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Journal Articles Journal of Ambient Intelligence and Humanized Computing Year : 2018

Cluster-based Scheduling for Cognitive Radio Sensor Networks

Abstract

In this paper, we define a cluster based scheduling algorithm for Cognitive Radio Sensor Networks (CRSNs). To avoid inter-clusters collision, we assign fixed channels only to nodes having one-hop neighbors out of their clusters. We denote these nodes as specific nodes. Previous studies assign distinct channels to whole neighbor clusters to avoid inter-clusters collision. Our objective is to optimize the spatial reuse and to increase the network throughput while saving sensors energy. We start by assigning channels only to the specific nodes. Once the problem of inter-clusters collision is solved, each cluster head (CH) schedules the transmissions in its cluster independently. For the cluster members that are specific nodes, the CH assigns only time slots because the channel assignment is already done. For other cluster members (CMs) (not specific nodes), the CH assigns the pair (channel, slot). Two solutions are proposed in this paper to schedule the CMs: The Frame Intra Cluster Multichannel Scheduling algorithm denoted Frame-ICMS and the Slot Intra Cluster Multichannel Scheduling algorithm denoted Slot-ICMS. We evaluate the performance of these algorithms in case of accurate PUs activity detection and in case of bad PUs activity estimation. We prove that our proposals outperform an existing one especially in terms of energy saving.
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Dates and versions

hal-01870909 , version 1 (10-09-2018)

Identifiers

  • HAL Id : hal-01870909 , version 1

Cite

Hanen Idoudi, Ons Mabrouk, Pascale Minet, Leila Azouz Saidane. Cluster-based Scheduling for Cognitive Radio Sensor Networks. Journal of Ambient Intelligence and Humanized Computing, 2018. ⟨hal-01870909⟩

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