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Quality-Aware Service Model Single autonomous service –Set of functions –Input data Output data Vectors of QoS parameter values Using resourses, e.g., CPU, MPU, memory, transport capacity Composite service –End-to-end QoS guarantees –Distributed –Sequence of autonomous services, independent operations, such as Transformations, synchronization, filtering –Can be connected into a Service graph e.g., an directed acyclic graph (DAG) –Inter-service satisfaction relation

Resources A resource is a system entity required by tasks for manipulating data Characteristics: –active/ passive –Shared or exclusive use –Single or multiple resources –Resource capacity Processor, network, memory

Resource Management Delivering QoS for an integrated distributed multimedia system: –Resource allocation –System resource management Establishment phase Runtime phase

Requirements on Resource Management Throughput Delay –Local –End-to-end Jitter –Determines the maximum allowed variance in the arrival data at the destination Reliability –Mapping to error handling algorithms

Model for Continuous Stream Linear Bounded Arrival Processes (LBAP) –Distributed system decomposed into a chain of resources traversed by the message on their end-to-end path Message arrival process at a resource –Maximum message size, M [bytes] –Maximum message rate, R [Msg/s] –Maximum burstiness, B [Msg]

LBAP example Two workstations, LAN CD player at one workstation Singe channel audio transferred to the other workstation Sampling rate 44.1 kHz, each sample coded with 16 bits The data rate: R byte = Hz x 16 bit/ 8bit/byte = bytes/sec

Some measures, calculations Burst Maximum Average Data Rate Maximum Buffer Size, receiver Logical Backlog (messages already arrived, ahead of schedule) Logical Arrival time (defined earlies arrival time) Other (read)

Runtime Phase Resources must be provided according to QoS specifications during the lifetime of an application Traffic shaping and appropriate scheduling

Establishment Phase Resources are reserved and allocated during the connection setup according to the QoS specifications. Calculation of QoS, mapping to resources Reservation or rejection The system provides a contract to the application/user Resources must be provided also in the Runtime Phase

Establishment Phase 1.User or application define QoS parameters 2.Distribution of parameters on peer levels 3.Translation between layers 4.Mapping to resources 5.Reservation, allocation of resources 6.Accounting

QoS Negotiation Application (Caller) Service User User (Caller) Service Provider System (Caller) User (Callee) Application (Callee) System (Callee) Peer-to-Peer Layer-to-Layer

QoS Translation Derivation of required QoS parameter values and resources at lower system and network level from user or application QoS requirements. –Example: in file systems the high-level user file name is translated into file identifier and block number, where the file physically starts Peer-to-peer translation may be necessary –Example: If a source produce an MPEG-2 stream and the receiver can only show bitmap, a transcoder is needed

User-Application QoS Translation Tuning service –Graphical User Interface –Presentation of video and audio clips with the requested perceptual quality (high,,,low) –Mapping to application QoS parameters (frame rate, number of pixels, etc)

Application-System QoS Translation Maps application QoS requirements into system QoS parameters E.g., from frame size to packet size Analytic translation, or off-line derived curves or tables Example: analytic translation from application APDU to transport TPDU

System-Network QoS Translation Maps system QoS into underlaying network QoS parameters Example: end-to-end delay of ATM cells into delays in nodes and propagation

QoS Scaling Scaling: subsample a data stream and present a fraction of its original content Transparent scaling –Transport system scales the media down –Controlled packet dropping, let basic layer packets pass, drop enhancement layer packets Non-transparent scaling –Interaction between transport layer and upper layer required –The media stream is scaled down before presented to the transport layer

Video scaling Temporal scaling Spatial scaling Frequency scaling, reduce the number of DCT coefficients Amplitude scaling, reduce color depth, apply a coarser quantization of the DCT coefficients Color space scaling, reduce the number of entries in the color space (extreme, switch from color to gray scale)

QoS Routing During establishment or runtime phase, find a path (route) that meets the QoS requirements (throughput, end-to-end delay, loss rate)

QoS Routing Unicast QoS Routing Given a source node s, a destination node t, a set of QoS constraints C and an optimization goal, we aim to find the best feasible path from s to t Examples: –Find the path with the highest bottleneck link capacity –Find a path with a bottleneck link capacity higher than a certain value –Find a path giving minimum cost –Find a path with an end-to-end delay below a certain value

QoS Routing Multicast QoS Routing Given a source node s, a set R of destination nodes, a set of constraints C and an optimization goal, we aim to find the best feasable tree covering all nodes Examples: –Steiner tree problem, find the least cost tree –Constrained Steiner tree problem, find the least cost tree with constrained delay –Delay-Jitter-constrained multicast problem

QoS Routing – QoS/Resource Management Services QoS Routing and Best-effort Routing –Connection oriented, resource reservation, reducing call-blocking, fairness, overall throughput, response times,,,, QoS Routing and Resource Reservation –CPU time, buffer, link capacity –Not affected by traffic dynamics of other connections sharing resources

QoS Routing – QoS/Resource Management Services QoS Routing and Admission Control –Determine whether a connection request shall be accepted or rejected –When accepted, required resources are guaranteed QoS Routing and QoS Negotiation –If a feasable path is not found, the system can reject the request or start negotiations

QoS Routing Strategies Source routing –Each node maintains the global state, including the network topology –Link state protocol Distributed routing –Global State information in each node –Distance vector protocol –Routing is done hop-by-hop Hierarchical routing –Nodes are clustered into groups –Multi-level hierachy –Each node maintains an aggregated global state and state information of own group and other groups

Admission Control Part of Resource Management Checks availability by calling tests in the resource management The tests return either ’reserved’ with admitted or modified QoS, or ’rejected’ Schedulabiltiy test –Used for resources such as CPU or network Spatial test –Buffer allocation Link Bandwidth test –Ensures proper capacity

Reservation Pessimistic Approach Avoid resource conflicts by making reservation for the worst case Example: MPEG-2 where the relative occurance of I, P and B frames may vary

Reservation Optimistic Approach Reserve resources according to an average workload Gives high resource utilization Gives overload, which may result in failure Overload detection should be implemented

Additional Reservation Mechanisms Resource table –Co-located with resource manager –Info about the managed resources Reservation table –Provides info about the connection and/or tasks for allocated resources Reservation function –Determines the reserved QoS parameter values that can be given (via admission control) –Reserves resource capacities via Resource table and Reservation table

Traffic Shaping The concept was first developed by LAR by 1980, and paper published at ITC10 in Montreall in Title: Analysis of a traffic shaping scheme The idea was to reduce variability of bursty traffic by measuring the traffic in nodes in the network and smoothing the traffic at the entry of the network.

Traffic Shaping Used in Runtime Phase Traffic characteristics description Admission control Traffic monitoring Confirmation of promised behavior

Traffic Shaping Leaky Bucket [1986] –Each connection has its leaky bucket –Packets to be sent are placed into a bucket –Packets drain out of the bottom of the bucket at a constant rate

Rate Control A rate-based service discipline provides a user with a minimum service rate independent of other users New rate-based flow control needed New rate-based scheduling needed

Rate Control Fair Queueing –Packets arrive to N queues –The N queues share one output link –One packet is served from each queue in a Round Robin manner –But, each queue may be allowed to serve more than one packet for each round

Rate Control Virtual Clock –Emulates Time Division Multiplexing –N queues share an output link –Each queue is allocated a time slot for each round Delay Earliest-Due-Date (read) Jitter Earlies-Due-Date (read) Stop-and-Go (read) Hierarchical Round Robin (read)