Mirghiasaldin Seyedebrahimi

Quality of Service Oriented Access Point Selection Framework for Large Wi-Fi Networks

This paper addresses the problem of access point (AP) selection in large Wi-Fi networks. Unlike current solutions that rely on received signal strength to determine the best AP that could serve a wireless user’s request, we propose a novel framework that considers the quality of service (QoS) requirements of the user’s data flow. The proposed framework relies on a function reflecting the suitability of a Wi-Fi AP to satisfy the QoS requirements of the data flow. The framework takes advantage of the flexibility and centralised nature of software defined networking (SDN). A performance comparison of this algorithm developed through an SDN-based simulator shows significant achievements against other state-of-the-art solutions in terms of provided QoS and improved wireless network capacity.

A quality driven framework for adaptive video streaming in mobile wireless networks

The concern over the quality of delivering video streaming services in mobile wireless networks is addressed in this work. A framework that enhances the Quality of Experience (QoE) of end users through a quality driven resource allocation scheme is proposed. To play a key role, an objective no-reference quality metric, Pause Intensity (PI), is adopted to derive a resource allocation algorithm for video streaming. The framework is examined in the context of 3GPP Long Term Evolution (LTE) systems. The requirements and structure of the proposed PI-based framework are discussed, and results are compared with existing scheduling methods on fairness, efficiency and correlation (between the required and allocated data rates). Furthermore, it is shown that the proposed framework can produce a trade-off between the three parameters through the QoE-aware resource allocation process.

Adaptive Resource Allocation for QoE-Aware Mobile Communication Networks

A real-time adaptive resource allocation algorithm considering the end users Quality of Experience (QoE) in the context of video streaming service is presented in this work. An objective no-reference quality metric, namely Pause Intensity (PI), is used to control the priority of resource allocation to users during the scheduling process. An online adjustment has been introduced to adaptively set the schedulers parameter and maintain a desired trade-off between fairness and efficiency. The correlation between the data rates (i.e. Video code rates) demanded by users and the data rates allocated by the scheduler is taken into account as well. The final allocated rates are determined based on the channel status, the distribution of PI values among users, and the scheduling policy adopted. Furthermore, since the users capability varies as the environment conditions change, the rate adaptation mechanism for video streaming is considered and its interaction with the scheduling process under the same PI metric is studied. The feasibility of implementing this algorithm is examined and the result is compared with the most commonly existing scheduling methods.

Investigation of PHY, MAC and APP Layers for Adaptive and Cross-Layer Optimization in IEEE802.11 WLAN

Due to huge popularity of portable terminals based on Wireless LANs and increasing demand for multimedia services from these terminals, the earlier structures and protocols are insufficient to cover the requirements of emerging networks and communications. Most research in this field is tailored to find more efficient ways to optimize the quality of wireless LAN regarding the requirements of multimedia services. Our work is to investigate the effects of modulation modes at the physical layer, retry limits at the MAC layer and packet sizes at the application layer over the quality of media packet transmission. Interrelation among these parameters to extract a cross-layer idea will be discussed as well. We will show how these parameters from different layers jointly contribute to the performance of service delivery by the network. The results obtained could form a basis to suggest independent optimization in each layer (an adaptive approach) or optimization of a set of parameters from different layers (a cross-layer approach). Our simulation model is implemented in the NS-2 simulator. Throughput and delay (latency) of packet transmission are the quantities of our assessments.

A centralised Wi-Fi management framework for D2D communications in dense Wi-Fi networks

In Wi-Fi networks, Device-to-Device (D2D) communications aim to improve the efficiency of the network by supporting direct communication between users in close proximity. However, in a congested Wi-Fi network, establishing D2D connections through a locally managed self-organising approach will intensify the congestion and reduce the scalability of the solution. Therefore, a centralised management approach must be involved in orchestrating those actions to guarantee the sufficiency of D2D communications. In this paper, we propose a novel management framework for D2D communications in dense Wi-Fi networks. The proposed framework employs a Software-Defined Networking (SDN) based centralised controller in synergy with a novel Access Point (AP) channel assignment process. This framework is designed to proactively establish and manage D2D connections in Wi-Fi networks considering the available radio resources and the effect of the subsequent interference. Thus, improving the overall performance of the network and providing users with higher data rate. Through simulation, we validate the effectiveness of the proposed framework and demonstrate how D2D deployment considerably improves the Wi-Fi network efficiency especially when the data rate requirements are high. Furthermore, we show that our proposed framework achieves better performance than the widely deployed Least Congested Channel selection strategy (LCC).

Client QoE-Oriented Segment Selection for DASH

A segment selection method controlled by Quality of Experience (QoE) factors for Dynamic Adaptive Streaming over HTTP (DASH) is presented in this paper. Current rate adaption algorithms aim to eliminate buffer underrun events by significantly reducing the code rate when experiencing pauses in replay. In reality, however, viewers may choose to accept a level of buffer underrun in order to achieve an improved level of picture fidelity or to accept the degradation in picture fidelity in order to maintain the service continuity. The proposed rate adaption scheme in our work can maximize the user QoE in terms of both continuity and fidelity (picture quality) in DASH applications. It is shown that using this scheme a high level of quality for streaming services, especially at low packet loss rates, can be achieved. Our scheme can also maintain a best trade-off between continuity-based quality and fidelity-based quality, by determining proper threshold values for the level of quality intended by clients with different quality requirements. In addition, the integration of the rate adaptation mechanism with the scheduling process is investigated in the context of a mobile communication network and related performances are analyzed.

Optimising QoE Distribution for Video Applications through LTE-WiFi Interworking

Mobile WiFi devices are becoming increasingly popular in non-seamless and user-controlled mobile traffic offloading alongside the standard WiFi hotspots. Unlike the operator-controlled hotspots, a mobile WiFi device relies on the capacity of the macro-cell for the data rate allocated to it. This type of devices can help offloading data traffic from the macro-cell base station and serve the end users within a closer range, but will change the pattern of resource distributions operated by the base station. We propose a resource allocation scheme that aims to optimize user quality of experience (QoE) when accessing video services in the environment where traffic offloading is taking place through interworking between a mobile communication system and low range wireless LANs. In this scheme, a rate redistribution algorithm is derived to perform scheduling which is controlled by a no-reference quality assessment metric in order to achieve the desired trade-offs between efficiency and fairness. We show the performance of this algorithm in terms of the distribution of the allocated data rates throughout the macro-cell investigated and the service coverage offered by the WiFi access point.

Ensuring QoE in contemporary mobile networks for video content distribution

A framework that aims to best utilize the mobile network resources for video applications is presented in this paper. The main contribution of the work proposed is the QoE-driven optimization method that can maintain a desired trade-off between fairness and efficiency in allocating resources in terms of data rates to video streaming users in LTE networks. This method is concerned with the control of the user satisfaction level from the service continuitys point of view and applies appropriate QoE metrics (Pause Intensity and variations) to determine the scheduling strategies in combination with the mechanisms used for adaptive video streaming such as 3GP/MPEG-DASH. The superiority of the proposed algorithms are demonstrated, showing how the resources of a mobile network can be optimally utilized by using quantifiable QoE measurements. This approach can also find the best match between demand and supply in the process of network resource distribution.