Studying of different parameters that affect QoS in IPTV systems

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1 Studying of different parameters that affect QoS in IPTV systems ARIANIT MARAJ 1, ADRIAN SHEHU 2, ROZETA MIHO MITRUSHI 3 Telecommunication Department Faculty of Information Technology, Polytechnic University of Tirana Prishtina, Republic of Kosova 1 Tirana, Republic of Albania 2, 3 arianit.maraj@ptkonline.com, adshehu@tcn.al, rmiho@fti.edu.al Abstract: - Quality of Service (QoS) has become major criteria to implement IPTV services. Increasing QoS is seen today as one of the most important means for increasing subscribers' loyalty and securing successful service growth. The majority of content delivery network deployments are designed with highly reliable components and numerous degrees of redundancy, thus it is yet impossible to completely eliminate all potential network-level failures. To satisfy QoS requirements for delivering IPTV services we should study parameters that affect directly to the QoS. Here we will consider three parameters: jitter, losses and delays. For transmitting different services which are sensitive in QoS, it is desired to design some controlling mechanisms for solving different problems that might occur in network in case of delays, losses etc. These problems usually occur in bottleneck links, where it is needed better link utilization. Because of complex nature of controlling mechanisms it is desired to design intelligent controlling techniques. One of the intelligent techniques that would be present in this paper is Fuzzy Logic Controller (FLC). In this paper we will design FLC using Matlab software. As input parameters will be three parameters mentioned above, whereas as output parameter will be link utilization. It is well known that the link utilization is one of the most important parameters for congestion avoidance and control mechanisms, thus avoiding congestion we will increase QoS. The aim is to obtain better values of link utilization using different rules from Rule Editor and using appropriate defuzzification method. Key-Words: - IPTV, QoS, Fuzzy Logic Controller, jitter, loss, delay 1 Introduction There are a number of techniques as to how QoS can be implemented in an operator s network: (1) Overprovisioning; (2) Integrated services (Intserv); (3) DiffServ (with or without MPLS). The Intserv model has its well-known scalability problems. Using only over provisioning technique, it is quite expensive and not appealing for some operators. In addition, without differentiated services it is difficult to use different overprovisioning ratios per service class. Selective prioritization of high priority traffic -class would make the over-provisioning factor only applicable for that class. The best solution is to combine over-provisioning of bandwidth to minimize the long-term average level of congestion, while also deploying DiffServ to address the requirements of delay, and jitter sensitive traffic during short-term periods of congestion. It is only by using a combination of technologies being able to support a portfolio of differentiated services on a large scale, with high QoS and at a reasonable cost. Service transport over IP has a number of issues that must be carefully considered when designing an IP network. The network must have low latency, jitter and low percentage of packet loss. It should have enough bandwidth allocated for each service, especially for IPTV services. IPTV is used to transmit digital television via broadband connections using Internet Protocols. IPTV is designed to send streams of video programming to each costumer. These streams are continuous each customer can select the stream they want to view. This process is functionally identical to the programming delivered by local broadcasters [1]. IPTV service is transmitted through telephone lines and this is the reason why telephone companies are in the first position for offering IPTV to the customers. Preserving video quality in IPTV networks that rely in copper access lines is a big challenge for operators. Service providers need intelligent mechanisms in core and in distribution networks to offer IPTV services. IPTV service providers receive content in different formats and from different sources. Through IPTV technology all of these formats should be converted in IP format in order to be transmitted to customers as service with high quality in the same IP network. In this paper it is described IPTV technology, IPTV services [2], QoS requirements for IPTV services, network parameters and their effect in QoS. A special attention is paid for the main branch of soft computing fuzzy logic and design of intelligent controllers based on fuzzy logic. Finally, it is made a simple analysis using rules from Rule Editor (Matlab software) for providing better link utilization for delivering IPTV services through bottleneck links. ISSN: ISBN:

2 2 IPTV technology and services For offering IPTV services the network should be prepared for supporting some specific protocols for signal stream processing. The main reason for using these protocols is that the bandwidth demands are increasing from day to day. Bandwidth limiting is critical in copper lines. So, it is needed to use some intelligent compressed techniques that are specified by some international standards for telecommunication. The main techniques for video compression are MPEG [3] (moving pictures expert groups) techniques. Usually, for video compression is used MPEG-2 TS (for transport stream) and MPEG-4 (for aggregated streams). Also it is needed to use audio compression protocols such as MPEG-1 audio, DOULBY digital etc. The equipment in access network must support IGMP [4] snooping. IPTV technology is based in 4 main layers (see Figure 1) [5]: Services (Video head end, internet, VoIP etc), Edge/core and aggregation, Access network and Home network. Figure 1. General centralized architecture for offering IPTV services Video head end receives content from different sources and transforms it into appropriate form for transmission through IP network. This content can be mix of national and local TV programs, advertisements, satellite content and interactive video services. Video head end encompass broad range of heterogeneous technologies. Internet and VoIP are not the scope of this paper. The video head end is comprised from: - Satellite antenna farms which receives broadcast analog and digital TV content, - Terrestrial antennas for receiving national content from different TV providers, - Cable TV receivers which receive content from CATV providers and live TV content in different formats from studio. IPTV head end collects different formats of content from different sources and prepares it for transmitting in IP format. The equipments which convert different formats of content into IP format are: Video encoders- encode content in MPEG-2 and MPEG-4/H.264 and transmit it into IP network. Audio encoders-encode audio in multiple formats MPEG-1, Dolby Digital 2.0 Audio etc. The edge/core and aggregation nodes are based on feature rich BSR (broadband service routers) and BSA (Broadband service aggregator) supporting all standardized protocols for IP/MPLS/Ethernet networks, guaranteeing QoS and respecting data traffic security for offering triple play services. Access network: contains nodes which are broadband multiservice access nodes (BSAN). These nodes enable delivering of broadband services (IPTV, HIS, VoIP), with QoS guarantees through wireline (ADSL, FTTH) or wireless (WiMAX) connections. Home network: contains home equipments (STB, residential Gateways, modems, TV set etc). These equipments enable conversation of IP packet format into analog or digital TV signals. IPTV services: There are a lot of services that IPTV technology can offer: VoD content/movies: Video on demand [6] allows users to select and view to video on demand. VoD content that can be transmitted through IPTV platform includes a library with movie titles, music on demand etc [7]. Pay per view or subscribe VoD: service which offers consumers access to one or more VOD movies for a subscription. PVR-personal video recorded: The personal video recorded (PVR) must allow the end-user to record broadcast content. The service mimics recording of broadcast TV channels in video cassette recorders (VCR). Network PVR- Network recording: NPVR is a PVR service where content is recorded on service provider equipment (VoD servers). Service must be activated per subscriber, and must support quota to limit amount of recorded content. Teletext for SD Live TV Channels: contain embedded teletext information (VTI) Picture- in- Picture: The Picture-in-Picture (PIP) service enables the end-user to bring up an additional broadcast channel in an overlay window to create a picture-in-picture. 3 QoS challenges for offering IPTV service; bandwidth requirements IPTV services require very strict QoS guarantees [8]. The most challenging issue for offering IPTV services is ISSN: ISBN:

3 ensuring quality of service and QoE (Quality of Experience). QoS is fundamental in every system, especially in systems that are characterized with limited capacity. According to ITU-T E.800, QoS is defined as the collective effect of performance which determines the degree of satisfaction of a user of the service. In IPTV systems the QoS is a measure of performance of system itself. QoS mechanisms can be implemented at different levels. For example at the network level it includes traffic management mechanisms such as buffering and scheduling employed to differentiate between traffics belong to different applications. Other QoS mechanisms at levels other than the transport include loss concealment, application forward error correction (FEC), etc. [8] There are a lot of parameters that affect directly QoS in IPTV systems. In this paper we will use the most important parameters: jitter, delays, and losses. Operators must deliver broadband services with high QoS (IPTV, VoIP, HIS-High speed Internet) to any user at any time in the most efficient and cost effective way. To achieve this, operators must use a variety of access technologies including [9]: FTTx technology, DSL technology, Carrier Ethernet, WiMAX technology. Bandwidth is the most important parameter for offering services with high QoS. Thus, in order to manage bandwidth usage we should use some compression techniques. As we know there are different MPEG compression methods for offering IPTV service. The most common methods used in IPTV systems are MPEG2 and MPEG4. Bandwidth requirements for offering one TV channel with MPEG-2 compression methods are: MPEG-2 SD 4 Mbps MPEG-2 HD Mbps Whereas, bandwidth requirements for offering one TV channel with MPEG-4 compression methods are: MPEG-4 SD 2 Mbps MPEG-4 HD 8 Mbps These requirements for broadband dictate the needs for using broadband access technology. The best case is using FTTH (or FTTU-Fiber to the User). In rural areas this wireline technology is very expensive, so in these areas it is more appropriate to use wireless access broadband technology such as WiMAX [10]. 4 Analysis of QoS parameters that affect IPTV using FLC As we have mentioned above, for IPTV QoS analysis we will use FLC as intelligent controlling technique. A Fuzzy Logic Controller [11] is a rule based system in which fuzzy rule represents a control mechanism. In this case, a fuzzy controller uses fuzzy logic to simulate human thinking. In particular the FLC is useful in two special cases: [12] - When the control processes are too complex to analyze by conventional quantitative techniques - When the available sources of information are interpreted qualitatively or uncertainly. Fuzzy logic controller consists of: fuzzifier, rule base, fuzzy inference and defuzzifier (see Figure 2). Fuzzifier: A fuzzifier operator has the effect of transforming crisp value to fuzzy sets. Fuzzifier is presented with x=fuzzifier(x 0 ), where x 0 is input crisp value; x is a fuzzy set and fuzzifier represents a fuzzification operator. Rule-Base (Linguistic Rules): Contains IF-THEN rules that are determined through fuzzy logic. Example: if x is A i and Y is B i the Z is C i, Where x and y are inputs and z is controlled output; A i, B i and C i are linguistic terms, like: low, medium, high etc. Fuzzy Inference: Is a process of converting input values into output values using fuzzy logic. Converting is essential for decision making. Fuzzy Inference process includes: membership functions and logic operations Defuzzifier: can be expressed by: y ou =defuzzifier(y), where y identifies fuzzy controller action, y ou identifies crisp value of control action and defuzzifier presents defuzzifier operator. Converting process of fuzzy terms in crisp values is called defuzzification. There are some defuzzification methods: COG (Centre of Gravity), COGS (Centre of Gravity for Singletons), COA (Centre of Area), LM (Left Most Maximum) and RM (Right Most Maximum). In our case, we will use COG (Centre of Gravity), being one of the most important methods. By the COG method, the defuzzified crisp output U is given: U Max u Min Max Min u u Where, U is deffuzification result, u = output variable, membership function, Min=minimum limit for deffuzification, Max=maximum limit for deffuzification. du du Fig.2. Fuzzy Logic Controller (1) ISSN: ISBN:

4 Fuzzy logic is based in membership functions. Membership functions are graphs that define how one point in the input space is mapped to membership values between 0 and 1. Input space is often referred as the universe of discourse or universal set (u), which contain all the possible elements of concern in each particular application [13]. 5 Design of FLC using MATLAB In this paper we will take as example the multiplexed IPTV queue system for transmitting 3 video sources which are transmitted through a common buffer and than multiplexed and transmitted through a common link (see Figure 3). As we know, QoS for offering IPTV is very strict, especially when we have bottleneck links. In this case we have to gain high link utilization. Video Sources Source 1 Source 2 Source 3 Pre- Buffers Common Buffer Link Destination Figure 3. The multiplexed IPTV queue system for 3 video sources For transmitting different services which are sensitive in QoS, it is desired to design some controlling mechanisms for solving problems that might occur in different cases such as: where we have delays, losses, jitter etc. Thus, it is desired to design some intelligent controlling mechanisms. Since the fuzzy logic is based in soft computing it is considered as intelligent. Fuzzy logic controller is based in Fuzzy logic. It is well known that FLC controller is convenient when we have more than 2 parameters in input. In non-intelligent controllers it is not possible to make precise analysis with more than 2 parameters in input. For real-time services, like IPTV broadcast television, the quality of the provided service is an important aspect. When the provided service quality does not satisfy the customer, the customer will not use the service. The minimum requirements for a specific service are typically defined as a Quality of Service or QoS level. QoS is often defined and enforced by network-based service level agreements by means of objectively measured network metrics like delay, jitter and packet loss [14]. To design FLC we will use IPTV metrics as input parameters at the FLC input. These input parameters can be with crisp or fuzzy values. Since the main disadvantages of for offering IPTV services consist in: loss, delay and jitter, then these three network parameters will be taken as input metrics. FLC processes these parameters through four steps: fuzzifier, fuzzy interface engine, rule based and deffuzifier. Figure 4. Fuzzy logic controller 3 parameters acting at the input of FLC The aim is to obtain better link utilization. Said on other words, it is required to make all possible combinations of these parameters in order to obtain better QoS. Networks of different types or in different topology have different theoretical peek value under general conditions. However, this doesn't mean that the higher network utilization is better. We must make sure there is no packet loss, jitter and delays when network utilization reaches a certain value. In our approach we try to get high bottleneck link utilization, more than 80% from link capacity (network resource). It is also important to define fuzzy membership function for input parameters. In this case we will use triangular membership functions. The table below presents input parameters in FLC and corresponding fuzzy sets to these parameters. Table 1. Network Metrics and Fuzzy sets Inputs Jitter Delays Losses Fuzzy Sets {Low, Medium, High}-ms {acceptable, tolerable, intolerable}-ms {acceptable, tolerable, intolerable}-% Based in table above for fuzzy sets of these input parameters, using MATLAB software we can draw membership functions for these metrics in IPTV network. Using this simple software program, the membership functions for jitter, delays, losses and output of fuzzy system are shown in figure as below (see Figure 5): ISSN: ISBN:

5 a) Jitter b) Packet loss After defining the membership function and input parameters, we also have to define fuzzy rules for relevant parameters. It is important to recognize that fuzzy sets are different from simple probabilities. The operations that are used to manipulate fuzzy sets have little in common with probability theory. Fuzzy logic is a subset of predicate logic, and the operators for fuzzy sets and for non-fuzzy sets are much the same. Logic operators are based on truth values that range from 0 (false) to 1 (true). When these logic operators are applied to non-fuzzy values, they give the same results as the familiar operators AND, OR, and NOT. An intersection element that has a degree of membership in Set A and a different degree of membership in Set B has the lesser value as its membership in the intersection set. This is an application of f-and (fuzzy-and) [15]. In this paper we will use AND operator, this means: a f- AND b = min (a, b). Some of fuzzy rules derived from Rule Editor (MATLAB software), using f-and operators are: Rule 1: IF (Jitter is Low) AND (Loss is Intolerable) AND (Delay is Acceptable) THEN (Output QoS is High=86.2 %) c) Delays Figure 6. Rule editor in MATLAB for Rule 1 Figure below shows in 3 D the surface viewer using COG method for this rule: d) Link utilization (Output QoS) Figure 5. Membership functions for inputs and output of FLC Figure 7. 3D view for rule 1 Rule 2: If (Jitter is High) AND (Loss is Acceptable) AND (Delay is Acceptable) THEN (QoS is Medium = 44.8% ) ISSN: ISBN:

6 Figure 8. Rule editor in MATLAB for Rule 2 Rule 3: If (Jitter is High) AND (Loss is Intolerable) AND (Delay is Intolerable) THEN (QoS is Low=13.9% ) Figure 9. Rule editor in MATLAB for Rule 3 Figure below shows in 3 D the surface viewer using COG method for this rule: Figure 10. 3D in MATLAB for Rule 1 For 3 rules, as defuzzification method we have used COG method. Conclusion It is well known that for satisfying QoS requirements for delivering IPTV services we should study parameters that affect directly to the QoS. In this paper we have analyzed three parameters: jitter, losses and delays. Taking into consideration 3 or more metrics it is hard job, but using soft computing it is possible. In this paper we have used one intelligent controller that is based in fuzzy logic. As input parameters that act in this intelligent controller we took three main parameters of IPTV network. The main part of FLC is defuzzifier that plays a key role for obtaining crisp values in the output. As e defuzzification method we used COG (Centre of Gravity) method. The aim is to define a maximum value of link utilization among links of the network, where link utilization is defined as the amount of bandwidth used by IPTV traffic demands transmitted through a certain link with respect to a total capacity of the link. The maximum link utilization is calculated as a percentage. After using these rules from Matlab, we will see that using Rule 1 and f-and operator we will get high link utilization (more than 85 %), this value is calculated for bottleneck links. For offering IPTV services, we need more bandwidth and in a case where the link capacity is limited, it is required to highly utilize the links for offering these services. That s why for offering IPTV services it is good idea to use Rule 1 in order to maintain these parameters as low as it is possible (jitter, delay and losses) for better link utilization. Analysis of these metrics are made with MATLAB software and these analysis show that Rule 1 from rule editor shows better results in aspect of link utilization (approximately 86.2%). References [1]. IPTV and internet Video-Copyright 2007, Elsevier Inc.- ISBN 13: [2] The state of IPTV 2006, new millennium research council, June 2006 [3] Introduction to MPEG; MPEG-1, MPEG-2 and MPEG-4 by Lawrence Harte (Paperback - Aug 21, 2006) [4] Introduction to IGMP for IPTV Networks- Understanding IGMP Processing in the Broadband Access Network - White Paper - Juniper Networks, Inc North Mathilda Avenue, Part Number: Oct 2007 [5] Skender Rugova, Arianit Maraj, Traffic load and cost analysis for different IPTV architectures, 8th WSEAS International Conference on Telecommunications and Informatics (TELE-INFO '09), Included in ISI/SCI Web of Science and Web of Knowledge ISTANBUL, TURKEY, May 30 - June 1, 2009 [6] Whitepaper IPTV/VoD: "The IPTV/VoD Challenge - Upcoming Business Models" By Jochen Altgeld1 and John D. (J.D.) Zeeman2- IBM Paper for the International Engineering Consortium (IEC) [7] Next generation IPTV services and technologies- Copyright # 2008 by John Wiley & Sons, Inc. New Jersey. [8] Mohammad Ahasan Habib - QoS evaluation of Bandwidth Schedulers in IPTV Networks Offered SRD Fluid Video Traffic, 2009, Master Thesis in Computer Engineering Reg. No: E3682D [9] Architecture of Mobile IPTV over the IEEE e Mobile WiMAX Network: A Survey Gary K. W. Wong,-TECHNICAL REPORTS, HKUST, JANUARY [10] Arianit Maraj, S.Rugova Analysis of routing metrics for offering IPTV over WiMAX using fuzzy logic JOURNAL Transactions: WSEAS TRANSACTIONS ON COMMUNICATIONS-2009, ISSN: [11] D. Driankov, H. Hellenndoorn and M. Reinfrank An Introduction to fuzzy Control, Springer Verlang, Berlin, New York, 1993 [12] K. H. Lee, Firs Course on fuzzy theory and applications [book], pages: , ISBN Springer Berlin Heidelberg NewYork, Springer-Verlag Berlin Heidelberg 2005 [13] Types of Membership functions article by nostalgia, edited & published by Ricky on September 15, 2009 [14] Bruce Chen- Simulation and analysis of quality of service parameters in IP networks with video traffic, 2002 SIMON FRASER UNIVERSITY, May 06, 2002 [15] ISSN: ISBN: