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9th International Conference on Cognitive Radio Oriented Wireless Networks

Research Article

Algorithms for Opportunistic Load Balancing Cognitive Engine

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2014.255392,
        author={Marko M\aa{}kel\aa{}inen and Zaheer Khan and Tuomo H\aa{}nninen and Harri Saarnisaari},
        title={Algorithms for Opportunistic Load Balancing Cognitive Engine},
        proceedings={9th International Conference on Cognitive Radio Oriented Wireless Networks},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2014},
        month={7},
        keywords={cognitive engine load balancing algorithms},
        doi={10.4108/icst.crowncom.2014.255392}
    }
    
  • Marko Mäkeläinen
    Zaheer Khan
    Tuomo Hänninen
    Harri Saarnisaari
    Year: 2014
    Algorithms for Opportunistic Load Balancing Cognitive Engine
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2014.255392
Marko Mäkeläinen,*, Zaheer Khan1, Tuomo Hänninen1, Harri Saarnisaari1
  • 1: Centre for Wireless Communications
*Contact email: markomak@ee.oulu.fi

Abstract

This paper presents a cognitive engine (CE) that intelligently and dynamically allocates spectrum resources to users in the following two cases: 1) a scenario where a network has an exclusive access to a spectrum band; and 2) a spectrum sharing scenario where along with the exclusive utilization to its own spectrum band a network also can opportunistically utilize shared spectrum band as a second user. Moreover, the implemented CE performs two main tasks: 1) Accepts or rejects arrival user requests based on a priority based algorithm; and 2) It intelligently load balances the user traffic between the two available network resources, while taking into account the primary user activity in the shared spectrum band. We evaluate performance of the proposed algorithms under different primary and secondary user traffic scenarios. We show that the proposed load balancing algorithm increases average throughput of the network and it also reduces the average number of users rejected by the network.

Keywords
cognitive engine load balancing algorithms
Published
2014-07-23
Publisher
IEEE
http://dx.doi.org/10.4108/icst.crowncom.2014.255392
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