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, 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

WLAN Cell Handoff Latency Abatement Using an FPGA Fuzzy Logic Algorithm Implementation

Following the path toward 4 G set by its wireless siblings LTE and WiMax, IEEE 802.11 technology, universally known as WiFi, is evolving to become a high data rate QoS-enabled mobile platform. The IEEE 802.11n standard yields data rates up to 450 Mbp s and the 802.11e standard ensures proficient QoS for real-time applications. Still in need of better performance, multicell environments that provide extended coverage allow the mobile station nomadic passage beyond a single cell by means of cell dissociation-association process known as handoff. This process poses a challenge for real-time applications like voice over IP (150 ms maximum delay) and video (200–400 ms) sessions, to give the user a seamless cell-crossing without data loss or session breakage. It presented an approach of a predictive fuzzy Logic controller to reduce the channel scanning process to a tenth of the standard time, and its efficient FPGA implementation to speed up the processing time. The algorithm of the fuzzy controller was implemented in C language. Experimental results are provided

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, 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.Sadiq, AS.; Fisal, NB.; Ghafoor, KZ.; Lloret, J. (2014). An adaptive handover prediction scheme for seamless mobility based wireless networks. Scientific World Journal. 2014. doi:10.1155/2014/610652S2014You, I., Han, Y.-H., Chen, Y.-S., & Chao, H.-C. (2011). Next generation mobility management. Wireless Communications and Mobile Computing, 11(4), 443-445. doi:10.1002/wcm.1136Sepúlveda, R., Montiel-Ross, O., Quiñones-Rivera, J., & Quiroz, E. E. (2012). WLAN Cell Handoff Latency Abatement Using an FPGA Fuzzy Logic Algorithm Implementation. Advances in Fuzzy Systems, 2012, 1-10. doi:10.1155/2012/219602Song, W. (2012). Resource reservation for mobile hotspots in vehicular environments with cellular/WLAN interworking. EURASIP Journal on Wireless Communications and Networking, 2012(1). doi:10.1186/1687-1499-2012-18Sadiq, A. S., Bakar, K. A., Ghafoor, K. Z., Lloret, J., & Khokhar, R. (2013). An Intelligent Vertical Handover Scheme for Audio and Video Streaming in Heterogeneous Vehicular Networks. Mobile Networks and Applications, 18(6), 879-895. doi:10.1007/s11036-013-0465-8Nahrstedt, K. (2011). Quality of Service in Wireless Networks Over Unlicensed Spectrum. Synthesis Lectures on Mobile and Pervasive Computing, 6(1), 1-176. doi:10.2200/s00383ed1v01y201109mpc008Magagula, L. A., Chan, H. A., & Falowo, O. E. (2011). Handover approaches for seamless mobility management in next generation wireless networks. Wireless Communications and Mobile Computing, 12(16), 1414-1428. doi:10.1002/wcm.1074Sadiq, A. S., Bakar, K. A., Ghafoor, K. Z., Lloret, J., & Mirjalili, S. (2012). A smart handover prediction system based on curve fitting model for Fast Mobile IPv6 in wireless networks. International Journal of Communication Systems, 27(7), 969-990. doi:10.1002/dac.2386Çeken, C., Yarkan, S., & Arslan, H. (2010). Interference aware vertical handoff decision algorithm for quality of service support in wireless heterogeneous networks. Computer Networks, 54(5), 726-740. doi:10.1016/j.comnet.2009.09.018Dutta, A., Das, S., Famolari, D., Ohba, Y., Taniuchi, K., Fajardo, V., … Schulzrinne, H. (2007). Seamless proactive handover across heterogeneous access networks. Wireless Personal Communications, 43(3), 837-855. doi:10.1007/s11277-007-9266-3Xu, C., Teng, J., & Jia, W. (2010). Enabling faster and smoother handoffs in AP-dense 802.11 wireless networks. Computer Communications, 33(15), 1795-1803. doi:10.1016/j.comcom.2010.04.044Holis, J., & Pechac, P. (2008). Elevation Dependent Shadowing Model for Mobile Communications via High Altitude Platforms in Built-Up Areas. IEEE Transactions on Antennas and Propagation, 56(4), 1078-1084. doi:10.1109/tap.2008.91920