Bego Blanco

Technology pillars in the architecture of future 5G mobile networks: NFV, MEC and SDN

This paper analyzes current standardization situation of 5G and the role network softwarization plays in order to address the challenges the new generation of mobile networks must face. This paper surveys recent documentation from the main stakeholders to pick out the use cases, scenarios and emerging vertical sectors that will be enabled by 5G technologies, and to identify future high-level service requirements. Driven by those service requirements 5G systems will support diverse radio access technology scenarios, meet end-to-end user experienced requirements and provide capability of flexible network deployment and efficient operations. Then, based on the identified requirements, the paper overviews the main 5G technology trends and design principles to address them. In particular, the paper emphasizes the role played by three main technologies, namely SDN, NFV and MEC, and analyzes the main open issues of these technologies in relation to 5G.

Size-based and channel-aware scheduling algorithm proposal for mean delay optimization in wireless networks

This paper deals with the analysis of the impact of different scheduling algorithms on flow level mean delay performance of elastic traffic in a single cell wireless downlink data channel paradigm. An enhanced size-based and channel-aware discipline is proposed, which is based on the sized-aware Gittins index approach applied to a time-varying channel context. In order to compare the proposed Opportunistic Gittins rule performance with well-known scheduling algorithms, several simulations have been performed for stochastically arriving flows with Pareto sizes under fading conditions, for different network loads and channel quality indicator reporting rates. As concluded, an approach that combines both flow size-awareness and channel-awareness is the best option, which guarantees a trade-off between minimizing uplink overhead due to channel quality reports and improving scheduling performance aimed at reducing overall flow mean delay.

Service provisioning and pricing methods in a multi-tenant cloud enabled RAN

The Cloud Enabled Small Cell (CESC) concept proposed in EU funded project SESAME has emerged as a promising solution to form a multi-tenant, multi-service architecture at the network edge according to 5G needs. It allows several operators/service providers to engage in a sharing model of both radio access capacity and Mobile Edge Computing (MEC) capabilities. From a business perspective, the shared ecosystem guarantees benefits such as easy system upgrades and CAPEX/OPEX reduction. However, depending on the adapted model which is reflected at Service Level Agreement (SLA) between involved stakeholders, cost and benefit of each party are subject to change. This paper is an effort to identify and analyse different radio and cloud models and pricing schemes for the joint provisioning of radio access capacity and MEC services in a multi-tenant Radio Access Network (RAN).

Design of Cognitive Cycles in 5G Networks

Adding cognitive capabilities to the wireless networks makes it possible to leverage the control and management information used in the network operation to infer information about the local state and exploit it to improve the overall performance. This paper deals with the combined use of centralized and distributed cognitive cycles integrated at different planes in 5G networks: an integrated data plane, a unified control plane and a cross-layer management plane. This context-aware cognitive schema acts on the decision making modules depending on the monitored environment to prevent failures, balance the virtualized execution and get a global enhancement in the provision of mobile services. The multi-level cognitive cycle supports the interaction between the edge and the cloud blurring the line that separates two paradigms: centralized radio operation and mobile edge services.

Suitability of ad hoc routing in WNR

A major issue in the application of ad hoc networking to Wireless Networked Robotics is the choice of the routing protocol that performs better in a given scenario. However, far too little attention has been paid to routing issues involving enhanced robotic nodes. In view of the lack of a significant and comprehensive analysis, this research work completes an in-depth performance comparison of mostly well-known ad hoc routing protocols under a wide variety of conditions and applies the obtained results to a case study with three examples of real-world Wireless Networked Robotics scenarios.

Application of Cognitive Techniques to Adaptive Routing for VANETs in City Environments

The evolution of smart vehicles has widened the application opportunities for vehicular ad hoc networks. In this context, the routing issue is still one of the main challenges regarding to the performance of the network. Although there are multiple ad hoc routing proposals, the traditional general-purpose approaches do not fit the distinctive properties of vehicular network environments. New routing strategies must complement the existing protocols to improve their performance in vehicular scenarios. This paper introduces a novel intelligent routing technique that makes decisions in order to adaptively adjust its operation and obtain a global benefit. The nodes sense the network locally and collect information to feed the cognitive module which will select the best routing strategy, without the need of additional protocol message dissemination or convergence mechanism.

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.

Performance Analysis of a Network Sensor's Packet Processing System using Generalized Stochastic Petri Nets

This paper describes a modeling based on Generalized Stochastic Petri Nets (GSPN) to analyze the performance of a network probing node in terms of throughput. The probing node is part of a distributed monitoring system. In this environment, the use of multiprocessor and multicore systems, as well as the parallelization of applications, is aimed at improving the node performance. Petri nets allow not only to represent the parallelization feature, but also to include the main events identified in the system: the packet arrival and a two-stage processing. The two-stage processing consists of a first stage in which packet capturing functionalities are performed, and a second stage in which a deeper packet treatment is performed. In addition, the Petri net model can reproduce a shared buffer control mechanism to ensure the integrity of the data. After detailing all the model components, the verification and validation of the model are done by using a simulation tool. With this model, it is expected to estimate the efficiency of the probing node early in the design and development stages.

Providing Mission-Critical Services over 5G Radio Access Network

5G is called to introduce a major transformation in communication network architectures with its transition to cloud native networks. This transformation will enable new unique service capabilities that will drive the development of innovative applications. But, for 5G being successful in this task, the identification of the vertical sectors’ requirements is of outmost importance in order to map them into the design of the network architecture. This paper proposes a novel Cloud-Enabled Radio Access Network (CE-RAN) architecture to support Public Safety services at the edge of the network. This proposal leverages Network Functions Virtualisation, Software Defined Networking and Mobile Edge Computing principles to provide Mission-Critical services through an isolated network slice. We suggest a CE-RAN architecture with two levels of cloudification to bring the service closer to the end user.

Energy vs. QoX Network- and Cloud Services Management

Network Performance (NP)- and more recently Quality of Service/Experience/anything (QoS/QoE/QoX)-based network management techniques focus on the maximization of associated Key Performance Indicators (KPIs). Such mechanisms are usually constrained by certain thresholds of other system design parameters. e.g., typically, cost. When applied to the current competitive heterogeneous Cloud Services scenario, this approach may have become obsolete due to its static nature. In fact, energy awareness and the capability of modern technologies to deliver multimedia content at different possible combinations of quality (and prize) demand a complex optimization framework.