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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Comparing the Use of Simu5G and 5G‐Sim‐V2I/N Modules When Analysing the Edge Computing Resource Management Efficiency
(Wiley, 2025-04-29)
Bernad, Cristina
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Gilly, Katja
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Thomas, Nigel
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Roig, Pedro Juan
Performance analysis of smart edge computing orchestration algorithms should be done using a realistic urban simulation environment wherein mobile users are accessing their edge services using a readily available 5G network. In this paper, we investigate the influence of using two different 5G simulation frameworks, which are provided as readily available possibilities to model the access network used to deliver edge computing services. The results show that although both frameworks aim to implement the 5G specifications and are deemed suitable choices for simulating a 5G smart city vehicular environment, there can be significant differences in the obtained macro results. The analysis of the simulation results from two identical studies where the only change is the choice of a 5G simulation framework shows that the obtained average end-to-end edge service latency as perceived by edge users can differ up to more than 21 times. The choice of 5G simulation framework is also reflected in the overall generated workload for the edge computing orchestration leading to over 25% more migrations when using 5G-Sim-V2I/N compared to Simu5G.
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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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IoT Serverless Computing at the Edge: Open Issues and Research Direction
(Scholar Publishing, 2021-12)
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Bernad Canto, Cristina
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Juan Roig, Pedro
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Gilly, Katja
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Novel computing paradigms aim to enable better hardware utilization, allowing a greater number of applications to be executed on the same physical resources. Serverless computing is one example of such an emerging paradigm, enabling faster development, more efficient resource usage, as well as no requirements for infrastructure management by end users. Recently, efforts have been made to utilize serverless computing at the network edge, primarily focusing on supporting Internet of Things (IoT) workloads. This study explores open issues, outlines current progress, and summarizes existing research findings about serverless edge computing for IoT by analyzing 67 relevant papers published between 01.01.2015 and 01.09.2021. We discuss the state-of-the-art research in 8 subject areas relevant to the use of serverless at the network edge, derived through the analysis of the selected articles. Results show that even though there is a noticeable interest for this topic, further work is needed to adapt serverless to the resource constrained environment of the edge.
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Implementing Multi-Access Edge Computing with Kubernetes
(ICT Innovations, 2022)
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Bernad Canto, Cristina
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Gilly, Katja
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The introduction of novel telecommunication standards such as 5G and beyond, which offer increased throughput and more efficient network communication, serve as enablers for new technologies. One of these technologies is Multi-Access Edge Computing (MEC), with the potential to revolutionize existing computing architectures and their feature set as we know them to-day. By collocating compute nodes with mobile networking equipment, customers are offered reduced latency and increased privacy, compared to alternative scenarios where the traffic is indiscriminately routed to the cloud. However, the distributed nature of the mobile landscape, coupled with the huge number of involved parties, requires careful consideration and standardization before any rollout. A number of reference documents have been published in recent years with the aim of standardizing the communication interfaces of MEC. We discuss these standardization efforts and provide a description of a MEC architecture centered around the Kubernetes container orchestrator, replacing the concept of virtualized MEC applications with containerized instances which can be deployed as serverless functions. We also offer a use-case scenario leveraging the described component mapping, showcasing the scalability and load-balancing features of the proposed architecture.
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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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Mobile‐aware dynamic resource management for edge computing
(Wiley, 2019-04-26)
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Gilly, Katja
Shifting cloud computing capabilities close to the edge enables provisioning of low latency location-based Internet services that are adapted to user behaviour. However, this can be achieved neither with a simple move of the physical hosts closer to edge networks, nor continuing to abide by the same principles as the ones implemented in traditional cloud computing approaches. In order to accomplish the promised high quality of service, changes must be made to the resource management techniques so that they are adapted to the requirements of fog computing. This paper introduces a novel location-based handoff management and its corresponding implementation of dynamic resource management modules that introduce resource allocation and migration strategies adapted specifically to fog computing. The aim is the implementation of the follow-me behaviour of edge resources considering a tightly coupled perspective with the user location. The proposal is based on the concept of mapping physical areas to logical resource communities while triggering migration of resources to the corresponding logical community when mobile nodes move from the boundaries of one physical area to another. The results analysis from the simulation-based scenarios shows that the effectiveness of our community-based dynamic resource management proposal in following the geographical trajectory of mobile users with wearable devices is over 90% and that it copes very well for highly saturated environments. The comparison with traditional resource management techniques clearly presents the advantages of our proposal, while the parameter wise in-depth analysis discusses its dependencies on the number of mobile nodes, speed, and available resources.
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Dynamic Resource Management of Real-Time Edge Services for Intelligent Vehicular Networks: A Case Study
(Publishing House Technologija, 2019-08-07)
Gilly, Katja
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Alcaraz Carrasco, Salvador
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<jats:p>The Internet of Vehicles requires high bandwidth and low latency services to unleash the potential of fully connected vehicles. Thus, the offloading proposals that successfully manage massive real-time service requests from vehicle nodes are needed. In this paper, we analyse the dynamic resource management for intelligent vehicular networks based on Multi-access Edge Computing architecture services. Using a combination of CloudSim and SUMO simulators, we present a case study of infotainment services in the city centre of Alicante, in Spain, that shows a high degree of optimality both in service allocation and migration when considering dense urban environments.</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.

Faculty of Computer Science and Engineering

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