Adaptive Gene Level Mutation

Al-Afandi, Jalal; András, Horváth

doi:10.3390/a14010016

Cited by 4 publications

(4 citation statements)

References 31 publications

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“…The area covered by the wireless network is divided into appropriately small sub-areas called cells, within which mobile subscribers move. Each cell is equipped with a base station responsible for collecting and updating user data and intermediating the user's connection with a selected subscriber of the same network, another network, or a fixed-line network [4]. Dividing the area into cells allows you to reduce the power of transmitters and allows for multiple use of the same frequency range.…”

Section: Adaptive Antennas In Radio Communicationsmentioning

confidence: 99%

Adaptive Antenna Array Control Algorithm in Radiocommunication Systems

Wnuk

2024

Algorithms

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An important element of modern telecommunications is wireless radio networks, which enable mobile subscribers to access wireless networks. The cell area is divided into independent sectors served by directional antennas. As the number of mobile network subscribers served by a single base station increases, the problem of interference related to the operation of the radio link increases. To minimize the disadvantages of omnidirectional antennas, base stations use antennas with directional radiation characteristics. This solution allows you to optimize the operating conditions of the mobile network in terms of reducing the impact of interference, better managing the frequency spectrum and improving the energy efficiency of the system. The work presents an adaptive antenna algorithm used in mobile telephony. The principle of operation of adaptive systems, the properties of their elements and the configurations in which they are used in practice are described. On this basis, an algorithm for controlling the radiation characteristics of adaptive antennas is presented. The control is carried out using a microprocessor system. The simulation model is described. An algorithm was developed based on the Mathcad mathematical program, and the simulation results of this algorithm, i.e., changes in radiation characteristics as a result of changing the mobile position of subscribers, were presented in the form of selected radiation characteristics charts.

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Section: Adaptive Antennas In Radio Communicationsmentioning

confidence: 99%

Adaptive Antenna Array Control Algorithm in Radiocommunication Systems

Wnuk

2024

Algorithms

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“…If a microservice is not deployed on any edge server, the subsequent microservices of the service will also not be allocated resources from edge servers. The algorithm selects individuals from the population by an elitist strategy 40 and generates new individuals by a uniform crossover strategy 41 and simple mutation strategy 42 . If the fitness of the new individual is higher than that of its parents, the new individual will replace its parents.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…The algorithm selects individuals from the population by an elitist strategy 40 and generates new individuals by a uniform crossover strategy 41 and simple mutation strategy. 42 If the fitness of the new individual is higher than that of its parents, the new individual will replace its parents. The fitness is the overall performability in SRAP.…”

Section: Baselinementioning

confidence: 99%

PARA: Performability‐aware resource allocation on the edges for cloud‐native services

Guo

Liu

Xiao

et al. 2022

Int J of Intelligent Sys

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This paper explores resource allocation strategy in the Baidu Over The Edge system to enable mobile edge computing (MEC) datacenters to effectively support cloud-native services downstream to the network edge. There are many challenges to this issue. First, MEC datacenters are resourceconstrained to fully meet resource demands. Second, previous works regard the resource requirements of each service as an indivisible unit, resulting in idle MEC resources, even if the resources can meet the demands of some microservices decoupled by the service. Third, they are confined to optimize the allocation for a single slot, failing to adapt to the dynamic demands. To improve resource utilization, we propose performability-aware resource allocation (PARA), a PARA on the edges for cloud-native services. It takes microservices as the unit of resource allocation and allows services to perform with degraded services when only part of microservices' demands are met. It also considers dependency among microservices, dynamic resource requirements, and resource supply characteristics of MEC and cloud. Performability is a unified

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“…e mutation operator aims to maintain population diversity, which is critical to the algorithm's searching ability. is work selects the locus mutation operator [20], which judges whether a gene value should be flipped by generating a random number in [0, 1] and comparing it with the mutation probability. end while e gene values of each individual are initialized as 1 or 0, and then the population's solutions are evaluated.…”

Section: Mutationmentioning

confidence: 99%

Matching Cyber Security Ontologies through Genetic Algorithm-Based Ontology Alignment Technique

Lin

Haga²

2021

Security and Communication Networks

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Security ontology can be used to build a shared knowledge model for an application domain to overcome the data heterogeneity issue, but it suffers from its own heterogeneity issue. Finding identical entities in two ontologies, i.e., ontology alignment, is a solution. It is important to select an effective similarity measure (SM) to distinguish heterogeneous entities. However, due to the complex semantic relationships among concepts, no SM is ensured to be effective in all alignment tasks. The aggregation of SMs so that their advantages and disadvantages complement each other directly affects the quality of alignments. In this work, we formally define this problem, discuss its challenges, and present a problem-specific genetic algorithm (GA) to effectively address it. We experimentally test our approach on bibliographic tracks provided by OAEI and five pairs of security ontologies. The results show that GA can effectively address different heterogeneous ontology-alignment tasks and determine high-quality security ontology alignments.

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Adaptive Gene Level Mutation

Cited by 4 publications

References 31 publications

Adaptive Antenna Array Control Algorithm in Radiocommunication Systems

Adaptive Antenna Array Control Algorithm in Radiocommunication Systems

PARA: Performability‐aware resource allocation on the edges for cloud‐native services

Matching Cyber Security Ontologies through Genetic Algorithm-Based Ontology Alignment Technique

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