Developing an SDWN Architecture for Wireless Network Engineering to Support a Quality of Experience Aware Handover

The massive growth of data consumption and the variety of wireless technology emergence has made the handover (HO) an attractive research topic nowadays, mainly due to the popularity of Wireless Local Area Networks (WLANs), which allow users to reach high-speed data communication while they are in movement. Moreover, mobile devices such as tablets and smartphones have also become increasingly popular due to their low cost and ease of use, and an increase in mobile device use is expected to accelerate in the coming years, along with the availability and use of applications such as real-time services and online gaming. The traditional HO methods will likely not meet the requirements of mobile devices for modern applications due to the lack of intelligence, lack of awareness Quality of Service (QoS) and Quality of Experience (QoE) requirements of mobile users. We, therefore, introduce a novel architecture that supports horizontal HO in homogenous networks. This architecture is based on the Software-Defined Wireless Networking (SDWN) concept, where the wireless network is controlled centrally and the wireless Access Points (APs) are programmable. In this architecture, HO algorithms will assist wireless users to find the network that could best support the application requirements through Quality of Service (QoS) and Quality of Experience (QoE) management policies. The first HO algorithm proposed in this thesis is called Quality of Experience Oriented Handover Algorithm. This algorithm will guarantee the best possible connectivity to the users in terms of their QoE and QoS requirements and outperforms the traditional methods in a sparse network environment. The second contribution is called Optimised Handover Algorithm for Dense WLAN Environments. This algorithm has been designed to address dense network environments via taking into consideration the Adaptive Hysteresis Value (AHV). The AHV will help the Optimised Handover Algorithm via reducing the so-called ping-pong effect. This contribution shows promising performance results by selecting the best candidate AP, decreasing the number of redundant HO and avoiding the ping-pong effect. The final contribution is called Priority Based Handover Algorithm. We extended our proposed SDWN architecture in order to include the concept of prioritising users and make a smart decision during the process of HO. This algorithm will prioritise a certain class of users to avoid the effect of the over-congestion. The results show that the approach based on priority outperforms the state of the art and provides better QoE to the high priority users despite the over-congestion situation

Towards a knowledge-based intelligent handover in heterogeneous wireless networks

International audienceThis work presents a knowledge-based handover anticipation scheme. We propose to construct a knowledge plane using intelligent agents. Agents are delegated to information collection for nourishing the knowledge plane and also, handover decision and a proper network selection. We use the parameters of RSS, bandwidth, cost, user preferences, and mobility pattern of the mobile user. We estimate the future attachment point for the mobile user and anticipate the handover. Finally, we analyze the performance of our approach for (1) assuring the quality of service for different types of ongoing sessions during the handover, (2) reducing handover latency, (3) reducing the ping-pong effect and (4) signaling overhead

Towards a knowledge-based intelligent handover in heterogeneous wireless networks

International audienceThis work presents a knowledge-based handover anticipation scheme. We propose to construct a knowledge plane using intelligent agents. Agents are delegated to information collection for nourishing the knowledge plane and also, handover decision and a proper network selection. We use the parameters of RSS, bandwidth, cost, user preferences, and mobility pattern of the mobile user. We estimate the future attachment point for the mobile user and anticipate the handover. Finally, we analyze the performance of our approach for (1) assuring the quality of service for different types of ongoing sessions during the handover, (2) reducing handover latency, (3) reducing the ping-pong effect and (4) signaling overhead