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

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

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

Resource identification in fog-to-cloud systems: toward an identity management strategy

og-to-Cloud (F2C) is a novel paradigm aiming at extending the cloud computing capabilities to the edge of the network through the hierarchical and coordinated management of both, centralized cloud datacenters and distributed fog resources. It will allow all kinds of devices that are capable to connect to the F2C network to share its idle resources and access both, service provider and third parties’ resources to expand its own capabilities. However, despite the numerous advantages offered by the F2C model, such as the possibility of offloading delay-sensitive tasks to a nearby device and using the cloud infrastructure in the execution of resource-intensive tasks, the list of open challenges that needs to be addressed to have a deployable F2C system is pretty long. In this paper we focus on the resource identification challenge, proposing an identity management system (IDMS) solution that starts assigning identifiers (IDs) to the devices in the F2C network in a decentralized fashion using hashes and afterwards, manages the usage of those IDs applying a fragmentation technique. The obtained results during the validation phase show that our proposal not only meets the desired IDMS characteristics, but also that the fragmentation strategy is aligned with the constrained nature of the devices in the lowest tier of the network hierarchy.Peer ReviewedPostprint (author's final draft

Fog-to-Cloud (F2C) Data Management for Smart Cities

Smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, smart city resources management rely on cloud based solutions where sensors data are collected to provide a centralized and rich set of open data. The advantages of cloudbased frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for real-time or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. We have defined a new framework for data management in the context of a smart city through a global fog to cloud resources management architecture. This model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. In this paper, we present the data acquisition block of our framework and discuss the advantages. As a first experiment, we estimate the network traffic in this model during data collection and compare it with a traditional real systemPeer ReviewedPostprint (published version

Methodology definition for reliable network experimentation

©2013 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.As researchers in the networking area keep adopting experimental network testing as a valid mechanism to develop, validate, and improve their research, it becomes more apparent that an overall framework supporting and assisting during the experimentation process is necessary. Particularly, this assistance is relevant in processes such as experiment preparation, or results validation. As a consequence, the goal, and thus the contribution, of this paper is twofold, on the one hand we propose a novel set of guidelines which establish the set of requirements any testbed for network experimentation should follow. On the other hand, as the other relevant contribution of this work, we propose a mechanism for generating meta-data information on the experiments that ease the publication of the obtained datasets. Finally, as a usecase, we present a particular implementation of this framework which we deploy in a real scenario to prove the capabilities of the proposed testing procedure.This work was partially funded by Spanish Ministry of Science and Innovation under contract TEC2009-07041, and the Catalan Government under contract 2009 SGR1508.Peer ReviewedPostprint (author's final draft

Managing resources continuity from the edge to the cloud: Architecture and performance

The wide spread deployment of smart edge devices and applications that require real-time data processing, have with no doubt created the need to extend the reach of cloud computing to the edge, recently also referred to as Fog or Edge Computing. Fog computing implements the idea of extending the cloud where thePostprint (author's final draft

Deploying fog-to-cloud towards a security architecture for critical infrastructure scenarios

Critical infrastructures are bringing security, and safety for people in terms of healthcare, water, electricity, industry, transportation, etc. The huge amount of data produced by CIs need to be aggregated, filtered, and stored. Cloud computing was merged into the CIs for utilizing cloud data centers as a pay-as-you-go online computing system for outsourcing services for data storage, filtering and aggregating. On the other hand, CIs need real-time processing for providing sophisticated services to people. Consequently, fog computing is merged into CIs aimed at providing services closer to the users, turning into a smooth real-time decision making and processing. When considering both, that is fog and cloud (for example, deploying the recently coined hierarchical fog-to-cloud F2C concept), new enriched features may be applied to the CIs. Security in CIs is one of the most essential challenges since any failure or attack can turn into a national wise disaster. Moreover, CIs also need to support quality of service (QoS) guarantees for users. Thus, bringing balanced QoS vs security is one of the main challenges for any CI infrastructure. In this paper, we illustrate the benefits of deploying an F2C system in CIs, particularly identifying specific F2C security requirements to be applied to CIs. Finally, we also introduce a decoupled security architecture specifically tailored to CIs that can bring security with reasonable QoS in terms of authentication and key distribution time delay.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

Improving IA-RWA algorithms in translucent networks by regenerator allocation

In this paper we present the impact of considering regenerator allocation when selecting routes and wavelengths in translucent networks. In the regular operation of translucent networks, i.e. with dynamic traffic, we assume that a certain number of 3R regenerators are installed in some nodes of the network. These regenerators break the optical transparency of the lightpaths, but allow establishing the optical connections with the required optical signal quality. We show the performance improvement of the MINCOD-Q IA-RWA algorithm when an efficient regenerator allocation policy is employed (optical regeneration is only performed when the signal quality goes bellow a pre-established threshold). Under this policy, the (extended) MINCOD-Q algorithm performs slightly better in terms of blocking probability, but and most important, this figure is obtained with a significant reduction of the number of 3R regenerators installed in the network.Postprint (published version

Exploring potential implementations of PCE in IoT world

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The recently coined Internet of Things (IoT) paradigm leverages a large volume of heterogeneous Network Elements (NEs) demanding broad connectivity anywhere, anytime and anyhow, fueling the deployment of innovative Internet services, such as Cloud or Fog Computing, Data Center Networks (DCNs), Smart Cities or Smart Transportation. The proper deployment of these novel Internet services is imposing hard connectivity constraints, such as high transmission capacity, reliable communications, as well as an efficient control scheme capable of enabling an agile coordination of actions in large heterogeneous scenarios. In recent years, novel control schemes, such as the so-called Path Computation Element (PCE) has gained momentum in the network research community turning into real PCE implementations. Indeed, there is a wealth of studies assessing the PCE performance, clearly showing the potential benefits of decoupling routing control tasks from the forwarding nodes. Nevertheless, recognized the need for a control solution in IoT scenarios, there is not much published information analyzing PCE benefits in these IoT scenarios. In this paper, we distill how the PCE may gracefully provide for service composition in an agile manner, handling the specific constraints and requirements found in IoT scenarios. To this end, we propose a novel PCE strategy referred to as Service-Oriented PCE (SPCE), which enables network-aware service composition.Peer ReviewedPostprint (author's final draft