspill routing in optical networks (ORION). In this paper we develop a control technique to set up LSPs in this novel network environment. It is based on the GMPLS paradigm and needs no extra control messages.

Traffic grooming in networks employing WDM is gaining attention due to the difference between the bandwidth requirements of the traffic demands coming from the client layer and the capacity of a wavelength in an optical transport network (OTN). In this paper an algorithm for efficient traffic grooming in a multi-layer IP/MPLS-over-meshed OTN scenario is presented. It allows designing the IP/MPLS logical topology best suited to deal with the offered traffic pattern, taking into account the unidirectional and maybe asymmetric character of IP traffic. This multi-layer traffic grooming algorithm is based on the idea of charging the IP/MPLS layer for the capacity it consumes in the optical layer. In order to assess its performance, a comparison with other grooming approaches is made. The results show that our method allows for serious savings in the overall network design cost. It also allows for a gradual capacity installation in the network, thus spreading the installation cost.

In large dynamic networks it is extremely difficult to maintain accurate routing information on all network nodes. Different causes can motivate this inaccuracy, such as the state aggregation produced in hierarchical networks, the delay in flooding the network state, and the triggering policy used to determine when this network state information must be updated. This paper focuses on the inaccuracy caused by the triggering policies. Triggering policies are included in the routing protocol to reduce the large number of update messages needed to guarantee accurate network state information on all the network nodes. The BYPASS based optical routing (BBOR) has already been proposed by the authors to reduce the effects of having inaccurate routing information in networks operating under the wavelength-continuity constraint This paper extends the BBOR mechanism to be applied to wavelength convertible networks and evaluates its performance.

The explosive growth of data traffic-for example, due to the popularity of the Internet-poses important emerging network requirements on today's telecommunication networks. This paper describes how core networks will evolve to optical transport networks (OTNs), which are optimized for the transport of data traffic, resulting in an IP-directly-over-OTN paradigm. Special attention is paid to the survivability of such data-centric optical networks. This becomes increasingly crucial since more and more traffic is multiplexed onto a single fiber (e.g., 160/spl times/10 Gb/s), implying that a single cable cut can affect incredible large traffic volumes. In particular, this paper is tackling multilayer survivability problems, since a data-centric optical network consists of at least an IP and optical layer. In practice, this means that the questions "in which layer or layers should survivability be provided?" and "if multiple layers are chosen for this purpose, then how should this functionality in these layers be coordinated?" have to be answered. In addition to a theoretical study, some case studies are presented in order to illustrate the relevance of the described issues and to help in strategic planning decisions. Two case studies are studying the problem from a capacity viewpoint. Another case study presents simulations from a timing/throughput performance viewpoint.