INVESTIGATING QUALITY OF SERVICE ISSUES FOR VIDEO TRAFFIC OVER THE INTERNET
There is a rapidly growing demand for multimedia applications over the internet, and with it, the need to bolster the quality and efficiency with which they can be available. Video traffic presents a singular technical challenge because of the sheer size of such traffic, associated applications and the effects on other forms of traffic, Dar & Latif (2010). Bandwidth utilization is an important problem, whose resolution lies at the heart of the efficiency of the internet, which is why the core role of the QoS is to resolve congestion issues. This is particularly significant for assured traffic. In order to ensure QoS, multiple technologies have been, or are being developed to solve a range of issues from queueing, scheduling, prioritization, discrimination between different forms of traffic, transmission and reception, security of the data while in transmission, network configurations and infrastructure among others, Jaffar, Hashim, & Hamzah (2009). This paper seeks to investigate the quality of service (QoS) for video traffic over the internet, as well as understanding the varied issues associated with the implementation of varied technologies. In order to achieve this, the paper conducts an analytical analysis of the available theoretical and empirical research evidence on QoS frameworks, and the implementation of these frameworks in multiple contexts.
Overall Motivation. 9
CHAPTER ONE. 10
1.0 QUALITY OF SERVICE (QoS) 10
1.1 Converged Network QoS. 11
CHAPTER TWO.. 12
2.1 Video QoS for Multimedia Consumer Terminals 12
2.2 Guaranteeing QoS for Video-on-Demand. 14
2.3 Issues of Implementation of VoIP with QoS. 15
2.4 QoS for Converged Data and VoIP Networks 16
2.5 QoS Video Traffic Management in Mobile Phones 18
2.6 Traffic Prioritization in Switched LANs 19
2.7 Video Prioritization over Ad Hoc Wireless Networks 20
2.8 The Impact of Security on VoIP Call Quality. 20
CHAPTER THREE. 22
3.0 QoS Frameworks 22
3.1 Over Provisioning. 23
3.2 Resource Management 24
3.2.1 The Resource Reservation Signaling Mechanism.. 24
3.2.2 Traffic Policing. 28
3.2.3 Admission Control 34
3.2.4 Policy Control 37
3.2.5 Bandwidth Brokerage. 38
CHAPTER FOUR 39
4.0 Routing and Traffic Engineering. 39
4.1 QoS Routing. 39
4.2 Multi-protocol Label Switching (MPLS) 40
4.3 Label Distribution Protocols (LDP) 41
CHAPTER FIVE 41
5.1 Video QoS in DiffServ-Aware Multiprotocol Label Switching Network. 43
5.2 Data Path Framework/Mechanisms 46
5.3 Queuing Management 48
5.4 Scheduling. 51
CHAPTER SIX 56
6.1 Over-provisioning. 56
6.2 IntServ and DiffServ. 58
6.3 DiffServ Solves Over-provisioning & IntServ Difficulties 59
6.4 MPLS. 65
6.5 Queue Management and Scheduling. 67
6.6 Routing, Policy Control and Data Path Mechanisms 69
7.0 Frameworks to Mitigate the Shortcomings of Current QoS Technologies 69
7.1 Congestion Control Requires Scalable Data Algorithms 70
7.2 TEAM TE Automated Manager 72
7.3 DiffServ MPLS TE. 74
References LIST. 81
List of figures
Figure 2: RSVP and RESV Message PATHs 28
Figure 3: Resource Reservation and Signaling Mechanism, Davidson, Fox, & et al (2002) 29
Figure 4: IntServ, DiffServ and Best Effort 31
Figure 1: Service bucket, adapted from Zhao, Olshefski, & Schulzrinne (2009) 33
Figure 5: Leaky Bucket Mechanism of Traffic Policing. 34
Figure 6: Token Bucket Traffic Policing Mechanism.. 36
Figure 7: Effectiveness on Admission controls on QoS, adapted from Ergin, Gruteser, Luo, Raychaudhuri, & Liu (2008) 39
Figure 8: Policy Architecture (Zhao, Olshefski, & Schulzrinne, 2009) 41
Figure 9: Planes of IMS and QoS as well as the Signaling Paths for ISP. 49
Figure 10: Data Paths and Queuing. 50
Figure 11: The initial packet of a frame receives a deadline towards the beginning of the actual clock cycle, with the last receiving a deadline that is equal to the clock and the inter-frame time. 54
Figure 12: packet Isolation & Scheduling. 55
Figure 13L Classification of Schedulers 56
Figure 14: Priority Scheduling. 57
Figure 15: Strict Priority. 58
Figure 1: A simple SVA Architecture. 73
Figure 2: TEAM Traffic Engineering. 75
Figure 3: the TEAM Architecture, based on the SVA Architecture. It is adapted from, Chakraborty, Sanyal, Chakraborty, Ghosh, Chattopadhyay, & Chattopadhyay (2010) 76
Figure 4. 78
Figure 5: Lack of resources can force LSPs to take the longest paths 80
The internet revolutionized the manner in which people communicate, and the revolution has in turn created new needs and technical challenges for the continued, efficient and secure provision of services. The rising demand for multimedia applications i.e. video, audio, images in addition to the conventional types of data that are distributed and involve both communication and networking has presented with greater demand-driven challenge that requires urgent measures to solve them. Given the demand, the appetite for meeting these challenges is high, despite the need to keep costs, access, ease of use and the need to respect protocols such as IEEE 802.1p, Wang, Mai, Magnussen, Xuan, & Zhao (2009). Video and audio represents one of such multimedia applications that have rapidly gained ground especially with the emergency of e-commerce, e-learning, virtual companies, social media and other general communication needs. Video and audio traffic has imposed massive strains on the existent bandwidth and other network resources. Multiple efforts have been proposed or already implemented to help with the alleviation of the problem, including elimination of congestion especially for assured traffic. Thus far, QoS efforts have sought to not only increase the available capacity, but crucially to efficiently management the available resources in order to ensure efficiency, Bless & Rohricht (2010). Chapter One, introduces QoS basics, including the definition as well as the emergent technical and practical difficulties presented by converged networks. Chapter presents the literature review, which includes video QoS for multimedia consumer terminals, guaranteeing QoS, VoIP implementation, VoIP networks, traffic prioritization, QoS in mobile phones and switched LANs. Chapter three presents the QoS frameworks, including over provisioning, resource management and traffic engineering. It includes admission control, traffic policing, policy control and bandwidth brokerage. Traffic engineering is discussed in chapter four, and it includes QoS routing, Multi-protocol Label Switching and label Distribution Protocols. Chapter five offers QoS protocols in practice, along with more frameworks, key of which is scheduling and queuing.
BACKGROUND: MULTIMEDIA QoS REQUIREMENTS
New Age in Communication
Social media, video conferencing, e-commerce, e-learning and other communication requirements have made internet traffic more and more towards multimedia. The technological improvements have made it possible for voice to be transmitted over the internet, which has in turn facilitated internet telephony and other emergent technologies such as video conferencing and video streaming, Dar & Latif (2010). While it still struggles with quality and efficiency issues, VoIPs potential has ensured that it rivals PSTN. It is basically a communication form that differs from circuit switching, which arose after it was realized that it was technically possible to voice could also be digitized and sent over a network, Nisar, Hasbullah, & Said (2009). The nature of multimedia traffic is substantially different from the conventional data applications. The differences include variations in data rates, reliability, delays, user expectations and communication modes, coupled by the requirement to have integrated services for varied types of media over a single network. Video and audio services have multiple variations in the requirements during their transmission, which makes it is imperative that networks have the capacity to meet the equally different needs of this traffic. Some of the technically important differences, which this paper seeks to increase the understanding of, as well as exploring the existent solutions include the following:
The conventional data applications result in bursty traffic i.e. the actual time and volume of demand for network resources is not only difficult to predict, but also characterized by significant variations, DeCusatis & Jacobowitz (2006). In addition, there is no known idea of the required data rate that can be associated with sessions or sources, which makes it difficult to plan and accommodate the demand in an efficient manner. This is not least because the design of networks builds on ability to share bandwidth. Contrary to conventional traffic, video and audio traffic is stream-oriented, which necessitates that there a continuous flow of information at a given rate of data. This requires a certain amount of bandwidth must be dedicated to the transmission of video traffic, while at once supporting several concurrent streams that would make the aggregate bandwidth requirements considerable and potentially disruptive to other traffic, if they are not managed well. The rates of data that are associated with streams may vary significantly according the media type, the data compression technology used as well as the desired level of quality. For instance, digitized voice has a data rate of 64Kbps if they use The Pulse Code Modulation, while if differential encoding technologies are used, it is possible to achieve multiply lower data rates, Sulaiman, Carrasco, & Chester (2008).
Data applications require and can easily achieve complete reliability, especially because of the lack of explicit latency needs, which makes it possible to attain reliability as the transport layer through effective error detections and retransmissions of the damaged packets. Video and audio traffic applications have an acceptable level of packet losses for practical reasons i.e. due to buffer overflows transmitting and receiving stations or in the routers and switches, Bless & Rohricht (2010). Losses also occur at the MAC layer due to excessive collisions and end-to-end delays beyond the highest latency requirements that forces data packets to be dropped. Packet losses result in markedly poorer quality of the output or glitches, Chiu, Huang, Lo, Hwang, & Shieh (2003). The acceptable amounts of information losses is dependent on the media involved, user expectations, the compression scheme adopted and the type of application in use.
Traditional applications do not have particular network delays, despite the fact that fast responses are naturally desirable. Delays are simple inconveniences that cause slowed, but harmless application execution. In multimedia applications, any such losses in data cause massive quality degradations, which have in turn necessitated the setting of acceptable data losses, beyond which an application would abort the entire data received, Bless & Rohricht (2010). End-to-end delays are described as the duration taken between the generation and reception of data, and it must be defined so that the quality of the audio or video is meaningfully interactive etc. This is high in interactive media and relatively lower for one-way Video-on-Demand applications (VoD). The fact that video conferencing involves geographically-dispersed users, the networks are like to comprises of wide area backbone and local area networks, making the expected delays to under 20ms for interactive video and audio. Video-on-Demand allows delays of up to 1 second from the moment the data is dispatched to the moment it is received as output.
Data applications are supported by one or multiple networks producing traffic that has the same characteristics, which implies that differentiation is impossible among the varied applications. Multimedia data is different because by its very nature, it comprises of differentiated media and types of information, which naturally presents traffic with varied characteristics, have varied traffic characteristics and require different network services. According to Bless & Rohricht (2010), the fact that multimedia data uses a considerable amount of network resources, and a lack thereof results in unacceptable delays, the proper management of the traffic and other network resources in order to ensure continued availability of network resources, both for the multimedia traffic as well as the traditional data types. This is especially critical because of the bursty nature of traffic, which can results in traffic jams that in turn cloak the entire network resources leading to extremely poor quality as well as transmission failures in the case of excessive delays. Multimedia traffic can only be efficiently handled if networks can accommodate differentiated treatment of different data types, Badard, Diascorn, Boulmier, Vicard, Renard, & Dimassi (2001).
Conventionally, communication was basic, comprising of point-to-point, multi-cast traffic that represented a comparatively low volume, which could be handled by either sending a single copy to every destination or through broadcasting of the data to the host applications that in turn filter the data appropriately. The majority of multimedia applications involve multipoint communications, which comprises point-to-multipoint communication such as television broadcasting as well as multipoint-to-multipoint as in the case of virtual collaborative projects and video conferencing. The rates of data in multimedia are considerably higher than in data applications, there is massive inefficiencies in the use of network resources at presents (DeCusatis & Jacobowitz, 2006). Broadcasting of multicast traffic for instance results in the cloaking of the network for other date types.
It is crucial to understand the available technologies, technical possibilities and the existent or future potential of efficient video traffic over the internet, especially with the growing demand across the world. This paper will seek to accomplish precisely this, by reviewing their theoretical and practical research evidence from leading academics and technical practitioners across the world. In addition, this study will seek to increase the understanding of varied concepts of Quality of Service and its application to not only video, but also multimedia traffic as a whole. It is the intention of this paper to highlight not only the existent research efforts, but perhaps most importantly, to highlight possible breakthroughs towards achieving greater video QoS and efficiency. In order to do this, the paper includes a wealth of theoretical and experimental research into possible technologies that could become useful in this area of study.
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