On-Demand Hybrid Routing for Cognitive Radio Ad-Hoc Network

Zareei, Mahdi; Mohamed, Ehab Mahmoud; Anisi, Mohammad Hossein; Vargas-Rosales, César; Tsukamoto, Kazuya; Khan, Muhammad Khurram

doi:10.1109/access.2016.2626721

Cited by 36 publications

(30 citation statements)

References 19 publications

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“…Routing in CRAHN varies from routing in out-dated ad hoc systems as it has to familiarize to active variations of band because of stochastic performance of PU and SU. Furthermore, routing procedures in CRAHN must contract with heterogeneity of sources (accessible networks and accessible dynamism) [5].…”

Section: Cognitive Radio Ad-hoc Network (Crahn)mentioning

confidence: 99%

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Multi-Population Firefly Algorithm (Mfa) for Relay Assisted Efficient Routing in Cognitive Radio Ad-Hoc Networks (Crahn)

2020

jcr

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The existing routing techniques in Cognitive Radio ad-hoc networks (CRAHN) do not consider the delay, energy consumption, interference, traffic load parameters and success rate of data delivery. In order to solve these problems, in this paper, we propose to design a relay assisted cost effective routing protocol for CRAHNS. In this routing protocol, some of the secondary users are designated as relay nodes along the route towards the destination. Multi-population Firefly Algorithm (MFA) is used to establish the routing path based on the Interference to PUs, Number of Hops and Average current traffic load, Packet reception ratio and Average residual energy metrics. By simulation results, we show that the proposed technique improves the data delivery rate and reduces the energy consumption.

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Section: Cognitive Radio Ad-hoc Network (Crahn)mentioning

confidence: 99%

“…Mahdi Zareei et al [5] have suggested a new on-demand clusterbased fusion routing procedure for cognitive radio ad hoc network with uneven nodule circulation. Initially, a new spectrum-aware grouping device is familiarized.…”

Section: Related Workmentioning

confidence: 99%

Multi-Population Firefly Algorithm (Mfa) for Relay Assisted Efficient Routing in Cognitive Radio Ad-Hoc Networks (Crahn)

2020

jcr

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“…The criterion used in [28] is a combination of the link delay, link data rate, and hop count of the route. In this criterion, the link delay is obtained from the sum of the transmission delay, back-off delay, queuing delay, and switching delay, and the link data rate is specified based on the activity of PU senders.…”

Section: Multimetric-based Routing Criteria (Combined Routing Critementioning

confidence: 99%

Design of optimum criterion for opportunistic multi-hop routing in cognitive radio networks

2018

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The instability of operational channels on cognitive radio networks (CRNs), which is due to the stochastic behavior of primary users (PUs), has increased the complexity of the design of the optimal routing criterion (ORC) in CRNs. The exploitation of available opportunities in CRNs, such as the channel diversity, as well as alternative routes provided by the intermediate nodes belonging to routes (internal backup routes) in the route‐cost (or weight) determination, complicate the ORC design. In this paper, to cover the channel diversity, the CRN is modeled as a multigraph in which the weight of each edge is determined according to the behavior of PU senders and the protection of PU receivers. Then, an ORC for CRNs, which is referred to as the stability probability of communication between the source node and the destination node (SPC_SD), is proposed. SPC_SD, which is based on the obtained model, internal backup routes, and probability theory, calculates the precise probability of communication stability between the source and destination. The performance evaluation is conducted using simulations, and the results show that the end‐to‐end performance improved significantly.

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“…Good amount of research can be found in [15], [33]. By applying different metrics in routing several approaches are proposed [8], [23], [33]- [42]. Therefore routing on demand opportunistically comes under two categories:…”

Section: Related Workmentioning

confidence: 99%

“…The Federal communications commission has mentioned that most of the spectrum is static allocated in certain geographical regions and hence large portions of the spectrum are underutilized [4]. To have an efficient usage of spectrum cognitive radio has been introduced [5]- [8]. In cognitive radio networks (CRNs) primary users and secondary users coexist to transfer their data.…”

Section: Introductionmentioning

confidence: 99%

Quality and Availability of spectrum based routing for Cognitive radio enabled IoT networks

Kaushik

Yoganandam

Sahoo

2018

JCOMSS

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Abstract-With the recent emergence and its wide spread applicability Internet of Things (IoT) is placing pressure on network resources and most importantly on availability of spectrum. Spectrum scarcity is the issue to be addressed in networking within IoT. Cognitive radio is the technology which addresses the problem of spectrum scarcity in an efficient way. Equipping the IoT devices with cognitive radio capability will lead to a new dimension called cognitive radio enabled IoT devices. To achieve ON-demand IoT solutions and interference free communications cognitive radio enabled IoT devices will become an effective platform for many applications. As there is high dynamicity in availability of spectrum it is challenging for designing an efficient routing protocol for secondary users in cognitive device networks. In this work we are going to estimate spectrum quality and spectrum availability based on two parameters called global information about spectrum usage and instant spectrum status information. Enhanced energy detector is used at each and every node for better probability of detection. For estimating spectrum quality and availability we are introducing novel routing metrics. To have restriction on the number of rerouting and to increase the performance of routing in our proposed routing metric only one retransmission is allowed. Then, two algorithms for routing are designed for evaluating the performance of routing and we find that the bit error rates of proposed algorithms (nodes are dynamic) have decreased a lot when compared to conventional methods (nodes are static) and throughput of proposed algorithm also improved a lot.

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On-Demand Hybrid Routing for Cognitive Radio Ad-Hoc Network

Cited by 36 publications

References 19 publications

Multi-Population Firefly Algorithm (Mfa) for Relay Assisted Efficient Routing in Cognitive Radio Ad-Hoc Networks (Crahn)

Multi-Population Firefly Algorithm (Mfa) for Relay Assisted Efficient Routing in Cognitive Radio Ad-Hoc Networks (Crahn)

Design of optimum criterion for opportunistic multi-hop routing in cognitive radio networks

Quality and Availability of spectrum based routing for Cognitive radio enabled IoT networks

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