FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285125975> ?p ?o ?g. }

• W4285125975 endingPage "13" @default.
• W4285125975 startingPage "1" @default.
• W4285125975 abstract "The exponential demand for multimedia services is one reason behind the substantial growth of mobile data traffic. Video traffic patterns have significantly changed in the past two years due to the coronavirus disease (COVID-19). The worldwide pandemic has caused many individuals to work from home and use various online video platforms (e.g., Zoom, Google Meet, and Microsoft Teams). As a result, overloaded macrocells are unable to ensure high Quality of Experience (QoE) to all users. Heterogeneous Networks (HetNets) consisting of small cells (femtocells) and macrocells are a promising solution to mitigate this problem. A critical challenge with the deployment of femtocells in HetNets is the interference management between Macro Base Stations (MBSs), Femto Base Stations (FBSs), and between FBS and FBS. Indeed, the dynamic deployment of femtocells can lead to co-tier interference. With the rolling out of the 5G mobile network, it becomes imperative for mobile operators to maintain network capacity and manage different types of interference. Machine Learning (ML) is considered a promising solution to many challenges in 5G HetNets. In this paper, we propose a Machine Learning Interference Classification and Offloading Scheme (MLICOS) to address the problem of co-tier interference between femtocells for video delivery. Two versions of MLICOS, namely, MLICOS1 and MLICOS2, are proposed. The former uses conventional ML classifiers while the latter employs advanced ML algorithms. Both versions of MLICOS are compared with the classic Proportional Fair (PF) scheduling algorithm, Variable Radius and Proportional Fair scheduling (VR+PF) algorithm, and a Cognitive Approach (CA). The ML models are assessed based on the prediction accuracy, precision, recall and F-measure. Simulation results show that MLICOS outperforms the other schemes by providing the highest throughput and the lowest delay and packet loss ratio. A statistical analysis was also carried out to depict the degree of interference faced by users when different schemes are employed." @default.
• W4285125975 created "2022-07-14" @default.
• W4285125975 creator A5045501875 @default.
• W4285125975 creator A5050234051 @default.
• W4285125975 creator A5066166445 @default.
• W4285125975 date "2022-01-01" @default.
• W4285125975 modified "2023-10-14" @default.
• W4285125975 title "A Machine Learning Solution for Video Delivery to Mitigate Co-Tier Interference in 5G HetNets" @default.
• W4285125975 doi "https://doi.org/10.1109/tmm.2022.3187607" @default.
• W4285125975 hasPublicationYear "2022" @default.
• W4285125975 type Work @default.
• W4285125975 citedByCount "0" @default.
• W4285125975 crossrefType "journal-article" @default.
• W4285125975 hasAuthorship W4285125975A5045501875 @default.
• W4285125975 hasAuthorship W4285125975A5050234051 @default.
• W4285125975 hasAuthorship W4285125975A5066166445 @default.
• W4285125975 hasBestOaLocation W42851259751 @default.
• W4285125975 hasConcept C108037233 @default.
• W4285125975 hasConcept C120314980 @default.
• W4285125975 hasConcept C127413603 @default.
• W4285125975 hasConcept C152504517 @default.
• W4285125975 hasConcept C153646914 @default.
• W4285125975 hasConcept C158207573 @default.
• W4285125975 hasConcept C206729178 @default.
• W4285125975 hasConcept C21547014 @default.
• W4285125975 hasConcept C2777118422 @default.
• W4285125975 hasConcept C31258907 @default.
• W4285125975 hasConcept C41008148 @default.
• W4285125975 hasConcept C555944384 @default.
• W4285125975 hasConcept C68649174 @default.
• W4285125975 hasConcept C76155785 @default.
• W4285125975 hasConceptScore W4285125975C108037233 @default.
• W4285125975 hasConceptScore W4285125975C120314980 @default.
• W4285125975 hasConceptScore W4285125975C127413603 @default.
• W4285125975 hasConceptScore W4285125975C152504517 @default.
• W4285125975 hasConceptScore W4285125975C153646914 @default.
• W4285125975 hasConceptScore W4285125975C158207573 @default.
• W4285125975 hasConceptScore W4285125975C206729178 @default.
• W4285125975 hasConceptScore W4285125975C21547014 @default.
• W4285125975 hasConceptScore W4285125975C2777118422 @default.
• W4285125975 hasConceptScore W4285125975C31258907 @default.
• W4285125975 hasConceptScore W4285125975C41008148 @default.
• W4285125975 hasConceptScore W4285125975C555944384 @default.
• W4285125975 hasConceptScore W4285125975C68649174 @default.
• W4285125975 hasConceptScore W4285125975C76155785 @default.
• W4285125975 hasLocation W42851259751 @default.
• W4285125975 hasOpenAccess W4285125975 @default.
• W4285125975 hasPrimaryLocation W42851259751 @default.
• W4285125975 hasRelatedWork W1990678570 @default.
• W4285125975 hasRelatedWork W2022479666 @default.
• W4285125975 hasRelatedWork W2031992841 @default.
• W4285125975 hasRelatedWork W2042799635 @default.
• W4285125975 hasRelatedWork W2111559726 @default.
• W4285125975 hasRelatedWork W2112481076 @default.
• W4285125975 hasRelatedWork W2132485550 @default.
• W4285125975 hasRelatedWork W2805967187 @default.
• W4285125975 hasRelatedWork W3195379373 @default.
• W4285125975 hasRelatedWork W867969198 @default.
• W4285125975 isParatext "false" @default.
• W4285125975 isRetracted "false" @default.
• W4285125975 workType "article" @default.