Matches in SemOpenAlex for { <https://semopenalex.org/work/W4295116521> ?p ?o ?g. }
Showing items 1 to 67 of
67
with 100 items per page.
- W4295116521 abstract "In this work, we develop a framework that jointly decides on the optimal location of wireless extenders and the channel configuration of extenders and access points (APs) in a Wireless Mesh Network (WMN). Typically, the rule-based approaches in the literature result in limited exploration while reinforcement learning based approaches result in slow convergence. Therefore, Artificial Intelligence (AI) is adopted to support network autonomy and to capture insights on system and environment evolution. We propose a Self-X (self-optimizing and self-learning) framework that encapsulates both environment and intelligent agent to reach optimal operation through sensing, perception, reasoning and learning in a truly autonomous fashion. The agent derives adequate knowledge from previous actions improving the quality of future decisions. Domain experience was provided to guide the agent while exploring and exploiting the set of possible actions in the environment. Thus, it guarantees a low-cost learning and achieves a near-optimal network configuration addressing the non-deterministic polynomial-time hardness (NP-hard) problem of joint channel assignment and location optimization in WMNs. Extensive simulations are run to validate its fast convergence, high throughput and resilience to dynamic interference conditions. We deploy the framework on off-the-shelf wireless devices to enable autonomous self-optimization and self-deployment, using APs and wireless extenders." @default.
- W4295116521 created "2022-09-10" @default.
- W4295116521 creator A5026448728 @default.
- W4295116521 creator A5046376290 @default.
- W4295116521 creator A5057362333 @default.
- W4295116521 creator A5075029993 @default.
- W4295116521 date "2018-05-16" @default.
- W4295116521 modified "2023-09-25" @default.
- W4295116521 title "Self-X Design of Wireless Networks: Exploiting Artificial Intelligence and Guided Learning" @default.
- W4295116521 doi "https://doi.org/10.48550/arxiv.1805.06247" @default.
- W4295116521 hasPublicationYear "2018" @default.
- W4295116521 type Work @default.
- W4295116521 citedByCount "0" @default.
- W4295116521 crossrefType "posted-content" @default.
- W4295116521 hasAuthorship W4295116521A5026448728 @default.
- W4295116521 hasAuthorship W4295116521A5046376290 @default.
- W4295116521 hasAuthorship W4295116521A5057362333 @default.
- W4295116521 hasAuthorship W4295116521A5075029993 @default.
- W4295116521 hasBestOaLocation W42951165211 @default.
- W4295116521 hasConcept C105339364 @default.
- W4295116521 hasConcept C108037233 @default.
- W4295116521 hasConcept C111919701 @default.
- W4295116521 hasConcept C120314980 @default.
- W4295116521 hasConcept C154945302 @default.
- W4295116521 hasConcept C157764524 @default.
- W4295116521 hasConcept C162324750 @default.
- W4295116521 hasConcept C177264268 @default.
- W4295116521 hasConcept C199360897 @default.
- W4295116521 hasConcept C2777303404 @default.
- W4295116521 hasConcept C31258907 @default.
- W4295116521 hasConcept C41008148 @default.
- W4295116521 hasConcept C50522688 @default.
- W4295116521 hasConcept C555944384 @default.
- W4295116521 hasConcept C76155785 @default.
- W4295116521 hasConcept C97541855 @default.
- W4295116521 hasConceptScore W4295116521C105339364 @default.
- W4295116521 hasConceptScore W4295116521C108037233 @default.
- W4295116521 hasConceptScore W4295116521C111919701 @default.
- W4295116521 hasConceptScore W4295116521C120314980 @default.
- W4295116521 hasConceptScore W4295116521C154945302 @default.
- W4295116521 hasConceptScore W4295116521C157764524 @default.
- W4295116521 hasConceptScore W4295116521C162324750 @default.
- W4295116521 hasConceptScore W4295116521C177264268 @default.
- W4295116521 hasConceptScore W4295116521C199360897 @default.
- W4295116521 hasConceptScore W4295116521C2777303404 @default.
- W4295116521 hasConceptScore W4295116521C31258907 @default.
- W4295116521 hasConceptScore W4295116521C41008148 @default.
- W4295116521 hasConceptScore W4295116521C50522688 @default.
- W4295116521 hasConceptScore W4295116521C555944384 @default.
- W4295116521 hasConceptScore W4295116521C76155785 @default.
- W4295116521 hasConceptScore W4295116521C97541855 @default.
- W4295116521 hasLocation W42951165211 @default.
- W4295116521 hasOpenAccess W4295116521 @default.
- W4295116521 hasPrimaryLocation W42951165211 @default.
- W4295116521 hasRelatedWork W2098887866 @default.
- W4295116521 hasRelatedWork W2102630975 @default.
- W4295116521 hasRelatedWork W2147978005 @default.
- W4295116521 hasRelatedWork W2512844215 @default.
- W4295116521 hasRelatedWork W2607247987 @default.
- W4295116521 hasRelatedWork W260766989 @default.
- W4295116521 hasRelatedWork W2971048123 @default.
- W4295116521 hasRelatedWork W3113137637 @default.
- W4295116521 hasRelatedWork W3126373388 @default.
- W4295116521 hasRelatedWork W2185483493 @default.
- W4295116521 isParatext "false" @default.
- W4295116521 isRetracted "false" @default.
- W4295116521 workType "article" @default.