97 research outputs found

    An adaptive handover prediction scheme for seamless mobility based wireless networks

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    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

    Advanced mobility handover for mobile IPv6 based wireless networks

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    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches.Sadiq, AS.; Fisal, NB.; Ghafoor, KZ.; Lloret, J. (2014). Advanced mobility handover for mobile IPv6 based wireless networks. Scientific World Journal. 2014. doi:10.1155/2014/602808S2014You, 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.1136Li, L., Ma, L., Xu, Y., & Fu, Y. (2014). Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network. The Scientific World Journal, 2014, 1-7. doi:10.1155/2014/341038Nahrstedt, 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/s00383ed1v01y201109mpc008Cho, I., Okamura, K., Kim, T. W., & Hong, C. S. (2013). Performance analysis of IP mobility with multiple care-of addresses in heterogeneous wireless networks. Wireless Networks, 19(6), 1375-1386. doi:10.1007/s11276-012-0539-8Magagula, 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.2386Sadiq, 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/s11036-013-0465-8Lee, K.-W., Seo, W.-K., Cho, Y.-Z., Kim, J.-W., Park, J.-S., & Moon, B.-S. (2009). Inter-domain handover scheme using an intermediate mobile access gateway for seamless service in vehicular networks. International Journal of Communication Systems, 23(9-10), 1127-1144. doi:10.1002/dac.1076Lee, C.-W., Chen, M. C., & Sun, Y. S. (2012). Protocol and architecture supports for network mobility with QoS-handover for high-velocity vehicles. Wireless Networks, 19(5), 811-830. doi:10.1007/s11276-012-0503-7Castelluccia, C. (2000). HMIPv6. ACM SIGMOBILE Mobile Computing and Communications Review, 4(1), 48-59. doi:10.1145/360449.360474Modares, H., Moravejosharieh, A., Lloret, J., & Salleh, R. B. (2016). A Survey on Proxy Mobile IPv6 Handover. IEEE Systems Journal, 10(1), 208-217. doi:10.1109/jsyst.2013.2297705Modares, H., Moravejosharieh, A., Lloret, J., & Salleh, R. (2014). A survey of secure protocols in Mobile IPv6. Journal of Network and Computer Applications, 39, 351-368. doi:10.1016/j.jnca.2013.07.013Modares, H., Moravejosharieh, A., Salleh, R. B., & Lloret, J. (2014). Enhancing Security in Mobile IPv6. ETRI Journal, 36(1), 51-61. doi:10.4218/etrij.14.0113.0177Meneguette, R. I., Bittencourt, L. F., & Madeira, E. R. M. (2013). A seamless flow mobility management architecture for vehicular communication networks. Journal of Communications and Networks, 15(2), 207-216. doi:10.1109/jcn.2013.000034Al-Surmi, I., Othman, M., Abdul Hamid, N. A. W., & Ali, B. M. (2013). Enhancing inter-PMIPv6-domain for superior handover performance across IP-based wireless domain networks. Wireless Networks, 19(6), 1317-1336. doi:10.1007/s11276-012-0535-

    HUC-HISF: A Hybrid Intelligent Security Framework for Human-centric Ubiquitous Computing

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    制度:新 ; 報告番号:乙2336号 ; 学位の種類:博士(人間科学) ; 授与年月日:2012/1/18 ; 早大学位記番号:新584

    A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

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    This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover

    Towards a reliable seamless mobility support in heterogeneous IP networks

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    Next Generation networks (3G and beyond) are evolving towards all IP based systems with the aim to provide global coverage. For Mobility in IP based networks, Mobile IPv6 is considered as a standard by both industry and research community, but this mobility protocol has some reliability issues. There are a number of elements that can interrupt the communication between Mobile Node (MN) and Corresponding Node (CN), however the scope of this research is limited to the following issues only: • Reliability of Mobility Protocol • Home Agent Management • Handovers • Path failures between MN and CN First entity that can disrupt Mobile IPv6 based communication is the Mobility Anchor point itself, i.e. Home Agent. Reliability of Home Agent is addressed first because if this mobility agent is not reliable there would be no reliability of mobile communication. Next scenario where mobile communication can get disrupted is created by MN itself and it is due to its mobility. When a MN moves around, at some point it will be out of range of its active base station and at the same time it may enter the coverage area of another base station. In such a situation, the MN should perform a handover, which is a very slow process. This handover delay is reduced by introducing a “make before break” style handover in IP network. Another situation in which the Mobile IPv6 based communication can fail is when there is a path failure between MN and CN. This situation can be addressed by utilizing multiple interfaces of MN at the same time. One such protocol which can utilize multiple interfaces is SHIM6 but it was not designed to work on mobile node. It was designed for core networks but after some modification in the protocol , it can be deployed on mobile nodes. In this thesis, these issues related to reliability of IPv6 based mobile communication have been addressed.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

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    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

    A hybrid intelligent model for network selection in the industrial Internet of Things

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    Industrial Internet of Things (IIoT) plays an important role in increasing productivity and efficiency in heterogeneous wireless networks. However, different domains such as industrial wireless scenarios, small cell domains and vehicular ad hoc networks (VANET) require an efficient machine learning/intelligent algorithm to process the vertical handover decision that can maintain mobile terminals (MTs) in the preferable networks for a sufficient duration of time. The preferred quality of service parameters can be differentiated from all the other MTs. Hence, in this paper, the problem with the vertical handoff (VHO) decision is articulated as the process of the Markov decision aimed to maximize the anticipated total rewards as well as to minimize the handoffs’ average count. A rewards function is designed to evaluate the QoS at the point of when the connections take place, as that is where the policy decision for a stationary deterministic handoff can be established. The proposed hybrid model merges the biogeography-based optimization (BBO) with the Markov decision process (MDP). The MDP is utilized to establish the radio access technology (RAT) selection’s probability that behaves as an input to the BBO process. Therefore, the BBO determines the best RAT using the described multi-point algorithm in the heterogeneous network. The numerical findings display the superiority of this paper’s proposed schemes in comparison with other available algorithms. The findings shown that the MDP-BBO algorithm is able to outperform other algorithms in terms of number of handoffs, bandwidth availability, and decision delays. Our algorithm displayed better expected total rewards as well as a reduced average account of handoffs compared to current approaches. Simulation results obtained from Monte-Carlo experiments prove validity of the proposed model

    LTE Optimization and Resource Management in Wireless Heterogeneous Networks

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    Mobile communication technology is evolving with a great pace. The development of the Long Term Evolution (LTE) mobile system by 3GPP is one of the milestones in this direction. This work highlights a few areas in the LTE radio access network where the proposed innovative mechanisms can substantially improve overall LTE system performance. In order to further extend the capacity of LTE networks, an integration with the non-3GPP networks (e.g., WLAN, WiMAX etc.) is also proposed in this work. Moreover, it is discussed how bandwidth resources should be managed in such heterogeneous networks. The work has purposed a comprehensive system architecture as an overlay of the 3GPP defined SAE architecture, effective resource management mechanisms as well as a Linear Programming based analytical solution for the optimal network resource allocation problem. In addition, alternative computationally efficient heuristic based algorithms have also been designed to achieve near-optimal performance
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