Cognitive Network Framework for Heterogeneous Wireless Networks

Al-Saadi, Ahmed; Setchi, Rossitza; Hicks, Yulia

doi:10.1016/j.procs.2015.08.121

Cited by 7 publications

(3 citation statements)

References 22 publications

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“…al. [11] has worked on the Routing Protocol for Heterogeneous Wireless Mesh Networks. This paper proposes a heterogeneous metropolitan area network architecture that combines an IEEE 802.11 wireless mesh network (WMN) with a long-term evolution (LTE) network.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Routing with Segmental Routing Mechanism for Wireless Mesh Network (WMN)

2019

IJITEE

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The wireless mesh networks (WMN) are the growing mediums of connectivity for the purpose of internet or intranet connectivity. The routing among the WMN becomes a challenging task with the rise in the number of nodes across the network and the larger data volumes. In this paper, the work has been carried out on the growing WMNs with the dynamic number of nodes. The node availability aware neighbor formation and status tracking mechanism has been applied in this scheme in order to keep the network updated about the working nodes and to eliminate the non-functional nodes from the connected mesh network. The neighbor query process is utilized for the path building towards the base stations (BTS) or Sink node in the given WMN networks. Additionally; the routing information is collected from all of the neighboring nodes towards the destination paths using the desired mechanism for the path discovery under the segmental routing mechanism for WMN, which has been created with the capability of handling the network path failures dynamically in the local domain of the given network zone. The performance of the proposed model has been analyzed in the form of energy consumption, end-to-end delay and detailed energy & packet based analysis

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Section: Literature Reviewmentioning

confidence: 99%

Smart Routing with Segmental Routing Mechanism for Wireless Mesh Network (WMN)

2019

IJITEE

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“…al. [8] worked towards the development of routing among the heterogeneous wireless networks. In this paper, the author has discussed the situation of Metropolitian networks, and works on the wireless standard IEEE 802.11.…”

Section: Literatre Reviewmentioning

confidence: 99%

A Review: Fuzzy Logic Controller (Flc) in Wireless Sensor Networks (Wsn)

Verma

Singh²

2018

ijarcs

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“…The semantic system consists of a semantic knowledge base and a semantic inference engine. The semantic knowledge base is based on the recently proposed ontology of heterogeneous networks [38] and a rule base. The novel semantic inference engine utilizes fuzzy logic to create instances of the ontology in the knowledge base that represent the QoS parameters of each RAN.…”

Section: Semantic Systemmentioning

confidence: 99%

Semantic Reasoning in Cognitive Networks for Heterogeneous Wireless Mesh Systems

Al-Saadi

Setchi

Hicks

2017

IEEE Trans. Cogn. Commun. Netw.

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The next generation of wireless networks is expected to provide not only higher bandwidths anywhere and at any time but also ubiquitous communication using different network types. However, several important issues including routing, selfconfiguration, device management, and context awareness have to be considered before this vision becomes reality. This paper proposes a novel cognitive network framework for heterogeneous wireless mesh systems to abstract the network control system from the infrastructure by introducing a layer that separates the management of different radio access networks from the data transmission. This approach simplifies the process of managing and optimizing the networks by using extendable smart middleware that automatically manages, configures, and optimizes the network performance. The proposed cognitive network framework, called FuzzOnto, is based on a novel approach that employs ontologies and fuzzy reasoning to facilitate the dynamic addition of new network types to the heterogeneous network. The novelty is in using semantic reasoning with cross-layer parameters from heterogeneous network architectures to manage and optimize the performance of the networks. The concept is demonstrated through the use of three network architectures: 1) wireless mesh network; 2) long-term evolution (LTE) cellular network; and 3) vehicular ad hoc network (VANET). These networks utilize nonoverlapped frequency bands and can operate simultaneously with no interference. The proposed heterogeneous network was evaluated using ns-3 network simulation software. The simulation results were compared with those produced by other networks that utilize multiple transmission devices. The results showed that the heterogeneous network outperformed the benchmark networks in both urban and VANET scenarios by up to 70% of the network throughput, even when the LTE network utilized a high bandwidth.

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Cognitive Network Framework for Heterogeneous Wireless Networks

Cited by 7 publications

References 22 publications

Smart Routing with Segmental Routing Mechanism for Wireless Mesh Network (WMN)

Smart Routing with Segmental Routing Mechanism for Wireless Mesh Network (WMN)

A Review: Fuzzy Logic Controller (Flc) in Wireless Sensor Networks (Wsn)

Semantic Reasoning in Cognitive Networks for Heterogeneous Wireless Mesh Systems

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