An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks
We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength,...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/610652 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832552276624932864 |
|---|---|
| author | Ali Safa Sadiq Norsheila Binti Fisal Kayhan Zrar Ghafoor Jaime Lloret |
| author_facet | Ali Safa Sadiq Norsheila Binti Fisal Kayhan Zrar Ghafoor Jaime Lloret |
| author_sort | Ali Safa Sadiq |
| collection | DOAJ |
| description | We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches. |
| format | Article |
| id | doaj-art-1a99b81e422040acbded9e0be705d5ab |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-1a99b81e422040acbded9e0be705d5ab2025-02-03T05:59:03ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/610652610652An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless NetworksAli Safa Sadiq0Norsheila Binti Fisal1Kayhan Zrar Ghafoor2Jaime Lloret3Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, Gambang, 26300 Kuantan, Pahang, MalaysiaUTM MIMOS CoE in Telecommunication Technology, Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor Darul Takzim, MalaysiaFaculty of Engineering, Koya University, Danielle Mitterrand Boulevard, Koya, Kurdistan Region, IraqInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universidad Politécnica de Valencia, 46022 Valencia, SpainWe propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.http://dx.doi.org/10.1155/2014/610652 |
| spellingShingle | Ali Safa Sadiq Norsheila Binti Fisal Kayhan Zrar Ghafoor Jaime Lloret An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks The Scientific World Journal |
| title | An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks |
| title_full | An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks |
| title_fullStr | An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks |
| title_full_unstemmed | An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks |
| title_short | An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks |
| title_sort | adaptive handover prediction scheme for seamless mobility based wireless networks |
| url | http://dx.doi.org/10.1155/2014/610652 |
| work_keys_str_mv | AT alisafasadiq anadaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT norsheilabintifisal anadaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT kayhanzrarghafoor anadaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT jaimelloret anadaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT alisafasadiq adaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT norsheilabintifisal adaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT kayhanzrarghafoor adaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks AT jaimelloret adaptivehandoverpredictionschemeforseamlessmobilitybasedwirelessnetworks |