A novel model using Reo for IoT self-configuration systems

Abdellaoui, Ghouthi; Megnafi, Hicham; Bendimerad, Fethi Tarik

doi:10.1109/ccssp49278.2020.9151679

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…We see that the solution 1,2, 3,4,6,7,8,9,10,11,12,13 is better that the solution obtained by de GA algorithme, it cover 2780 users Modified GA algorithm has replaced region 5 which has 120 customers by the subset of regions formed by the regions: 9,10,11,12,13 and we note that the sum of the population of this subset is equal to 130 customers, we also notice that region 4 which has 150 customers has not been replaced because there is no subset which replaces this region and which can improve the solution.…”

Section: The Modified Gamentioning

confidence: 92%

“…There are numerous and important complex problems in 5G that needs to be solved efficiently like the problem of resource management [1,5], the problem of planning and dimensioning [6], the problem of antenna positioning and selection [7], the problem of optimal routing [8,9,11], the problem of Inspection of the Cellular Networks Relays [10], and so on. These problems are also characterized by the great number of possible solutions.…”

Section: Introductionmentioning

confidence: 99%

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A Modified Greedy Algorithm for Solving the Planification of eNodB Position in 5G network

2022

IICAST-22, TCBEM-22, ALHSS-22 &Amp; TBEEL-22 Dec. 15-16, 2022 Istanbul (Turkey)

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5th generation mobile networks known as 5G can provide high-speed internet connection with a very large number of connected objects, but due to high propagation loss and characteristics sensitive to blocking millimeter waves (mm waves), the deployment of such a network requires to install ultra-dense base stations (eNodB) to achieve satisfactory coverage of communication services. However, finding optimal locations for these enodBs allow reducing the construction and operating costs of this type of network ensuring a best quality of coverage. Essentially, 5G eNodB location optimization to cover the largest users can be considered as a type of maximum coverage localization problem which is considered as a NP-complete problem which cannot be solved in determinate polynomial time, we propose an algorithm based on artificial intelligence approaches which give an approximate solution for this problem. The chosen so-called greedy algorithm initially favors the most important request areas, i.e. those with the greatest number of customers; the application of this technique allows optimizing the locations of eNodB which ensures maximum customer coverage. We were able to improve the result obtained by GA by proposing a new region selection technique, which is our contribution, in order to avoid a solution that remains stuck in a local minimum. The application of modified GA on the case of the city of Tlemcen gave a better solution than that found with the GA version.

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Section: The Modified Gamentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

A Modified Greedy Algorithm for Solving the Planification of eNodB Position in 5G network

2022

IICAST-22, TCBEM-22, ALHSS-22 &Amp; TBEEL-22 Dec. 15-16, 2022 Istanbul (Turkey)

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“…Achieving self-configuration in real time would smooth these processes that usually underserve the requesting users, which can be highly inconvenient in specific applications. Abdellaoui et al [ 94 ] propose a real-time self-configuration system that is capable of automatically connecting and disconnecting the modules (components) that make up the applications to reduce service outages and cause the least possible interruptions. Each connected object in the application is considered as a software module that is added or removed to be updated separately.…”

Section: Literature Review and Analysismentioning

confidence: 99%

Self-* Capabilities of Cloud-Edge Nodes: A Research Review

S-Julián

Lacalle

Vaño

et al. 2023

Sensors

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Most recent edge and fog computing architectures aim at pushing cloud-native traits at the edge of the network, reducing latency, power consumption, and network overhead, allowing operations to be performed close to data sources. To manage these architectures in an autonomous way, systems that materialize in specific computing nodes must deploy self-* capabilities minimizing human intervention across the continuum of computing equipment. Nowadays, a systematic classification of such capabilities is missing, as well as an analysis on how those can be implemented. For a system owner in a continuum deployment, there is not a main reference publication to consult to determine what capabilities do exist and which are the sources to rely on. In this article, a literature review is conducted to analyze the self-* capabilities needed to achieve a self-* equipped nature in truly autonomous systems. The article aims to shed light on a potential uniting taxonomy in this heterogeneous field. In addition, the results provided include conclusions on why those aspects are too heterogeneously tackled, depend hugely on specific cases, and shed light on why there is not a clear reference architecture to guide on the matter of which traits to equip the nodes with.

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“…The data measured during the Drive Test operation is stored on servers external to the company, The engineers then have to retrieve this data and process it to generate a measurement report. But this causes a time problem in the generation of reports [7]. This paper allows to develop a macro under Mapbasic which offers the possibility to extract figures that represent the radio coverage distribution and radio link quality in a map, and on the other hand to analyze them ISBN 978-989-9121-17-1 46th ISTANBUL-TURKEY International Conference on "Advances in Science & Technology" (IICAST-22) Dec. 15-16, 2022 Istanbul (Turkey) in order to propose actions to improve the quality of the link between the mobile and the BTS.…”

Section: Introductionmentioning

confidence: 99%

Automation of Radio Parameter Assessment by Developing a GIS Application for Radio Networks Optimization

2022

IICAST-22, TCBEM-22, ALHSS-22 &Amp; TBEEL-22 Dec. 15-16, 2022 Istanbul (Turkey)

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Cellular networks are a radio network with high capacity voice and data communication networks, are one of the most powerful engines in the telecommunications market and become the lifeline of communications. The radio access network uses radio signals to connect the cellular device of subscribers with the core network and give advanced features to subscribers, in order to offer subscribers a good quality of communication, it is necessary to assure the better functioning of the network taking into consideration several parameters which are variable and which must be permanently adapted to the radio link. that's why operators are trying to offer a better quality of service to avoid anomalies that could degrade the functioning of the network and therefore cause radio optimization problems. This paper aims to optimize the radio part of cellular networks, by creating a macro developed in Mapbasic to extract figures that represent the distribution of radio coverage and radio link quality in a geographical map in order to generate measurement reports after the analysis of the Drives test. The results of the work done in the mobile network for an integration of new site confirm the validation of our application.

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A novel model using Reo for IoT self-configuration systems

Cited by 8 publications

References 8 publications

A Modified Greedy Algorithm for Solving the Planification of eNodB Position in 5G network

A Modified Greedy Algorithm for Solving the Planification of eNodB Position in 5G network

Self-* Capabilities of Cloud-Edge Nodes: A Research Review

Automation of Radio Parameter Assessment by Developing a GIS Application for Radio Networks Optimization

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