Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

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Author: search.filters.author.Alcaraz, SalvadorHas files: Yes

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    Relocation of container-based services in a MEC-NFV orchestrated environment
    (Springer, 2024)
    Bernad, Cristina
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    Roig, Pedro
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    Alcaraz, Salvador
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    Gilly, Katja
    With the rapid growth of real-time next-generation mobile services, it has become necessary to work towards holistic orchestration of the benefits promised with edge computing based on bringing the computing infrastructure closer to the end user. While the concept of Multi-access Edge Computing (MEC) integrated with Network Function Virtualisation (NFV) is being standardised, there is still a lot of work to be done to orchestrate the relocation of edge applications integrated in 5G and beyond systems in a smooth and efficient manner. In this paper, we document the current status of the transparent relocation of edge services in an experimentally deployed MEC-NFV environment based on OSM. Working towards gathering monitoring training datasets necessary for the development of proactive MEC application orchestrators that will implement seamless follow-me behaviour for MEC services, we provide benchmark results for the service downtime of three potential MEC services hosted in lightweight containers. Our analysis of results shows that containers exhibit improved performance over that of virtual machines, but there are still some issues that require improvement in both the orchestration implementation as well at the relocation process for containers.
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    MEC Empowered Internet of Vehicles for Smart City Optimisations
    (IEEE, 2024-03-01)
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    Bernad, Cristina
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    Gilly, Katja
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    Roig, J. Pedro
    With the growth of data driven services, vehicles are moving one step beyond their connected nature by becoming an intelligent part of the Internet of Things ecosystem. The concept of Internet of Vehicles (IoV) stems from this development describing the network of humans, vehicles and things as a means of achieving an intelligent urban infrastructure. With the next-generation communication technologies promise of providing ultra low latencies, one of the major obstacles in achieving highly-performing smart city is the distribution of computing power where the vehicles computing power is no longer sufficient for the increasing multimedia based services and the cloud introducing unacceptable latency for real time scenarios. As multi-access edge computing (MEC) can be employed to overcome these issues by co-locating additional computing power with the communication access points, the main goal of this paper is to investigate the performances of this complex MEC empowered IoV ecosystem to support the development of smart cities. Our analysis shows that large scale urban scenarios can be created to simulate all relevant aspects of the ecosystem as a whole, but more work is needed in optimising the underlying technologies and their performances.
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    Multi-access Edge Computing Smart Relocation Approach from an NFV Perspective
    (Springer Nature, 2023-01-01)
    Bernad, Cristina
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    Roig, Pedro Juan
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    Alcaraz, Salvador
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    Gilly, Katja
    This paper analyses the virtualised entities migration process implementation within the ETSI-compliant edge framework, considering the necessary multi-access edge computing (MEC) modules information interchange required for instantiation, termination and migration of MEC applications. Based on the variant of the MEC-NFV architecture and the functions of each element of it, a communication process that includes network function virtualisation (NFV) interfaces is provided, as a step towards the unresolved challenge of modelling and developing a migration procedure that is aligned with the MEC standardisation process.
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    End-to-end simulation environment for mobile edge computing
    (Elsevier BV, 2022-12)
    Gilly, Katja
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    Bernad, Cristina
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    Roig, Pedro J.
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    Alcaraz, Salvador
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    Performances analysis of resource management techniques and algorithms for edge computing is a crucial step that reveals the effectiveness of edge service placement and migration strategies in terms of delay and usage. To be able to gauge how different optimisations affect the end user quality of experience a holistic approach is needed, so that the end-to-end delay can be measured in a combined setup where the edge infrastructure is integrated in the 5G system architecture. For these purposes we put forward an open source workflow based on the integration of proven simulators as SUMO, OMNeT++ and CloudSim, that will provide the means to create large scale urban mobile simulation environments. This paper discusses the benefits and challenges of such an approach, and provides example results that showcase a few aspects of the potential end-to-end delay analysis by processing the gathered simulation output.
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    An efficient architecture for edge data center networks
    (2022)
    Roig, Pedro Juan
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    Alcaraz, Salvador
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    Gilly, Katja
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    Bernad, Cristina
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    Edge AI environments are ever increasing as the amount of IoT-connected devices grow, thus rising the level of carbon emissions of such ecosystems. Therefore, sustainable AI cloud/edge systems are a must in order to minimize all those emissions, where AI plays its part in gaining efficiency. In this paper, a scheme to easily organize and optimize the computing resources in an edge data center is going to be proposed, based on a specific toroidal grid topology which minimizes distance between any pair of hosts being part of it, thus reducing energy needs. That architecture may be dynamically adjusted according to the current traffic conditions and their expected variations so as to further save power consumption by using just the necessary computing assets.
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    Formal algebraic modelling of a city-wide smart parking system
    (IEEE, 2020-06-12)
    Juan Roig, Pedro
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    Alcaraz, Salvador
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    Gilly, Katja
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    Aknin, Noura
    One of the main applications of smart cities are parking systems based on IoT/Fog technology. In this paper, we carry out the study of formal algebraic models for such systems. In that context, first of all we undertake the study of a model for a street with a single parking space, extending it with a string of parking spaces. Additionally, we add up some parking control at fog level in order to apply parking restrictions in case of local environment issues, such as air pollution or poor weather conditions. Eventually, we also add up an orchestration level so as to prevent parking related to intelligence information, such as traffic congestion down the road, an accident nearby, or adverse weather forecast to come.
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    Formal Algebraic Specification of an IoT/Fog Data Centre for Fat Tree or Leaf and Spine architectures
    (IEEE, 2020-06-12)
    Juan Roig, Pedro
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    Alcaraz, Salvador
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    Gilly, Katja
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    Aknin, Noura
    Fog computing is an evolution of cloud computing paradigm, whose key point is the location of computing resources at the edge of the network. Data center facilities at the fog level are smaller than those at the cloud level, but nevertheless, they may share similar topologies, such as fat tree or leaf and spine architectures. In this paper, a formal algebraic specification of an IoT/Fog environment based on each of both architectures is presented, where users may be moving around and their associated computing assets are meant to migrate among hosts in order to follow their respective users so as to be as close as possible to them.
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    Modelling edge computing in urban mobility simulation scenarios
    (IEEE, 2020-06-22)
    Gilly, Katja
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    Alcaraz, Salvador
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    Aknin, Noura
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    One of the main challenges in edge computing service management is to continuously maintain a high level of quality of service for the end-user mainly in terms of low latency. This can only be achieved with intelligent management of the edge infrastructure virtualised resources making sure that the edge services are always hosted on resources located as close to the end-user as possible. Thus, the problem of resource allocation and service migration in edge computing is intricately related to the user location and mobility pattern. Therefore, it is of great importance to analyse the edge services performance of proposed management techniques in an urban scenario with realistic mobility model. For these purposes, in this paper we discuss the problem of edge computing simulation and describe an integrated solution environment based on the combination of two proven simulators for datacentre services and urban mobility modelling.
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    Predictive Migration Performance in Vehicular Edge Computing Environments
    (MDPI AG, 2021-01-21)
    Gilly, Katja
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    Alcaraz, Salvador
    <jats:p>Advanced learning algorithms for autonomous driving require lots of processing and storage power, which puts a strain on vehicles’ computing resources. Using a combination of 5G network connectivity with ultra-high bandwidth and low latency together with extra computing power located at the edge of the network can help extend the capabilities of vehicular networks. However, due to the high mobility, it is essential that the offloaded services are migrated so that they are always in close proximity to the requester. Using proactive migration techniques ensures minimum latency for high service quality. However, predicting the next edge server to migrate comes with an error that can have deteriorating effects on the latency. In this paper, we examine the influence of mobility prediction errors on edge service migration performances in terms of latency penalty using a large-scale urban vehicular simulation. Our results show that the average service delay increases almost linearly with the migration prediction error, with 20% error yielding almost double service latency.</jats:p>
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    Offloading Edge Vehicular Services in Realistic Urban Environments
    (Institute of Electrical and Electronics Engineers (IEEE), 2020-01-09)
    Gilly, Katja
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    Alcaraz, Salvador
    The imminent deployment of 5G and the rapid development of multi-access edge computing standards are demanding advances in terms of vehicular low latency offloading design and modelling proposals. In this paper we describe the functionalities of a high-level multi-access edge computing orchestrator that arranges location based vehicular edge services by the means of hierarchical dynamic resource management. In this way low latency responses can be guaranteed due to the geo-aware and energy efficient service allocation and dynamic migration. The first steps towards the definition of a vehicle to infrastructure communication specification are also provided. We study the efficiency of our proposal applied to an infotainment case study deployed in the city centre of Alicante, Spain. The simulation results obtained show that latencies perceived by vehicles generally range from optimal to first order sub-optimal scales all over the coverage area and that the presented offloading solution energetically scales with the number of hosts at the edge.