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Smart Radio Environments (SRE) transform the wireless propagation phenomenon in a programmable process. Leveraging multiple Reconfigurable Intelligent Surfaces (RIS), the wireless waves emitted by a device can be almost freely routed and manipulated, reaching their end destination via improbable paths, with minimized fading and path losses. This work begins with the observation that each such wireless communication customization occupies a certain number of RIS units, e.g., to form a wireless path with consecutive customized reflections. Therefore, SREs can be modeled as a resource of constrained capacity, which needs to be sliced among interested clients. This work provides a foundational model of SRE-as-a-resource, defining Service Level Agreements (SLAs) and Service Level Objectives (SLOs) for the SRE client requests. Employing this model, we study a class of negative drift dynamic weighted round robin policies, that is able to guarantee specific SRE resource shares to competing user requests. We provide a general mathematical framework where the class of policies map ping user requests to resources does not require statistical knowledge regarding the arrival distribution or the duration of each user communication. We study the meaning of work conserving and non-work conserving modes of SRE operation, and also study the convergence properties of our scheduling framework for both cases. Finally, we perform the feasibility space analysis for our framework and we validate our analysis through extensive simulations.

This paper proposes a new paradigm for control plane in Time Sensitive Networks (TSN). An SDN controller proactively instructs network elements on the reconfigurations to perform locally if some specific events occur (e.g., failures, performance degradations). Instructions are given in the form of Finite State Machines (FSMs), which store information related to the actions that each network element should execute to react against a specific event. Thus, if such event occurs, the SDN controller is by-passed reducing reaction (e.g., recovery) time. Such an approach is here implemented for recovery upon failures in TSN. Experiments of failure recovery are carried out and measurements are presented comparing the FSM-based solution with a fully-centralized reactive restoration. Moreover, the proposed approach is compared through simulations against Frame Replication and Elimination for Reliability. Results will show how proactive FSM manipulation can strongly reduce recovery time in SDN-based TSN networks without overloading the network with frame replicas.

We present a graph-based approach for the data management tasks and the efficient operation of a system for session-based next-item recommendations. The proposed method can collect data continuously and incrementally from an ecommerce web site, thus seemingly prepare the necessary data infrastructure for the recommendation algorithm to operate without any excessive training phase. Our work aims at developing a recommender method that represents a balance between data processing and management efficiency requirements and the effectiveness of the recommendations produced. We use the Neo4j graph database to implement a prototype of such a system. Furthermore, we use an industry dataset corresponding to a typical e-commerce session-based scenario, and we report on experiments using our graph-based approach and other state-of-the-art machine learning and deep learning methods., Comment: Preprint version of the paper, the original paper is published on ACM DL. 6 pages, 1 figure, 1 table

In this paper we address the support of wearable mHealth applications in LTE and future 5G networks following a holistic approach that spans across the elements of a mobile network. The communication requirements change from one application to another so we propose a measurement methodology to facilitate the selection of the user equipment to fulfil these requirements. We also discuss a new network architecture to support traffic prioritization, RAN programmability, low latency and group communications to over-the-top applications. Our proposal is validated using several realistic experimentation platforms and the results show that mHealth systems can benefit from our approach.

The proliferation of mobile devices with ubiquitous Internet access has made content access patterns highly volatile and spatio- temporally varying. At the same time, virtualization techniques have enabled the emergence of virtual Content Delivery Network (vCDN) providers, that bundle together a virtual infrastructure by utilizing storage resources anywhere along the path between the access network and the corresponding data center, where the requested content actually resides. In this context, efficient content placement in the various storage layers depends on accurately estimating content access patterns from the different access networks at any given time. At the same time, different vCDN providers compete against each other to provide low content retrieval latency to their users. However, there are some interesting synergies that might emerge among otherwise competing vCDN providers: (i) host content of another vCDN provider and, (ii) provide own content to the users/customers of other vCDN providers. In this paper, we formulate the overall problem of content placement for multiple vCDN providers that employ collaboration as an overall social-welfare maximization problem. The solution to this problem gives the optimal placement, achievable only in the case of full information. Alleviating the need for full information and considering vCDN providers separately as profit seekers, we also devise a distributed algorithm for content placement by exchanging limited information among them. Extensive simulation experiments show that business collaboration among competing vCDN providers is beneficial, as compared to isolated offerings, and allows them to adapt faster to content pattern changes.

International audience; Ultra Dense Networks (UDNs) are a natural deployment evolution for handling the tremendous traffic increase related to the emerging 5G services, especially in urban environments. However, the associated infrastructure cost may become prohibitive. The evolving paradigm of network slicing can tackle such a challenge while optimizing the network resource usage, enabling multi-tenancy and facilitating resource sharing and efficient service-oriented communications. Indeed, network slicing in UDN deployments can offer the desired degree of customization in both vanilla Radio Access Network (RAN) designs, but also in the case of disaggregated multi-service RANs. In this article, we devise a novel multi-service RAN environment, i.e., RAN runtime, capable to support slice orchestration procedures and to enable flexible customization of slices as per tenant needs. Each network slice can exploit a number of services, which can either be dedicated or shared between multiple slices over a common RAN. The novel architecture we present concentrates on the orchestration and management systems. It interacts with the RAN modules, through the RAN runtime, via a number of new interfaces enabling a customized dedicated orchestration logic for each slice. We present results for a disaggregated UDN deployment where the RAN runtime is used to support slice-based multi-service chain creation and chain placement, with an auto-scaling mechanism to increase the performance.

The upcoming 5G ecosystem is envisioned to build business-driven network slices to accommodate the different needs of divergent service types, applications, and services in support of vertical industries. In this article, we describe the network slicing concept by unveiling a novel network slicing architecture for integrated 5G communications. Further, we demonstrate its realization for the case of evolved LTE using state-of-the-art technologies. Finally, we elaborate on the LTE-specific requirements toward 5G, and point out existing challenges and open issues.

In this paper the classical and generalized numerical Rogers–Ramanujan continued fractions are extended to a polynomial continued fraction in one and two dimensions. Using the new continued fractions, the fundamental recurrence formulas and a fast algorithm, based on matrix formulations, are given for the computation of their transfer functions. The presented matrix formulations can provide a new perspective to the analysis and design of Ladder-continued fraction filters in one and two dimensions signal processing. The simplicity and efficiency of the presented algorithms are illustrated by step-by-step examples.

In this work, we present novel Architectural Design Patterns towards open, cloud-based 5G communications. We provide a brief classification of technologies that cannot be ignored in the design process of 5G systems and illustrate how a new technological added value can be created, when current methodologies, design paradigms, as well as design patterns and their extensions are properly exploited in efficient Radio Access Network (RAN) architectures. We believe that in many cases, the required technology is already there; nevertheless the correct approach has to be worked out and placed within an appropriate context, especially in the case of the integration of complex RAN systems. The enhancements in RF optimization, the progress in cloud computing, Software Defined Networks (SDN) and Network Function Virtualization (NFV), new design concepts such as Network Slicing have to become part of the RAN design methodology. Diverse architectural concepts should break existing stereotypes to pave the way towards the true 5G system integration.

In this paper, we provide a revolutionary vision of 5G networks, in which SDN technologies are used for the programmability of the wireless network, and where a NFV-ready network store is provided to Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties. The proposed network serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enables 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the network provider as the application store is currently to a software platform.

In this work, we present how programmable data-plane technology (software routers) offers an easy-to-apply mechanism to create virtual wireless networks and support buffering and scheduling decisions. Furthermore, we present a feedback-based buffering mechanism that is able to provide throughput ratio guarantees per virtual network, without requiring any modifications in the 802.11 driver and without relying on statistical knowledge of the workload per virtual network or knowledge regarding the channel conditions. We implement the proposed mechanism in a software router in a 802.11 Access Point and we evaluate its performance in a wireless testbed environment. The methodology and the mechanics developed are generic and with some modifications can be applied to differentiating services for other types of guarantees like delay.