Wilson Ramírez

A survey and taxonomy of ID/Locator Split Architectures

The IP-based addressing scheme currently supporting the whole routing architecture embeds some well-known limitations that may significantly hinder the deployment of new applications and services on the Internet. Indeed, it is widely accepted that the unstoppable growth of Internet users is producing two well-known problems: (1) depletion of addresses, motivated by a design limitation of the currently deployed addressing scheme, and (2) the semantic overload of addresses. The main negative consequences of these problems may be summarized as: (i) exacerbating the geometrical growth of the routing tables, and (ii) affecting other network features, such as traffic engineering and mobility, in terms of resilience and disruption tolerant communications. The relevant consequences that addressing brings to the overall network operation is pushing the networking community to study and propose new addressing architectures that may limit or even remove the negative effects (affecting network performance) stemmed from the currently deployed addressing architecture. To this end, researchers working on this area must have a perfect understanding of the weaknesses and limitations coming up from the nowadays architecture as well as a comprehensive knowledge of the alternatives proposed so far along with the most appealing research trends. Aligned to this scenario, this paper comes up with the aim of assisting the reader to both: (i) get insights about the most prominent limitations of the currently deployed addressing architecture, and (ii) survey the existing proposals based on ID/Locator Split Architectures (ILSAs) including an analysis of pros and cons, as well as a taxonomy aiming at formulating a design space for evaluating and designing existing and future ILSAs.

Network Management Challenges and Trends in Multi-Layer and Multi-Vendor Settings for Carrier-Grade Networks

The exponential growth of Internet traffic gives no respite to the telecommunications industry and is visibly shortening the life-cycle of the technologies used for core networking. To cope with the traffic demand, the industry has primarily focused on the evolution of the data and control planes, and has rapidly made progress in both subjects. However, the innovations in the market have not reached the management plane at the same speed. This stems from a number of factors, most of which point to the segmentation of competencies in managing multi-layer infrastructures. Current carrier-grade networks are organized as multi-layer infrastructures, typically composed of two layers: IP routers deployed in tandem with optical transport nodes. In turn, each of the two layers is typically composed of devices from different vendors, each of which usually supplies its own (proprietary) network management system (NMS). In practice, the lack of broadly accepted mechanisms for enabling interoperability among the different NMSs has led to the isolation of these proprietary systems. As a result, the operation and maintenance tasks on the network are becoming increasingly complex, which is leading to duplication of functions, higher OPEX, and significant delays in the coordination of multi-layer provisioning processes. In this paper, we examine in detail the interoperability challenges of managing multi-layer and multi-vendor carrier-grade networks, and review the current trends and recent standards in the area, with strong focus on industrial advances. We cover the Multi-Technology Operations System Interface (MTOSI) as well as OpenFlow, and analyze their potential impact and reach. We also discuss some of the reasons why relevant carrier-grade management proposals have not been able to fulfill the requirements of Internet service providers (ISPs), and identify a set of features that might help pave the way to market for new management products.

Handling service allocation in combined Fog-cloud scenarios

The recent technological advances related to computing, storage, cloud, networking and the unstoppable deployment of end-user devices, are all coining the so-called Internet of Things (IoT). IoT embraces a wide set of heterogeneous services in highly impacting societal sectors, such as Healthcare, Smart Transportation or Media delivery, all of them posing a diverse set of requirements, including real time response, low latency, or high capacity. In order to properly address such diverse set of requirements, the combined use of Cloud and Fog computing turns up as an emerging trend. Indeed, Fog provides low delay for services demanding real time response, constrained to support low capacity queries, whereas Cloud provides high capacity at the cost of a higher latency. It is with no doubt that a new strategy is required to ease the combined operation of cloud and fog infrastructures in IoT scenarios, also referred to as Combined Fog-Cloud (CFC), in terms of service execution performance metrics. To that end, in this paper, we introduce and formulate the QoS-aware service allocation problem for CFC architectures as an integer optimization problem, whose solution minimizes the latency experienced by the services while guaranteeing the fulfillment of the capacity requirements.

Towards Distributed Service Allocation in Fog-to-Cloud (F2C) Scenarios

The novel Fog-to-Cloud (F2C) computing paradigm has been recently proposed aiming at the enhanced integration of Fog Computing and Cloud Computing through the coordinated management of underlying resources, taking into account the peculiarities inherent to each computing model, and enabling the parallel and distributed execution of services into distinct fog/cloud resources. Nevertheless, studies on F2C are still premature and several issues remain unsolved yet. For instance, in an F2C scenario service allocation must cope with the specific aspects associated to cloud and fog resource models, requiring distinct strategies to properly map IoT services into the most suitable available resources. In this paper, we propose a QoS-aware service distribution strategy contemplating both service requirements and resource offerings. We model the service allocation problem as a multidimensional knapsack problem (MKP) aiming at an optimal service allocation taking into consideration delay, load balancing and energy consumption. The presented results, demonstrate that the adopted strategy may be applied by F2C computing reducing the service allocation delay, while also diminishing load and energy consumption on cloud and fog resources.

Evaluating the benefits of combined and continuous Fog-to-Cloud architectures

Abstract The need to extend the features of Cloud computing to the edge of the network has fueled the development of new computing architectures, such as Fog computing. When put together, the combined and continuous use of fog and cloud computing, lays the foundation for a new and highly heterogeneous computing ecosystem, making the most out of both, cloud and fog. Incipient research efforts are devoted to propose a management architecture to properly manage such combination of resources, such as the reference architecture proposed by the OpenFog Consortium or the recent Fog-to-Cloud (F2C). In this paper, we pay attention to such a combined ecosystem and particularly evaluate the potential benefits of F2C in dynamic scenarios, considering computing resources mobility and different traffic patterns. By means of extensive simulations we specifically study the aspects of service response time, network bandwidth occupancy, power consumption and service disruption probability. The results indicate that a combined fog-to-cloud architecture brings significant performance benefits in comparison with the traditional standalone Cloud, e.g., over 50% reduction in terms of power consumption.

Network coding-based protection scheme for Elastic Optical Networks

Optical technologies are the foundations supporting the current telecommunication network backbones due to the high speed transmissions achieved in fiber optical networks. Traditional optical networks consist of a fixed 50 GHz grid, resulting in a low optical spectrum (OS) utilization, specifically with transmission rates above 100 Gbps. This issue is magnified when network resilience capabilities are required. For instance, proactive protection solutions such as Dedicated Protection (DP) are widely used because of their low recovery time. However, a significant drawback of DP is its high utilization of optical bandwidth. Recently, optical networks are undergoing significant changes with the purpose of providing a flexible grid that can fully exploit the potential of optical networks. This has led to a new network paradigm termed as Elastic Optical Networks (EON). Moreover, a novel strategy referred to as network coding (NC) has been proposed with the aim of improving network throughput. In this paper, we propose a proactive protection scheme so-called E-DPNC* that combines both the advantages concerning network throughput offered by EON and NC, and the low recovery time of a DP scheme, in order to enable network resilience against optical link failures while also reducing the optical spectrum utilization. Our evaluation results show that our solution reduces the OS utilization by 41% compared with conventional protection schemes deployed on fixed grid scenarios.

Applying Information Extraction for Abstracting and Automating CLI-Based Configuration of Network Devices in Heterogeneous Environments

With the continuous growth of current networks, configuration management has become increasingly relevant to the Information and Communication Technologies (ICT) field. Despite numerous standardization efforts, network administrators continue to rely on Command-Line Interfaces (CLIs) to modify and control the configuration of network devices. Nevertheless, network administrators must deal with the complexities that derive from this practice. On one hand, CLI-based configuration hinders the automation of network configuration tasks which are typically required in autonomic management. The only means for achieving a certain degree of automation is the creation of custom scripts, which is neither scalable nor practical, and is the reason why configuration management tasks are mainly performed through manual intervention. On the other hand, CLIs are generally both device and vendor-specific. In the context of heterogeneous network infrastructures—i.e., networks typically composed of multiple devices from different vendors—the use of several CLIs raises serious Operation, Administration and Management (OAM) issues. Moreover, multi-vendor configurations not only differ syntactically. Overall, the utilization of proprietary mechanisms allows neither reusing the configurations nor sharing knowledge consistently between vendors’ domains. Due to this heterogeneity, CLIs typically provide a help feature which is in turn a useful source of knowledge to enable semantic interpretation of a configuration space. The large amount of information a network administrator must learn and manage makes Information Extraction (IE) and other forms of natural language analysis of the Artificial Intelligence (AI) field key enablers for the network device configuration space. In this chapter we present an Ontology-Based Information Extraction (OBIE) System from the Command-Line Interface (CLI) of network devices. This system exploits natural language resources already available in CLIs in order to extract relevant information and automatically build the semantics of each configuration space. Overall, our solution provides network administrators with a simple tool which entirely automates and abstracts the complexities and heterogeneity of underlying configuration environments in order to reduce time and effort in the configuration of network devices. With such a tool, network administrators will no longer have to read hundreds of manuals, and configuration scripts can be automatically updated for new devices or system upgrades. We developed a prototype implementation to show how we complete the loop from the process of IE, to the configuration of network devices and final testing.

Ontology-based information extraction from the configuration command line of network routers

Knowledge extraction is increasingly attracting the attention of researchers from different disciplines, as a means to automate complex tasks that rely on bulk textual resources. However, the configuration of many devices in the networking field continues to be a labor intensive task, based on the human interpretation and manual entry of commands through a text-based user interface. Typically, these Command-Line Interfaces (CLIs) are both device and vendor-specific, and thus, commands differ syntactically and semantically for each configuration space. Because of this heterogeneity, CLIs always provide a “help” feature—i.e., short command descriptions encoded in natural language—aimed to unveil the semantics of configuration commands for network administrators. In this paper, we exploit this feature with the aim of automating the abstraction of device configurations in heterogeneous settings. In particular, we introduce an Ontology-Based Information Extraction (OBIE) system from the Command-Line Interface of network routers. We also present ORCONF, a domain Ontology for the Router CONFiguration domain, and introduce a semantic relatedness measure that quantifies the degree of interrelation among candidate concepts. The results obtained over the configuration spaces of two widely used network routers demonstrate that this is a promising line of research, with overall percentages of precision and recall of 93%, and 91%, respectively.

Handling outdated information in optical PCE environments

The rapid emergence of new network scenarios and architectures, such as Data Centers Networks (DCNs), Path Computation Element (PCE), and Software Defined Networking (SDN), has refreshed some on-line routing-related problems, objective of many research efforts in the past. As a result, new scalable and efficient path computation algorithms are required to address particular characteristics and demands of on-line scenarios, such as those brought by inaccurate Network State Information (NSI), strongly affecting the overall blocking probability. In this paper, we propose a prediction-based PCE scheme, referred to as PPCE. PPCE is devised for highly dynamic network scenarios, aiming at reducing the amount of signaling messages as well as the blocking probability.

Towards the scalability of a service-oriented PCE architecture for IoT scenarios

Despite the increasing number of mobile heterogeneous network elements (NEs) interconnected through the Internet, all of them setting the foundations for an agile IoT development, many issues remain still unsolved. The scalability of the current host-oriented Internet model is one of these problems. In this paper, we present a novel service-oriented architecture dealing with the scalability problem leveraging the Path Computation Element (PCE) concept. PCE has already been proved as an efficient technology to decouple the control tasks from the forwarding nodes, what undoubtedly impacts on scalability growth. Given the importance of control solutions for IoT, we propose to enrich the current host-oriented PCE model to become a Service-oriented PCE (SPCE). Results obtained after running several evaluation tests show that the proposed PCE-based solution may support a higher number of Network Elements (NEs).