<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.4 20241031//EN"
        "https://jats.nlm.nih.gov/publishing/1.4/JATS-journalpublishing1-4.dtd">
<article  article-type="research-article"        dtd-version="1.4">
            <front>

                <journal-meta>
                                    <journal-id></journal-id>
            <journal-title-group>
                                                                                    <journal-title>Politeknik Dergisi</journal-title>
            </journal-title-group>
                                        <issn pub-type="epub">2147-9429</issn>
                                                                                            <publisher>
                    <publisher-name>Gazi University</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id pub-id-type="doi">10.2339/politeknik.635065</article-id>
                                                                <article-categories>
                                            <subj-group  xml:lang="en">
                                                            <subject>Engineering</subject>
                                                    </subj-group>
                                            <subj-group  xml:lang="tr">
                                                            <subject>Mühendislik</subject>
                                                    </subj-group>
                                    </article-categories>
                                                                                                                                                        <title-group>
                                                                                                                        <trans-title-group xml:lang="tr">
                                    <trans-title>Optimization of Ant Colony for Next Generation Wireless Cognitive Networks</trans-title>
                                </trans-title-group>
                                                                                                                                                                                                <article-title>Optimization of Ant Colony for Next Generation Wireless Cognitive Networks</article-title>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0001-9446-0988</contrib-id>
                                                                <name>
                                    <surname>Bayrakdar</surname>
                                    <given-names>Muhammed Enes</given-names>
                                </name>
                                                                    <aff>DUZCE UNIVERSITY</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-5798-3103</contrib-id>
                                                                <name>
                                    <surname>Çalhan</surname>
                                    <given-names>Ali</given-names>
                                </name>
                                                                    <aff>DUZCE UNIVERSITY</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20210901">
                    <day>09</day>
                    <month>01</month>
                    <year>2021</year>
                </pub-date>
                                        <volume>24</volume>
                                        <issue>3</issue>
                                        <fpage>779</fpage>
                                        <lpage>784</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20191020">
                        <day>10</day>
                        <month>20</month>
                        <year>2019</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20200506">
                        <day>05</day>
                        <month>06</month>
                        <year>2020</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 1998, Journal of Polytechnic</copyright-statement>
                    <copyright-year>1998</copyright-year>
                    <copyright-holder>Journal of Polytechnic</copyright-holder>
                </permissions>
            
                                                                                                <trans-abstract xml:lang="tr">
                            <p>In this work, spectrumhandoff process carried out by secondary users according to priority classes incognitive radio network is proposed. Network structure design of analytical andsimulation models is simulated with RIVERBED software. Moreover, deciding onthe most suitable spectrum handoff process is determined by using artificialintelligence techniques. Using multi parameter decision making processes is theobjective of our work. Optimization of the spectrum handoff number with thehelp of ant colony algorithm is the main goal of our work. By studying similaraspects of cognitive radio networks and ant colony algorithms, the number ofhandoff is reduced within the most appropriate scenario.</p></trans-abstract>
                                                                                                                                    <abstract><p>In this work, the spectrum handoff process carried out by secondary users according to priority classes in cognitive radio networks is proposed. The network structure design of analytical and simulation models is simulated with the RIVERBED software. Moreover, deciding on the most suitable spectrum handoff process is determined by using artificial intelligence techniques. Using multi-parameter decision-making processes is the objective of our work. Optimization of the spectrum handoff number with the help of an ant colony algorithm is the main goal of our work. By studying similar aspects of cognitive radio networks and ant colony algorithms, the number of handoffs is reduced within the most appropriate scenario.</p></abstract>
                                                            
            
                                                                                        <kwd-group>
                                                    <kwd>Ant colony</kwd>
                                                    <kwd>  Cognitive radio</kwd>
                                                    <kwd>  Handoff</kwd>
                                                    <kwd>  Optimization</kwd>
                                                    <kwd>  Spectrum management</kwd>
                                            </kwd-group>
                            
                                                <kwd-group xml:lang="tr">
                                                    <kwd>Ant colony</kwd>
                                                    <kwd>  Cognitive radio</kwd>
                                                    <kwd>  Handoff</kwd>
                                                    <kwd>  Optimization</kwd>
                                                    <kwd>  Spectrum management</kwd>
                                            </kwd-group>
                                                                                                                                    <funding-group specific-use="FundRef">
                    <award-group>
                                                    <funding-source>
                                <named-content content-type="funder_name">Düzce Üniversitesi</named-content>
                            </funding-source>
                                                                            <award-id>2018.07.02.732</award-id>
                                            </award-group>
                </funding-group>
                                </article-meta>
    </front>
    <back>
                            <ref-list>
                                    <ref id="ref1">
                        <label>1</label>
                        <mixed-citation publication-type="journal">1.	Andreotti, R, Stupia, I, Giannetti, F, Lottici, V, Vandendorpe, L. Resource Allocation in OFDMA Underlay Cognitive Radio Systems based on Ant Colony Optimization, IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, Marrakech, Morocco, 2010, pp 1-5.</mixed-citation>
                    </ref>
                                    <ref id="ref2">
                        <label>2</label>
                        <mixed-citation publication-type="journal">2.	Bayrakdar, ME, Atmaca, S, Karahan, A. A Slotted Aloha based Random Access Cognitive Radio Network and its Performance Evaluation, International Conference on Software, Telecommunications and Computer Networks, Split, Croatia, 2012, pp 1-5.</mixed-citation>
                    </ref>
                                    <ref id="ref3">
                        <label>3</label>
                        <mixed-citation publication-type="journal">3.	Bayrakdar, ME, Calhan, A. Fuzzy Logic based Channel Selection for Mobile Secondary Users in Cognitive Radio Networks, Signal Processing and Communications Applications Conference, Malatya, Turkey, 2015, pp 331-334.</mixed-citation>
                    </ref>
                                    <ref id="ref4">
                        <label>4</label>
                        <mixed-citation publication-type="journal">4.	Bayrakdar, ME, Calhan, A. Optimization of Spectrum Handoff with Artificial Bee Colony Algorithm, Signal Processing and Communications Applications Conference, Antalya, Turkey, 2017, pp 1-4.</mixed-citation>
                    </ref>
                                    <ref id="ref5">
                        <label>5</label>
                        <mixed-citation publication-type="journal">5.	Cheng, X,  Jiang, M. Cognitive Radio Spectrum Assignment based on Artificial Bee Colony Algorithm, IEEE 13th International Conference on Communication Technology, Jinan, China, 2011, pp 161-164.</mixed-citation>
                    </ref>
                                    <ref id="ref6">
                        <label>6</label>
                        <mixed-citation publication-type="journal">6.	Coutinho, PS, Rocha Silva, MW, Rezende, JF. Detection Error Aware Spectrum Handoff Mechanism for Cognitive Radios, International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, Stockholm, Sweden, 2012, pp 48-53.</mixed-citation>
                    </ref>
                                    <ref id="ref7">
                        <label>7</label>
                        <mixed-citation publication-type="journal">7.	Feng, W, Cao, J, Zhang, C, Liu, C. Joint Optimization of Spectrum Handoff Scheduling and Routing in Multi-hop Multi-radio Cognitive Networks, IEEE International Conference on Distributed Computing Systems, Montreal, QC, Canada, 2009, pp 85-92.</mixed-citation>
                    </ref>
                                    <ref id="ref8">
                        <label>8</label>
                        <mixed-citation publication-type="journal">8.	Ghasemi, A, Jahromi, AF, Masnadi Shirazi MA, Biguesh, M, Ghasemi, F. Spectrum Allocation based on Artificial Bee Colony in Cognitive Radio Networks, 6th International Symposium on Telecommunications, Tehran, Iran, 2012, pp 182-187.</mixed-citation>
                    </ref>
                                    <ref id="ref9">
                        <label>9</label>
                        <mixed-citation publication-type="journal">9.	He, A, Bae, KK, Newman, TR, Gaeddert, J, Kim, K, Menon, R, Morales Tirado, L, Neel, JJ, Zhao Y, Reed, JH, Tranter, WH. 2010. A survey of artificial intelligence for cognitive radios. IEEE Transactions on Vehicular Technology; 59 (4): 1578-1592.</mixed-citation>
                    </ref>
                                    <ref id="ref10">
                        <label>10</label>
                        <mixed-citation publication-type="journal">10.	He, Q, Feng, Z, Wang, Y, Zhang, P. Cross-Layer Parameters Reconfiguration in Cognitive Radio Networks using Ant Colony Optimization, IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications, Sydney, NSW, Australia, 2012, pp 631-635.</mixed-citation>
                    </ref>
                                    <ref id="ref11">
                        <label>11</label>
                        <mixed-citation publication-type="journal">11.	He, Q, Zhang P. Dynamic Channel Assignment using Ant Colony Optimization for Cognitive Radio Networks, IEEE Vehicular Technology Conference, Quebec City, QC, Canada, 2012, pp 1-5.</mixed-citation>
                    </ref>
                                    <ref id="ref12">
                        <label>12</label>
                        <mixed-citation publication-type="journal">12.	Pradhan, PM. Design of Cognitive Radio Engine using Artificial Bee Colony Algorithm, International Conference on Energy, Automation, and Signal, Bhubaneswar, Odisha, India, 2011, pp 1-4.</mixed-citation>
                    </ref>
                                    <ref id="ref13">
                        <label>13</label>
                        <mixed-citation publication-type="journal">13.	Qiao, X, Tan Z, Li, J. Combined Optimization of Spectrum Handoff and Spectrum Sensing for Cognitive Radio Systems, International Conference on Wireless Communications, Networking and Mobile Computing, Wuhan, China, 2011, pp 1-4.</mixed-citation>
                    </ref>
                                    <ref id="ref14">
                        <label>14</label>
                        <mixed-citation publication-type="journal">14.	Raiyn, J. Developing Cognitive Radio Approach based on Dynamic SNR to Reduce Handoff Latency in Cellular Systems, International Symposium on Performance Evaluation of Computer &amp; Telecommunication Systems, Istanbul, Turkey, 2009, pp 231- 237.</mixed-citation>
                    </ref>
                                    <ref id="ref15">
                        <label>15</label>
                        <mixed-citation publication-type="journal">15.	Sheikholeslami, F, Nasiri Kenari, M, Ashtiani, F. 2015. Optimal probabilistic initial and target channel selection for spectrum handoff in cognitive radio networks. IEEE Transactions on Wireless Communications; 14(1): 570-584.</mixed-citation>
                    </ref>
                                    <ref id="ref16">
                        <label>16</label>
                        <mixed-citation publication-type="journal">16.	Soleimani, MT, Kahvand, M, Sarikhani, R. Handoff Reduction based on Prediction Approach in Cognitive Radio Networks, IEEE International Conference on Communication Technology, Guilin, China, 2013, pp 319-323.</mixed-citation>
                    </ref>
                                    <ref id="ref17">
                        <label>17</label>
                        <mixed-citation publication-type="journal">17.	Song, X. Utilization and Fairness in Spectrum Assignment for Cognitive Radio Networks: An Ant Colony Optimization&#039;s Perspective, International Conference on Wireless Communication and Sensor Network, Wuhan, China, 2014, pp 42-45.</mixed-citation>
                    </ref>
                                    <ref id="ref18">
                        <label>18</label>
                        <mixed-citation publication-type="journal">18.	Zhu, Z, Chen, J, Zhang, S. Spectrum Allocation Algorithm Based on Improved Ant Colony in Cognitive Radio Networks, IEEE International Conference on Internet of Things and IEEE Green Computing and Communications and IEEE Cyber, Physical and Social Computing and IEEE Smart Data, Chengdu, China, 2016, pp 376-379.</mixed-citation>
                    </ref>
                                    <ref id="ref19">
                        <label>19</label>
                        <mixed-citation publication-type="journal">19.	Riverbed Modeler, https://www.riverbed.com/gb/, March 2019.</mixed-citation>
                    </ref>
                                    <ref id="ref20">
                        <label>20</label>
                        <mixed-citation publication-type="journal">20.	Matlab, https://www.mathworks.com/products/matlab.html, March 2019.</mixed-citation>
                    </ref>
                            </ref-list>
                    </back>
    </article>
