International Journal of Advanced Networking and Applications

Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

It is suggested that multi-path routing is advantageous for applications with high traffic data characteristics, especially in the WSN environment. Sensor networks which transmit video will have to respond to the high data characteristic inherent in video data. Throughput, delay and packet loss are important metrics when considering video traffic. This work measures the performance of four multi-path routing protocols, MAOMDV, AOMDV, AntHocNet and MP-DSR in the WSN environment. It is shown that MAOMDV outperforms the other multi-path routing protocols in terms of the aforementioned metrics.

Keywords

Multi-Path, WSN, Video, Throughput, Delay, Packet Loss.

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Koffka Khan ¹, Wayne Goodridge ²

Affiliations
1 Department of Computing and Information Technology, The University of the West Indies, Trinidad and Tobago, W.I, IN
2 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, W.I, IN

Abstract

A new architecture for defining network collaboration in DASH is called SAND. It aims to standardize communication amongst network agents participating in the streaming process. This work produces a novel taxonomy for SAND-based approaches. It places AVS solutions into four categories: (1) Management Architecture (2) Cache-based, (3) Optimization, and (4) Paradigm. Sub-categories of Management Architecture are (a) Cognitive, (b) Prioritization, and (c) Encoding and Signaling, while sub-categories of Paradigm are (a) SDN-based, (b) CDN-based, and (c) CCN-based. The approaches representing each category are presented. It is shown that using the SANDs architecture proves beneficial to approaches adopting it. In recent years Cloud-based strategies for AVS have been an important area of research and industry. This paper elaborates on Cloud-based strategies. It places current strategies into a taxonomy. The Cloud-based AVS strategies are categorized into (1) Social- Awareness, (2) Cloud-based CDN, (3) Cloud-based Gaming, (4) Cloud-based SDN, (5) File-hosting services, (6) View synthesis techniques, and (7) Error Concealment techniques. The implementations that exist for the Cloudbased strategies are discussed. Thus, the advantages of both SAND and Cloud-based approaches for use in DASHbased systems are illustrated.

Keywords

DASH, SAND, Adaptive, Video, Streaming, Sdn, Optimization, Cache, CDN, Encoding, Signaling, Cloud, Social-Awareness, Gaming.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology, The University of the West Indies, Trinidad and Tobago, W.I, IN

Abstract

Server-based adaptive video streaming is gaining popularity in recent years. This is because clients (client-based) and in-network devices (network or proxy-based) are not powerful enough to run state of the art adaptation algorithms, for example, traffic shaping and machine learning. When decision making is placed at the server new and exciting possibilities are obtained for next best segment selection. This work highlights server-based solutions to adaptive video streaming. It provides a taxonomy of current state of the art solutions. It then illustrates various approaches used for server-based adaptive video streaming. Advantages and disadvantages are discussed. Network-assisted or in-network DASH solutions have certain advantages over traditional client-based approaches. It is proposed that the sharing of information would result in better network and client bandwidth estimations. This measure would ensure better next segment selections. In this paper a novel network-assisted DASH taxonomy is proposed. It consists of cache-based, optimization, rate-quality model, and co-operative elements. Recent approaches using the elements of the taxonomy are illustrated. These approaches show the advantages of using network-assisted entities in DASH-based systems.

Keywords

Server-Based, Adaptive Video Streaming, Traffic Shaping, Machine Learning, Taxonomy, Networkassisted, In-Network, Bandwidth, Segment, Cache, Optimization, Rate-Quality, Co-Operative, DASH.

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Koffka Khan ¹, Wayne Goodridge ²

Affiliations
1 Department of Computing and Information Technology, The University of the West Indies, Trinidad and Tobago, W.I, IN
2 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, W.I, IN

Abstract

Recently machine learning has been introduced into the area of adaptive video streaming. This paper explores a novel taxonomy that includes six state of the art techniques of machine learning that have been applied to Dynamic Adaptive Streaming over HTTP (DASH): (1) Q-learning, (2) Reinforcement learning, (3) Regression, (4) Classification, (5) Decision Tree learning, and (6) Neural networks.

Keywords

Machine Learning, DASH, Q-Learning, Reinforcement Learning, Regression, Classification, Decision Tree Learning, Neural Networks.

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Koffka Khan ¹, Wayne Goodridge` ²

Affiliations
1 Department of Computing and Information Technology, The University of the West Indies, TT
2 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Over recent years there has been a considerable shift, from quality of service (QoS) to quality of experience (QoE), when evaluating video delivery across networks. Hence, we first explore the need for this shift towards user-QoE in the video delivery ecosystem. Further, we investigate major QoE metrics researchers use in the evaluation of DASH users. We point out a huge problem with DASH beginning with its transport layer protocol. DASH utilizes Transmission control protocol (TCP) as the transport layer protocol. Thus, we give an overview of the mechanism of Transmission Control Protocol (TCP) and two mechanisms greatly impacting the streaming process: (1) TCP congestion mechanism and (2) TCP Fast Start. This leads us to investigate the impact of these TCP mechanisms on DASH players and consequently user-QoE.

Keywords

QoS, User-QoE, Video, TCP, Transport Layer, Dash, Congestion, Fast Start.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

In the adaptive video streaming (AVS) literature the term fair sharing has been used to describe equal amounts of bandwidth allocated to adaptive client players. However, we argue that even though bandwidth sharing is an important aspect in some problems the same does not apply to AVS. Here the term relative ‘fair’ sharing is more applicable. The reason is that videos have different quality levels and will require differing amounts of the bandwidth to satisfy their needs. A 90% to 10% sharing may be sufficient for two players, one with high demands and the other with low demands. A 50% sharing may lead the player with the high bandwidth demand to get too little of the needed bandwidth resource. In addition, channel conditions may lead to players requiring different amount of bandwidth. Again, the concept of fair sharing has to be extended to relative ‘fair’ sharing for such scenarios. Hence, bandwidth estimation techniques players use to estimate the network bandwidth is very important in segment selection. A player utilizes one of the many techniques to determine what share of the bandwidth it can utilize among competing players. In this paper we explore some of the techniques used in stateof- the-art players in their attempt to obtain a ‘fair’ share of the network bandwidth.

Keywords

Adaptive Video Streaming, Bandwidth, Demand, Sharing.

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Koffka Khan ¹

Affiliations
1 Department of Computing and Information Technology, The University of the West Indies, TT

Abstract

This work illustrates the AOMDV routing protocol. Its ancestor, the AODV routing protocol is also described. This tutorial demonstrates how forward and reverse paths are created by the AOMDV routing protocol. Loop free paths formulation is described, together with node and link disjoint paths. Finally, the performance of the AOMDV routing protocol is investigated along link and node disjoint paths. The WSN with the AOMDV routing protocol using link disjoint paths is better than the WSN with the AOMDV routing protocol using node disjoint paths for energy consumption.

Keywords

AOMDV, AODV, Paths, Loop-Free, Node Disjoint, Link Disjoint, Multi-Criteria, AOMDV.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Competition among adaptive video streaming players severely diminishes user-QoE. When players compete at a bottleneck link many do not obtain adequate resources. This imbalance eventually causes ill effects such as screen flickering and video stalling. There have been many attempts in recent years to overcome some of these problems. However, added to the competition at the bottleneck link there is also the possibility of varying network bandwidth which can make the situation even worse. This work focuses on such a situation. It evaluates current heuristic adaptive video players at a bottleneck link with time-varying bandwidth conditions. Experimental setup includes the TAPAS player and emulated network conditions. The results show PANDA outperforms FESTIVE, ELASTIC and the Conventional players.

Keywords

Adaptive Video Streaming, Bottleneck, Flickering, Stalling, Time-Varying, Bandwidth, TAPAS, PANDA, FESTIVE, ELASTIC.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology the University of the West Indies, TT
2 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

In recent years DASH has become the de facto standard for video streaming. However, applications continue to demand more bandwidth in an effort to satisfy users. This is based on applications such as 360° and immersive Virtual Reality/Augmented Reality (VR/AR) video. This paper explores current state of the art and introduces the reader to some of these DASH-aware bandwidth intensive applications.

Keywords

DASH, Applications, Bandwidth, Video, Streaming, 360°, VR, AR.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology the University of the West Indies, TT
2 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

ICN has received a lot of consideration in recent years, and is a likely approach for the Future Internet design. As multimedia is the dominating traffic, it is vital to study this type of data transmission in the context of ICN. In particular, the adaptive streaming of multimedia content is a promising approach for treatment within ICN. The client has full control over the streaming session. This enables the possibility of adapting the multimedia stream to its context (e.g. network conditions, device capabilities, user-QoE (Quality of Service)). These objectives are wellmatched with the standards accepted by ICN. In this article we investigate dynamic adaptive video streaming over HTTP (DASH) over networks adopting the ICN approach. In particular, we focus on seven main applications: (1) Mobile, (2) SVC-based (Scalable Video Coding), (3) Named Data Networking (NDN), (4) Vehicular Networks, (5) 5G systems, (6) Internet of Things (IoTs), and (7) Security.

Keywords

ICN, Future Internet, DASH, Mobile, SVC, NDN, Vehicular, 5G, IoT, Security.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Competition among adaptive video streaming players severely diminishes user-QoE. When players compete at a bottleneck link many do not obtain adequate resources. This imbalance eventually causes ill effects such as screen flickering and video stalling. This scenario worsens when Long-lived TCP flows compete with the video flows. It is a known fact that adaptive video players perform poorly in the presence of Long-lived TCP flows. This work evaluates current heuristic adaptive video players at a bottleneck link in the presence of Long-lived TCP flows. Experimental setup includes the TAPAS player and emulated network conditions. The results show ELASTIC outperforms PANDA, FESTIVE and the Conventional players.

Keywords

Adaptive Video Streaming, Bottleneck, Flickering, Stalling, TAPAS, ELASTIC, PANDA, FESTIVE.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Cross Site Scripting, SQL Injection, Denial of Service (DOS), Buffer Overflow and Password Cracking are current network-based security attacks that still looms on the Internet. Though these attacks have been around for decades and there exist protective mechanism for overcoming them they are still relevant today. In this paper we describe the basic workings of these attacks and outline how companies and individuals can mitigate these attacks. By taking the necessary precautions the severity of these attacks can be diminished.

Keywords

Cross Site Scripting, SQL Injection, Denial of Service (DOS), Buffer Overflow, Password Cracking, Security Attacks, Internet.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Competition among adaptive video streaming players severely reduces user-QoE. This occurs as resource allocation becomes unfair. We refer to this as the bottleneck link problem. The resource imbalance creates severe user annoyance such as screen flickering and video freezes. However, there are numerous conditions that amplifies the problems. Some of these are well documented in the literature but we intend to highlight the major conditions at a bottleneck link in household LANs. These are time-varying bandwidth, TCP long-lived flows, players pausing, starting/re-starting and stopping and increases in player numbers. We explore these conditions and evaluate the performance of heuristic adaptive video players. ELASTIC and PANDA players are evaluated. Experimental setup includes the TAPAS player and emulated network conditions. The results show that players are well suited to specific conditions.

Keywords

User-QoE, Resource, Allocation, Unfair, Screen Flickering, Video Freezes, Bottleneck, Household, Time-Varying, TCP Long-Lived Flow, TAPAS, ELASTIC, PANDA.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Competition among adaptive video streaming players severely diminishes user-QoE. When players compete at a bottleneck link many do not obtain adequate resources. This imbalance eventually causes ill effects such as screen flickering and video stalling. There have been many attempts in recent years to overcome some of these problems. This work focuses on such a situation. It evaluates current stochastic adaptive video players at a bottleneck link and when the number of players increases. Experimental setup includes the TAPAS player and emulated network conditions. The results show mDASH outperforms x-MDP, sdpDASH and the Conventional players.

Keywords

Adaptive Video Streaming, Bottleneck, Flickering, Stalling, TAPAS, mDASH, x-MDP, spdDASH.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Video-over-IP applications have recently attracted a large number of users on the Internet. Traditional clientserver based video streaming solutions incur lavish bandwidth provision cost on the server. Peer-to-Peer (P2P) networking is a new paradigm to build distributed network applications. Recently, several P2P streaming systems have been deployed to provide live and on-demand video streaming services on the Internet at low server cost. This paper explores dynamic adaptive streaming over HTTP (DASH) within P2P systems.

Keywords

Video-Over-IP, Internet, Peer-to-Peer, P2P, Streaming, DASH.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Q-Learning is an important class of stochastic optimization whichhas recently been used in the area of dynamic adaptive streaming over HTTP (DASH). Though DASH is very popular method of video delivery in recent years it is plagued with problems when multiple players share a bottleneck link. Thus, this area has becomea very active area of research. Two works which implement Q-Learning in DASH are selected and their performances compared against the Conventional DASH player. It is shown that Q-Learning works well for various network conditions.

Keywords

Q-Learning, Stochastic, Optimization, DASH, Video, Bottleneck, Network.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

The performance of today’s adaptive video streaming players (DASH) is severely hindered byoverlapping ON-OFF patterns that occurs during a streaming session. High switching rates, freezing and skipping annoy users resulting in poor user-QoE. This paper attempts to overcome the ON-OFF problem by keeping players awareof each other’s downloads and inter-request times. Using this a player is able to better predict future player actions and reschedule their downloads to produce least conflicts with others. If a player’s start segment download overlaps with the end of one or more players’current downloads within a certain time t 1it waits until the download of others completes before starting its own download. Conversely if too many players are sharing the bottleneck link a player will hold of its download by a time t2 enabling others to move towards completion of their downloads. This reduces the overlap of its download with other players. Both these methods help reduce competition at the bottleneck and producesa more balanced sharing of network resources.

Keywords

DASH, Overlapping, ON-OFF, Streaming, User-QoE, Bottleneck, Link, Network, Resources, DASH.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Stochastic Dynamic Programming (SDP) is an important class of optimization which has recently been used in the area of dynamic adaptive streaming over HTTP (DASH). Though DASH is very popular method of video delivery in recent years it is plagued with problems when multiple players share a bottleneck link. Thus, this area has become a very active area of research. Two works which implement SDP in DASH are selected and their performances compare d against the Conventional DASH player. It is shown that SDP works well for various network conditions.

Keywords

Stochastic, Dynamic, Programming, SDP, Optimization, DASH, Video, Bottleneck, Network.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, TT

Abstract

Reinforcement Learning is an important class of optimization which has recently been used in the area of dynamic adaptive streaming over HTTP (DASH). Though DASH is very popular method of video delivery in recent years it is plagued with problems when multiple players share a bottleneck link. Thus, this area has become a very active area of research. Two works which implement Reinforcement Learning in DASH are selectedand their performances compared against the Conventional DASH player. It is shown that SDP works well for various network conditions.

Keywords

Reinforcement Learning, Optimization, DASH, Video, Bottleneck, Network.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, W.I, TT

Abstract

Even though there is considerable work in adaptive video streaming, video players still suffer drawbacks which include: inadequate fair share, poor bandwidth utilization, frequent level shifts and high re-buffering ratios. These draw- backs result in poor perceived video quality which degrades a viewers quality of experience (QoE). DASH approaches have been known to deliver higher QoE to viewers by improving the video players segment selection. However, the transport layer protocol is another important aspect of video streaming. Hypertext Transfer Protocol (HTTP) is the most used application layer protocol over the Internet. It utilizes Transmission Control Protocol (TCP) as its transport layer protocol. TCP variants use different mechanisms for congestion control. The DASH standard uses HTTP, thus TCP variant selection becomes very important for effective video streaming. In this paper we test the performance of four linux-based TCP variants using the Conventional, PANDA and ELASTIC client-side DASH players in congested bottleneck link conditions. These experiments illustrate the varying impact on viewer QoE when using these various TCP congestion control mechanisms. The importance of TCP variant selection is exemplified as we observe that Westwood+ and YeAH are the most promising variants.

Keywords

QoE, DASH, HTTP, TCP, congestion, PANDA, ELASTIC, Westwood, YeAH.

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Koffka Khan ¹, Leah Joseph ¹, Emilie Ramsahai ²

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, West Indies
2 The School of Science, Artificial Intelligence and Computing, The University of the West Indies, Five Islands Campus, Trinidad and Tobago, West Indies

Abstract

A lot of research has been done in the area of TCP long-lived (TLL) and short-lived flows and well as UDP but there is limited research done on how they can affect adaptive video streaming at a single household bottleneck router. The goal of Adaptive streaming is to deliver videos to the user in the most efficient way possible and in the best quality possible. Several factors can affect the quality of videos including internet connection and other applications using the same router. It is important to note which applications can negatively affect streaming and cause issues such as poor-quality videos and buffering. This paper investigates the impact that various applications that use TCP long-lived flows have on streaming and its effect is compared to applications that use UDP flows. The aim is to determine which type of flow affects adaptive streaming the most. This investigation is carried out with the use of the TAPAS (a Tool for rApid Prototyping of Adaptive Streaming) player. Live experiments were conducted at a household bottleneck link with a client player, a TCP or UDP application. We show that UDP flows disrupt adaptive video streaming to a greater extent when compared to TCP TLL flows.

Keywords

Adaptive Streaming, Bottleneck, Live Experiments, Metrics, TAPAS, TCP Long-Lived Flows, TCP Shortlived Flows, UDP Flows.

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Koffka Khan ¹, Wayne Goodridge ¹

Affiliations
1 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, W.I, IN

Abstract

Dynamic Adaptive Streaming over HTTP (DASH) has revolutionized multimedia content delivery, enabling efficient video streaming over the internet. One-shot learning, a machine learning paradigm that allows recognition of new classes or objects with minimal training examples, holds promise for enhancing DASH systems. In this comparative study, we present a taxonomy-based analysis of one-shot learning techniques in the context of DASH, examining four taxonomies to provide a comprehensive understanding of their applications, evaluation metrics, and datasets. The first taxonomy focuses on categorizing one-shot learning techniques, including siamese networks, metric learning approaches, prototype-based methods, and generative models. This taxonomy reveals the diversity of techniques employed to tackle one-shot learning challenges in DASH environments. The second taxonomy explores the applications of one-shot learning in DASH. It highlights areas such as video quality prediction, buffer management, content adaptation, and bandwidth estimation, shedding light on how one-shot learning can optimize streaming decisions based on limited or single examples. The third taxonomy addresses evaluation metrics for one-shot learning in DASH. It encompasses accuracy-based metrics, generalization metrics, latency-related metrics, and robustness metrics, providing insights into the performance and effectiveness of one-shot learning approaches under various evaluation criteria. The fourth taxonomy delves into dataset characteristics for one-shot learning in DASH. It categorizes datasets into synthetic datasets, real-world datasets, transfer learning datasets, and unconstrained datasets, enabling researchers to select appropriate data sources and evaluate one-shot learning techniques in diverse streaming scenarios. By conducting this taxonomy-based analysis, our study provides researchers and practitioners with a structured framework for understanding and comparing different aspects of one-shot learning in DASH. It highlights the strengths, weaknesses, and potential applications of various techniques, offers guidance on evaluation metrics, and showcases dataset characteristics for benchmarking and future research. Ultimately, this comparative study aims to foster progress in one-shot learning for DASH by facilitating knowledge exchange, inspiring new research directions, and promoting the development of efficient and adaptive multimedia streaming systems over HTTP.

Keywords

DASH, One-Shot Learning, Taxonomy, Framework.

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Koffka Khan ¹

Affiliations
1 Department of Computing and Information Technology, St Augustine, University of the West Indies, JM

Abstract

As the demand for immersive experiences continues to surge, 360 Virtual Reality (VR) video streaming has emerged as a captivating medium. This review paper delves into the dynamic intersection of 360 VR video and cloud computing, exploring the advancements, challenges, and future prospects within this evolving landscape. Beginning with an introduction to the significance of 360 VR content, we navigate through the historical evolution of virtual reality and the fundamental principles of cloud computing. The paper elucidates the intricacies of 360 VR video capture and production, addressing challenges and technological breakthroughs. A critical examination of the role of cloud computing in video streaming services forms a pivotal section, encompassing discussions on architecture, protocols, and the optimization of cloud services for VR content. The unique challenges posed by 360 VR video streaming, including high bandwidth demands and latency considerations, are dissected, offering insights into the complexities of delivering immersive experiences in real-time. Furthermore, the paper scrutinizes existing cloud-based solutions and technologies dedicated to 360 VR video streaming. From streaming protocols to adaptive bitrate technologies, the review encapsulates the state-of-the-art developments in the field. Quality of Experience (QoE) and user perceptions are explored to gauge the impact of 360 VR video streaming on user engagement. In forecasting future trends, the paper discusses emerging technologies, ongoing research endeavors, and potential innovations that promise to shape the future of 360 VR video streaming in the cloud. The conclusion synthesizes key findings and emphasizes the integral role of cloud computing in advancing the realm of immersive video experiences. This comprehensive review aims to serve as a valuable resource for researchers, practitioners, and enthusiasts navigating the dynamic landscape of 360 VR video streaming and cloud-based solutions.

Keywords

360 Virtual Reality (VR), video streaming, cloud computing, bandwidth, immersive experiences.

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