A Seamless Mobile Learning and Tension Free Lifestyle by QoS Oriented Mobile Handoff

Abstract

Today, people use their cell phones not only for making phone calls or sending messages, they use the cell phone for online banking, online shopping, checking Email, viewing video, using social apps like facebook, getting online health and medical information via Internet access while walking down in the street or sitting in the restaurants. This usage of Internet-oriented services via mobile devices makes the human life much easier by saving valuable time and money. Also, most of the school and college students use the mobile phone for learning by viewing educational videos from various video servers. Today video conferencing, online classes are quite common. For achieving these benefits of mobile communication effectively Quality of Service (QoS) with seamless mobility is important. In this paper, we tried to improve the QoS and seamless mobility for enhancing the lifestyle of the people by performing a QoS oriented handoff in widely deployed WLAN. Deployment of IEEE 802.11n wireless local area network (WLAN) is very popular due to quick installation, low cost and higher data rate of about 600Mbps. The backward compatible 802.11n could not utilize its new features fully in the presence of legacy 802.11a/b/g nodes. The existence of such legacy nodes in the 802.11n network is common today since the users tend to upgrade their devices slowly. The performance anomaly caused by the legacy nodes have to be minimized in WLANs for maximizing the quality of service (QoS). In this paper we have proposed a QoS based handoff algorithm which helps in minimizing the impact of legacy nodes on 802.11n nodes by performing either Level 2 or Level 3 handoff based on the mobile type, ongoing application's type (i.e. real-time or non-real-time), required bandwidth, subnet ID, acceptable packet delay and network condition. The primary objective of our proposed work is to isolate the 802.11n nodes from the legacy nodes, eliminate the number of ungainful handoffs, giving preference to Level 2 than Level 3 handoff for reducing the handoff latency, improve the individual node's throughput, decrease the individual node's packet delay, and improve the overall network throughput significantly. Simulation results show that the proposed handoff algorithm improves both individual mobile node performance and overall network throughput significantly.