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«End-to-End QoS Provision over Heterogeneous IP and non IP Broadband Wired and Wireless Network Environments A dissertation submitted in satisfaction ...»

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(1) The Local Bearer Service, (2) the UMTS Bearer Service that bridges the gap between core network bearer service and the radio bearer service and also takes account of user profiles and mobility and (3) the External Local Bearer Service that connects the core network service to an external network, e.g. an IP DiffServ network. These bearer services have their own QoS attributes, some of which may be shared. Each UMTS bearer service is characterized by a number

of attributes. The most important attributes are:

• Traffic class - The UMTS QoS architecture defines four QoS classes. The Conversational and Streaming classes are both designed to meet the needs on real-time applications, while Interactive and Background classes refer to those only needing a best-effort response. The main attribute that seperates these QoS traffic classes are the connection delay, the bit-rate and the nature of traffic [17, 18].

• Maximum Bit Rate - Indicates the maximum number of bits that a UMTS bearer can deliver to service access points (SAP) in a specified interval. It is required in order to reserve radio resources. It limits the peak transient rate that can be supported, and controls selection of the appropriate peak rate for an application that can operate at a number of speeds.

• Guaranteed Bit Rate - Indicates the number of bits that UMTS guarantees to deliver to a SAP in a specified time. It specifies the minimum required resources and is used to support admission control.

• Traffic handling priority - Indicates the relative importance of handling all the service data units (SDUs) on one bearer as compared to another. It is mainly used for scheduling different types of interactive traffic.

• Allocation/retention priority - This is used to discriminate between the bearers when allocation or retaining scarce resources are used. It is a subscription attribute rather than something that can be negotiated by the mobile network.

2.5.4 802.11e QoS support IEEE 802.11 is the wireless local area network (WLAN) standard developed by the IEEE LAN/MAN Standards Committee (IEEE 802) in the 5 GHz and 2.4 GHz public spectrum. It is considered as the root standard, defining operation and interfaces at MAC and PHY for data networks such as the popular TCP/IP.

An unaccountable number of devices are based on this standard, making IEEE

802.11 the most widely used WLAN technology today.

Various amendments have been made to the original standard since 1997.

The most popular are IEEE 802.11b, 802.11g (in the 2.4 GHz band) and 802.11a (in the 5 GHz band) protocols. The basic 802.11 MAC layer uses Distributed Coordination Function (DCF) to share the medium between multiple stations. It is based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) in principle. As can be noticed, the DCF has no notion of high or low priority traffic at the MAC, which is necessary to permit some level of QoS to the traffic traversing the WLAN. This led to amendment in the form of IEEE 802.11e [1] that defines a set of QoS enhancements for IEEE 802.11 and has been approved as a standard as of late 2005. The standard is considered of critical importance for delay sensitive applications such as voice over IP (VoIP) and streaming multimedia. The protocol also addresses some fairness issues as observed in DCF.

IEEE 802.11e introduces QoS support through a new coordination function:

the Hybrid Coordination Function (HCF). The HCF defines two medium access mechanisms that are referred to as: (i) the contention-based channel access and (ii) the controlled channel access. The contention-based channel is referred to as Enhanced Distributed Channel Access (EDCA) whereas the controlled channel access is referred to as HCF Controlled Channel Access (HCCA). Both EDCA and HCCA define access categories (ACs). With IEEE 802.11e, there may be two phases of operation within a superframe, i.e. Contention Period and Contention Free Period. The EDCA is used only in the CP while the HCCA is used in both phases.

EDCA is the basis for the HCF. The QoS is realised with the introduction of AC. MAC Service Data Units (MSDU) are delivered through multiple backoff instances within one station, each backoff instance parameterised with AC-specific parameters, called the EDCA parameter set. In the CP, each AC within the stations contends for a transmission opportunity (TXOP) and independently starts a backoff after detecting the channel being idle for an Arbitration Interframe Space (AIFS). The AIFS can be different for each AC. After waiting for AIFS, each backoff sets a counter to a random number drawn from the interval [1,CW+1], where CW is the contention window. The minimum size of the contention window is another parameter dependent on the AC (CWmin[AC] ).

There are four ACs, thus, four backoff instances exist in each IEEE 802.11e

station. The ACs are labeled according to their target application, i.e. AC VO (voice), AC VI (video), AC BE (best effort), AC BK (background). This corresponds to one transmission queue for each AC, realised as virtual stations inside a station, with QoS parameters that determine their priorities. If the counters of two or more parallel ACs in a single station reach zero at the same time, a scheduler inside the station avoids the virtual collision. The scheduler grants the TXOP to the AC with the highest priority, out of the ACs that virtually collided within the station. Note that it is still possible that the transmitted frame collides in the wireless medium with a frame transmitted by other station.





2.6 Mapping application semantics to network semantics

Different levels of QoS involve different trade offs between QoS guarantees and resource utilization. Towards the design of a system that both obtains to maximize the utilization of network resources, and to guarantee different levels of QoS, a basic two steps process is required. At a first step, the application’s QoS requirements of the services to be run over the network have to be identified. At the second step, these requirements have to be mapped to network ones. The

most important QoS application performance parameters are:

1. Latency (delay and delay variation): Delay is the time elapsed while a data unit travels from the source to destination. It can also be from a network ingress to network engress, when we are dealing with different network domains. Real time multimedia streaming applications are delay and delay variation (jitter) sensitive because the transmitted information has to be played back at the receiver side in real time, or almost in real time. QoS can be specified in different parameters/characteristics including average

delay, variance average delay and delay bounds.

2. Packet Loss Rate (Reliability): Packets can be lost in a network because they may be dropped when a buffer in a network device overflows. From the real time application perspective a packet arriving at the destination after a certain time delay, making it useless, is counted as lost. It is difficult to set an absolute bound on the packet loss rate that cannot be exceeded under any circumstances. It is more common to set a specific packet loss rate dependent on the packet loss recover or protection schemes employed by the application entities. Note that the packet loss effect is not strictly proportional to the multimedia bit stream service quality.

3. Throughput (bandwidth): Throughput reflects the amount of information a network is able to deliver during a certain time interval. Higher throughput results in better quality of service in general. It is not appropriate to consider throughput as a direct QoS parameter for highly burst trafc such as encoded Variable Bit Rate (VBR) video, for which throughput changes drastically during time. For application VBR traffic, the actual throughput quantity may not be interesting, as long as the information can be delivered reliably in a timely fashion, for playback in real time. Also, it is neither necessary nor affordable for VBR applications to reserve the peak rate bandwidth in order to present a desired throughput requirement and thus to guarantee QoS. The effective bandwidth [19] or the minimum throughput rather than the peak rate is more used.

FGS provided by MPEG-4 is an efficient solution of content adaptation to undelying network characteristics and heterogeneity, in which the base layer is aimed to provide the basic visual quality in order to meet the minimal bandwidth requirements. The enhancement layer can be truncated to meet the heterogeneous network conditions. Another approach to content adaptation at a first stage is to use Object Based Compression features provided by MPEG4. In this case, the video quality is adapted by adding or dropping objects and their associated layer according to the network state. Objects are encoded separately providing the advantage that one object is not prevented from being decoded if another one is not received. The two subsections below describe these approaches, their advantages, how they differ and relate to each other and where they fit into networks that support DiffServ architecture.

2.7 Available QoS Architectural Framework This section presents a number of state-of-the-art leading-edge frameworks in which applications and the network can cooperatively maintain and optimize end-to-end QoS.

The authors in [9] provide a QoS mapping framework based on relative differentiated version of the IP DiffServ model. They have proposed a RPI-based video categorization and effective QoS mapping under a given cost constraint. The RPI has the major bridging role in enabling the network to be context-aware and provides delivery of packets with QoS requirements information associated with their contents. This results in better end-to-end video quality at a given cost. They also suggested practical guidelines for effective QoS mapping based on categorized RPI. In this approach, the differentiation of loss rates was only performed. Thus, it must be extended to also cover delay/jitter bounds. Combined loss rate/delay will provide a more comprehensive characterization of multimedia content, not only for the video stream itself but also among various kinds of multimedia trafc. By summarizing loss rates and delay priorities in the DS byte of the packet

header, more enhanced, content dependent forwarding will be feasible.

The authors in [20] provide a framework for dynamic QoS mapping control for real time multimedia applications including feedforward and feedback QoS control at a special-purpose node that they call continuous media gateway (CM Gateway). This research extends the limitation of per-flow based feedforward QoS mapping, using three layers of granularity (packet-based, session-based and class-based). This process combines the two approaches to QoS mapping control, the feedback and feedforward.

A framework for rate adaptation, prioritized packetization and differentiated packet forwarding is proposed for MPEG FGS video streaming [21]. One differentiated forwarding framework of error-resilient MPEG4 FGS video was investigated with fine-granular Base Layer and Enhancement Layer packet prioritizing.

Starting from the real distortion of each packet, they showed the gains of priority dropping over uniform dropping under different encoding and packetization parameters. A couple of issues are still open. First the mapping of both BL and EL packets to the DS level is very heuristic. Second, it is not clear how they exploit the maximum gain by mapping packets from different streams to different DS levels if multiple MPEG4 FGS packets are multiplexed. Finally, the current service model must be extended to cover rate adaptation, packet filtering and differentiated services in more complicated scenarios.

The authors in [22] propose an extension to the MPEG-4 System architecture with a new ”Media QoS Classification Layer” in order to provide automatic and accurate mapping between MPEG-4 Application-Level QoS metrics and underlying transport and network QoS mechanisms such as IP DiffServ. This ”Media QoS Classification Layer” makes use of a neural network classification model to group multimedia objects of a scene with same QoS requirements to create elementary video streams that are subsequently mapped to IP DiffServ PHB. These MPEG-4 Audio Visual Objects (AVOs) are classified based on application-level QoS criteria and AVO semantic descriptors according to the MPEG4 QoS descriptor. Thus, MPEG-4 AVOs requiring the same QoS from the network are automatically classified and multiplexed within one of the IP DiffServ PHB (Per Hop Behaviors). Object data-packets within the same class are then transmitted over the selected transport layer with the corresponding bearer capability and priority level. Performance evaluation results showed better protection of relevant video objects of a scene during transmission and network congestion.

Authors in [?] propose an architecture for end-to-end QoS control in a wiredwireless environment with effective QoS translation, proper control management, and dynamic SLA-based resource provisioning. They achieve this in the proposed CUE framework, which is an extension of the CADENUS architecture. To derive all the benefits of the CADENUS framework, the CUE architecture adds two new components, CUESM and CUE-RM, that can be used to provision end-to-end QoS in a wired-wireless network. The proposed framework makes use of dynamic QoS arbitration, by using PDP context activation/modify messages, which can be changed in real-time session. Ongoing research involves a thorough study of wired-wireless QoS interworking issues through simulations, and a practical performance evaluation of the framework over our testbed.



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