Optical Multi-Domain Routing

Optical networks provide a clear opportunity to redesign the multi-domain routing paradigm. This paper reviews the current limitations in multi-domain routing as well as some of the research lines in the optical area.Postprint (published version

Optical Multi-Domain Routing

Optical networks provide a clear opportunity to redesign the multi-domain routing paradigm. This paper reviews the current limitations in multi-domain routing as well as some of the research lines in the optical area.Postprint (published version

A survey of communication protocols for internet of things and related challenges of fog and cloud computing integration

The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput. These findings are thereafter used to place the protocols in each segment of the system (IoT, fog, cloud), and thus opens up the discussion on their choice, interoperability, and wider system integration. The survey is expected to be useful to system architects and protocol designers when choosing the communication protocols in an integrated IoT-to-fog-to-cloud system architecture.Peer ReviewedPostprint (author's final draft

A survey on mobility-induced service migration in the fog, edge, and related computing paradigms

The final publication is available at ACM via http://dx.doi.org/10.1145/3326540With the advent of fog and edge computing paradigms, computation capabilities have been moved toward the edge of the network to support the requirements of highly demanding services. To ensure that the quality of such services is still met in the event of users’ mobility, migrating services across different computing nodes becomes essential. Several studies have emerged recently to address service migration in different edge-centric research areas, including fog computing, multi-access edge computing (MEC), cloudlets, and vehicular clouds. Since existing surveys in this area focus on either VM migration in general or migration in a single research field (e.g., MEC), the objective of this survey is to bring together studies from different, yet related, edge-centric research fields while capturing the different facets they addressed. More specifically, we examine the diversity characterizing the landscape of migration scenarios at the edge, present an objective-driven taxonomy of the literature, and highlight contributions that rather focused on architectural design and implementation. Finally, we identify a list of gaps and research opportunities based on the observation of the current state of the literature. One such opportunity lies in joining efforts from both networking and computing research communities to facilitate future research in this area.Peer ReviewedPreprin

A user-centric mobility management scheme for high-density fog computing deployments

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe inherent mobility characterizing users in fog computing environments along with the limited wireless range of their serving fog nodes (FNs) drives the need for designing efficient mobility management (MM) mechanisms. This ensures that users' resource-intensive tasks are always served by the most suitable FNs in their vicinity. However, since MM decisionmaking requires control information which is difficult to predict accurately a-priori, such as the users' mobility patterns and the dynamics of the FNs, researchers have started to shift their attention towards MM solutions based on online learning. Motivated by this approach, in this paper, we consider a bandit learning model to address the mobility-induced FN selection problem, with a particular focus on scenarios with a high FN density. Following this approach, a software agent implemented within the user's device learns the FNs' delay performances via trial and error, by sending them the user's computation tasks and observing the perceived delay, with the goal of minimizing the accumulated delay. This task is particularly challenging when considering a high FN density, since the number of unknown FNs that need to be explored is high, while the time that can be spent on learning their performances is limited, given the user's mobility. Therefore, to address this issue, we propose to limit the number of explorations to a small subset of the FNs. As a result, the user can still have time to be served by the FN that was found to yield the lowest delay performance. Using real world mobility traces and task generation patterns, we found that it pays off to limit the number of explorations in high FN density scenarios. This is shown through significant improvements in the cumulative regret as well as the instantaneous delay, compared to the case where all newly-appeared FNs are explored.Peer ReviewedPostprint (author's final draft

An edge-based strategy for smart advertising

Smart advertising creates awareness about some offer with a more direct, personalized and interactive focus. In this area, AROUND is a social network aimed at providing smart advertising to suggest appealing business to their customers and friends. The AROUND system is supported by a sophisticated recommender system, which considers not only the customers historical behaviours, but also their current mood and accurate location. In such smart recommendation systems, the response time for the personalized advertising is critical for a successful users’ quality of experience. In this research work we first evaluate the current performance of the AROUND system in terms of processing and communication times considering that, nowadays, this social network has more than 3 million users. The current implementation of the system relies on the deployment of a network of beacons, and uses a domestic cloud provider as the main infrastructure. We show that when the number of concurrent requests becomes too high, the response time faces some limitations. In order to address this issue, we discuss several alternatives, and propose the use of an edge-based strategy as a solution for fast response time. In the experimental section, we measure the performance of the AROUND system, both in our current infrastructure at the cloud and with an edge-based approach, and show the additional advantages of leveraging the edge-based strategy even in the case of overloading the cloud capacity.This work has been supported by the Spanish Ministry of Science, Innovation and Universities and by the European Regional Development Fund (FEDER) under contract RTI2018-094532-B-I00.Peer ReviewedPostprint (author's final draft

Essentiality of managing the resource information in the coordinated fog-to-cloud paradigm

This is the peer reviewed version of the following article: Sengupta, S, Garcia, J, Masip‐Bruin, X. Essentiality of managing the resource information in the coordinated fog‐to‐cloud paradigm. Int J Commun Syst. 2019, which has been published in final form at https://doi.org/10.1002/dac.4286. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Fog-to-cloud (F2C) computing is an emerging computational platform. By combing the cloud, fog, and IoT, it provides an excellent framework for managing and coordinating the resources in any smart computing domain. Efficient management of these kinds of diverse resources is one of the critical tasks in the F2C system. Also, it must be considered that different types of services are offered by any smart system. So, before managing these resources and enabling the various types of services, it is essential to have some comprehensive informational catalogue of resources and services. Hence, after identifying the resource and service-task taxonomy, our main aim in this paper is finding out a solution for properly organizing this information over the F2C system. For that purpose, we are proposing a modified F2C framework where all the information is distributively stored near to the edge of the network. Finally, by presenting some experimental results, we evaluate and validate the performance of our proposing framework.This work has been supported by the Spanish Ministry of Science, Innovation and Universities and by the European Regional Development Fund (FEDER) under contract RTI2018-094532-B-I00 and by the H2020 European Union mF2C project with reference 730929.Peer ReviewedPostprint (published version

Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems

The recent advances in cloud services technology are fueling a plethora of information technology innovation, including networking, storage, and computing. Today, various flavors have evolved of IoT, cloud computing, and so-called fog computing, a concept referring to capabilities of edge devices and users' clients to compute, store, and exchange data among each other and with the cloud. Although the rapid pace of this evolution was not easily foreseeable, today each piece of it facilitates and enables the deployment of what we commonly refer to as a smart scenario, including smart cities, smart transportation, and smart homes. As most current cloud, fog, and network services run simultaneously in each scenario, we observe that we are at the dawn of what may be the next big step in the cloud computing and networking evolution, whereby services might be executed at the network edge, both in parallel and in a coordinated fashion, as well as supported by the unstoppable technology evolution. As edge devices become richer in functionality and smarter, embedding capacities such as storage or processing, as well as new functionalities, such as decision making, data collection, forwarding, and sharing, a real need is emerging for coordinated management of fog-to-cloud (F2C) computing systems. This article introduces a layered F2C architecture, its benefits and strengths, as well as the arising open and research challenges, making the case for the real need for their coordinated management. Our architecture, the illustrative use case presented, and a comparative performance analysis, albeit conceptual, all clearly show the way forward toward a new IoT scenario with a set of existing and unforeseen services provided on highly distributed and dynamic compute, storage, and networking resources, bringing together heterogeneous and commodity edge devices, emerging fogs, as well as conventional clouds.Peer ReviewedPostprint (author's final draft

SFDDM: a secure distributed database management in combined fog-to-cloud systems

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Technological revolutions have greatly increased the use of IoT devices for our daily life. Driving the fact that everything surrounding us is getting connected what turns into an unstoppable increase in the amount of data produced. This data represents the state of diverse environmental events and helps to control a large set of distinct activities. So, accurate and secure management of this data is essential for any computing platform. Moreover, in order to provide real-time services in a distributed system (i.e., smart city), the data should be properly and securely managed. It is well known that shifting these tasks to the edge (i.e., near to the end users), highly facilitates these two objectives. The recently proposed Fog-to-Cloud (F2C) model is intended to enable data processing near to the edge, which helps to get better latency-sensitive services. However, some challenges remain to accurately and securely manage this data over the system, mainly due to the distributed F2C nature. Thus, considering these facts and challenges, in this paper we propose an architectural solution aimed at building a secure distributed database for F2C systems. Then, considering a real-case scenario, we perform some tests to measure the performance of our proposing schema. Finally, by comparing the performance between traditional cloud, fog/edge based execution model and our proposing SFDDM, we validate the effectiveness of our proposing schema.This work has been supported by the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund (FEDER) under contract RTI2018- 094532-B-I00, and by the H2020 European Union mF2C project with reference 730929.Peer ReviewedPostprint (author's final draft

Hybrid clouds for data-Intensive, 5G-Enabled IoT applications: an overview, key issues and relevant architecture

Hybrid cloud multi-access edge computing (MEC) deployments have been proposed as efficient means to support Internet of Things (IoT) applications, relying on a plethora of nodes and data. In this paper, an overview on the area of hybrid clouds considering relevant research areas is given, providing technologies and mechanisms for the formation of such MEC deployments, as well as emphasizing several key issues that should be tackled by novel approaches, especially under the 5G paradigm. Furthermore, a decentralized hybrid cloud MEC architecture, resulting in a Platform-as-a-Service (PaaS) is proposed and its main building blocks and layers are thoroughly described. Aiming to offer a broad perspective on the business potential of such a platform, the stakeholder ecosystem is also analyzed. Finally, two use cases in the context of smart cities and mobile health are presented, aimed at showing how the proposed PaaS enables the development of respective IoT applications.Peer ReviewedPostprint (published version