Abdelhak Bentaleb

SDNDASH: Improving QoE of HTTP Adaptive Streaming Using Software Defined Networking

HTTP adaptive streaming (HAS) is being adopted with increasing frequency and becoming the de-facto standard for video streaming. However, the client-driven, on-off adaptation behavior of HAS results in uneven bandwidth competition and this is exacerbated when a large number of clients share the same bottleneck network link and compete for the available bandwidth. With HAS each client independently strives to maximize its individual share of the available bandwidth, which leads to bandwidth competition and a decrease in end-user quality of experience (QoE). The competition causes scalability issues, which are quality instability, unfair bandwidth sharing and network resource underutilization. We propose a new software defined networking (SDN) based dynamic resource allocation and management architecture for HAS systems, which aims to alleviate these scalability issues and improve the per-client QoE. Our architecture manages and allocates the network resources dynamically for each client based on its expected QoE. Experimental results show that the proposed architecture significantly enhances scalability by improving per-client QoE by at least 30% and supporting up to 80% more clients with the same QoE compared to the conventional schemes.

A Weight Based Clustering Scheme for Mobile Ad hoc Networks

Mobile Ad hoc networks (MANETs) are self-organizing and self-configuring multi-hop wireless networks without any pre-existing communication infrastructures or centralized management. Scalability in MANETs is a new issue where network topology includes large number of nodes and demands a large number of packets in limited wireless bandwidth and nodes mobility that results in a high frequency of failure regarding wireless links. Clustering in MANETs is an important topic that divides the large network into several sub networks and widely used in efficient network management, improving resource management, hierarchical routing protocol design, Quality of Service and a good monitoring architecture of MANETs security. Subsequently, many clustering approaches have been proposed to divide nodes into clusters to support routing and network management. In this paper, we propose a new efficient weight based clustering algorithm. It takes into consideration the metrics: trust (T), density (D), Mobility (M) and energy (E) to choose locally the optimal cluster heads during cluster formation phase. In our proposed algorithm each cluster is supervised by its cluster head in order to ensure an acceptable level of security. It aims to improve the usage of scarce resources such as bandwidth, maintaining stable clusters structure with a lowest number of clusters formed, decreasing the total overhead during cluster formation and maintenance, maximizing lifespan of mobile nodes in the network and reduces energy consumption. Preliminary simulation experiments are conducted to compare the performance of our algorithm to Lowest ID, Highest Degree and WCA in terms of Average Number of CHs, Average Number of CH Changes, Total Number of Re-affiliations, Clusters Stability and Total Overhead. The initial results show that our scheme performs better than other clustering schemes based on the performance metrics considered.

A new topology management scheme for large scale mobile ad hoc networks

Newly, with the emergence of demanding applications e.g. multimedia applications and its rapid prevalence on a large scale area e.g. urban environment. Supporting the scalability as well as satisfying QoS of demanding applications represent one of the main properties in urban environments. However, supporting applications and services in a such complex, distributed, large and diverse environment as well as building-up a wireless network in such environment that satisfies the scalability and QoS properties is a very hard task. In this paper, we propose an efficient scalable-QoS hierarchical topology management-based scheme in large scale network that supports and satisfies the urban environment properties. Our scheme consists of two hierarchical levels based on the combination between the clustering and virtual backbone techniques for large scale MANETs. In the first level, we propose an efficient weight based clustering approach which considers a trade-off between QoS requirements of multimedia services like bandwidth and link quality as well as the clustering metrics such as node (trust, density, mobility and energy). Whilst in the second level, we are based on connected dominating set algorithm to build the virtual backbone. The main purposes of our proposed scheme are: to support the network scalability when network size increases (thousands of nodes), supports the multimedia services with multimedia services QoS satisfaction. Simulation results have shown that our scheme performs generally better than the other topology management schemes.

A scalable clustering scheme and its performance evaluation

Purpose – Scalability is a fundamental problem in mobile ad hoc networks (MANETs), where network topology includes large number of nodes and demands a large number of packets in network that characterized by dynamic topologies, existence of bandwidth constrained, variable capacity links, energy constraint and nodes are highly prone to security threats. The key purpose of this paper is to overview the efficiency of the proposed clustering scheme for large-scale MANETs and its performance evaluation and especially in the case of a large number of nodes in the network. Design/methodology/approach – Designing clustering schemes for MANETs, which are efficient and scalable in the case of large number of mobile nodes, has received a great attention in the last few years. It is widely used to improve resources management, hierarchical routing protocol design, quality of service, network performance parameters such as routing delay, bandwidth consumption, throughput and security. MANETs are characterized by limit...

Want to play DASH?: a game theoretic approach for adaptive streaming over HTTP

In streaming media, it is imperative to deliver a good viewer experience to preserve customer loyalty. Prior research has shown that this is rather difficult when shared Internet resources struggle to meet the demand from streaming clients that are largely designed to behave in their own self-interest. To date, several schemes for adaptive streaming have been proposed to address this challenge with varying success. In this paper, we take a different approach and develop a game theoretic approach. We present a practical implementation integrated in the dash.js reference player and provide substantial comparisons against the state-of-the-art methods using trace-driven and real-world experiments. Our approach outperforms its competitors in the average viewer experience by 38.5% and in video stability by 62%.

Cliques and clusters based hierarchical scheme for sensor networks partitioning

The hierarchical clustering for wireless sensors networks is treated to solve the scalability problem in routing protocols for multi-hop wireless networks. Also a clustering-based technique is proposed to provide location management of devices for QoS support. To the best of our knowledge there is no protocol that combines the hierarchical partitioning into clusters and cliques taking into account the size of cliques and clusters (a clique is a network where every node can communicate directly with every other node in the same clique). In this paper, we propose a new partitioning scheme motivated by the need to have minimum and maximum size for cliques and clusters. In fact, this size has a direct effect on energy consumption. Indeed, for a large size of clique or cluster the cluster head should register the identities of its cluster members and manage them. That is not always feasible because sensor networks have a very limited memory capacity and energy. In addition, limiting the number of sensors in each clique or cluster avoids a significant number of cluster head re-election where the energy will be the parameter of election. So the characteristics of WSN are not satisfied, the aim of our work is to deal with these cases.

A Distributed Approach for Bitrate Selection in HTTP Adaptive Streaming

Past research has shown that concurrent HTTP adaptive streaming (HAS) players behave selfishly and the resulting competition for shared resources leads to underutilization or oversubscription of the network, presentation quality instability and unfairness among the players, all of which adversely impact the viewer experience. While coordination among the players, as opposed to all being selfish, has its merits and may alleviate some of these issues. A fully distributed architecture is still desirable in many deployments and better reflects the design spirit of HAS. In this study, we focus on and propose a distributed bitrate adaptation scheme for HAS that borrows ideas from consensus and game theory frameworks. Experimental results show that the proposed distributed approach provides significant improvements in terms of viewer experience, presentation quality stability, fairness and network utilization, without using any explicit communication between the players.

ORL-SDN: Online Reinforcement Learning for SDN-Enabled HTTP Adaptive Streaming

In designing an HTTP adaptive streaming (HAS) system, the bitrate adaptation scheme in the player is a key component to ensure a good quality of experience (QoE) for viewers. We propose a new online reinforcement learning optimization framework, called ORL-SDN, targeting HAS players running in a software-defined networking (SDN) environment. We leverage SDN to facilitate the orchestration of the adaptation schemes for a set of HAS players. To reach a good level of QoE fairness in a large population of players, we cluster them based on a perceptual quality index. We formulate the adaptation process as a Partially Observable Markov Decision Process and solve the per-cluster optimization problem using an online Q-learning technique that leverages model predictive control and parallelism via aggregation to avoid a per-cluster suboptimal selection and to accelerate the convergence to an optimum. This framework achieves maximum long-term revenue by selecting the optimal representation for each cluster under time-varying network conditions. The results show that ORL-SDN delivers substantial improvements in viewer QoE, presentation quality stability, fairness, and bandwidth utilization over well-known adaptation schemes.

A k -hop Scalable Management Scheme for Large Scale Mobile Ad Hoc Networks

The recent rapid growth of cities, the evolution of wireless/mobile technologies and diverse demanding applications, the world is becoming more and more urban. Today, wireless and mobile networks as well multimedia applications play an essential challenging role within urban environment and they are take a considerable attention to improve and render the urban environment increasingly sustainable and livable. The main purpose of wireless and mobile networks is to share the fresh updated information collected around the urban environment between the stakeholders and the citizen constantly. However, it’s very difficult to achieve this task in a complex, distributed, large (billions of heterogeneous connected devices) and diverse innovative demanding applications and services in urban environment. It is noteworthy that these demanding applications and services require constructing a wireless network that satisfies the scalability and QoS in this environment. In this paper, we propose an efficient k-hop scalability and QoS topology management scheme for large scale Mobile Ad Hoc Networks which is suitable for demanding application in urban environment. Our proposed scheme meets the scalability needs of urban environment as well the QoS of demanding applications like multimedia applications, by constructing a two hierarchical topology level based on trade-off between the clustering and virtual backbone mechanisms. To achieve and supports network scalability when network size increases (thousands of nodes) and satisfy the QoS of demanding applications, we propose in the first level, an efficient weight based clustering approach which considers a trade-off between the clustering metrics such as trust, density, mobility and energy, and QoS requirements like available bandwidth and link quality. In the second level, we based on connected dominating set algorithm to build a virtual backbone. Simulation results show that our scheme is able to reduce the number of cluster heads, the number of cluster heads re-affiliations, the total overheads and the number of dominating set, and increase the clusters stability, packets delivery ration and the network life time compared to other topology management schemes.