* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download 3-4-1_QoS Intro adap..
Multiprotocol Label Switching wikipedia , lookup
Policies promoting wireless broadband in the United States wikipedia , lookup
IEEE 802.1aq wikipedia , lookup
Backpressure routing wikipedia , lookup
TCP congestion control wikipedia , lookup
Internet protocol suite wikipedia , lookup
Zero-configuration networking wikipedia , lookup
Asynchronous Transfer Mode wikipedia , lookup
Distributed firewall wikipedia , lookup
Wireless security wikipedia , lookup
Computer network wikipedia , lookup
Network tap wikipedia , lookup
Wake-on-LAN wikipedia , lookup
Piggybacking (Internet access) wikipedia , lookup
Deep packet inspection wikipedia , lookup
Cracking of wireless networks wikipedia , lookup
Routing in delay-tolerant networking wikipedia , lookup
Airborne Networking wikipedia , lookup
Recursive InterNetwork Architecture (RINA) wikipedia , lookup
Outline • Wireless introduction • Wireless cellular (GSM, CDMA, UMTS) • Wireless LANs, MAC layer • Wireless Ad hoc networks – routing: proactive routing, on-demand routing, scalable routing, geo-routing – wireless Ad hoc multicast – TCP in ad hoc networks – QoS, adaptive voice/video apps • Sensor networks QoS Support • Objective: – Guarantee Quality of Service to real time users • QoS users: – Multimedia – Voice over IP – Time critical applications • QoS metrics: – Bandwidth / data rate – Delay – Delay variance / jitter – Packet loss – Bit Error rate – etc QoS Wireless Scenarios • Scenarios – Multihop ad hoc network – Wireless Internet access (from W-LAN or ad hoc net) – Wireless mesh networks • The above scenarios are all challenging: – Channel parameter fluctuations (motion, obstacles, interference) – Change in S/N ratio at receiver – Mobility (path breaks, must be repatched, etc) – Multiaccess channel (distributed queue scheduling) – Interference from nodes beyond one hop • QoS support truly a cross-layer design: – From physical layer to applications Physical Layer QoS • As distance between tx and rcv increases, and noise/interference increases, S/N ratio decreases. • This requires a reduction in data rate to maintain acceptable BER • In 802.11 a, the rate can be adjusted in the following steps: 6,9,12,18, 24,48,54 Mbps • In 802.11b: 1,2,5.5, 11 Mbps • ARF (Auto Rate Feedback): – Rate reduced by transmitter if ACK missed twice – Rate restored if 10 consecutive ACKs are correctly received • RBAR (Receiver Based Auto Rate): – Receiver measures S/N ratio from RTS; returns allowed rate in CTS MAC Layer QoS • IEEE 802.11e is addressing QoS: – DCF -> Enhanced DCF (EDCF); 8 priority levels defined by different AIFS values – PCF -> Hybrid CF (HCF): can “poll” nodes also in contention free period • 802.11e is mainly directed to infrastucture LANs • In ad hoc, multihop network one can use some of the EDCF features • Another problem in ad hoc nets is the simultaneous scheduling of multiple transmissions (spatial reuse) • Several solutions: – TDMA (eg, cluster TDMA) – Non interfering flow graph (SCOPE) Network layer QoS • QoS routing (either proactive or on demand) • QoS extension of LANMAR, Fisheye • Real time bandwidth measurement in mobile ad hoc networks • Bandwidth allocation (or re-allocation) • Bandwidth reservation • Call Acceptance Control • Mobility adaptation • Scheduling and policing • Coexistence with best effort traffic Application layer QoS • Rate adaptation of multimedia stream • Network to application layer feedback (with avail bandwidth information) • End to end bandwidth estimation • We will discuss a video adaptation example Adaptive , renegotiable QoS support • If nodes move, the end to end path capacity can change dynamically: – The connectivity and topology change – The channel propagation characteristics change (eg, multipath fading) – The external interference can change • A possible answer: – Renegotiable QoS – rate adaptation – preemption of lower priority users • Case study: adaptive video streaming Scalable, Adaptive Video Streaming FLIR server client Why Adaptive Video? • To prevent traffic congestion – Adjust the stream rate so that it “fairly” shares the available bandwidth • To deal with channel random interference, propagation, jamming – Adjust (reduce) video packet size, strengthen the channel encoding to combat random/burst errors • Challenge: – Distinguish between congestion (must reduce rate) and random errors (keep same rate but strengthen the code) The concept channel fading mobility internal interference MPEG server H263 server LOSS FROM CONGESTION LOSS FROM ERROR client client external interference (jamming, environment noise) • End to End Feedback Adaptation Approach – Traditional approach – Transport and Application employ end-to-end measurements to perform flow control • Network Feedback Adaptation Approach – Network layer propagates channel measurements to source – Ability to detect cause of degradation and react properly • Implemented in simulation, testbed and hybrid simulatn Adaptation Techniques • RTP Loss rate Adaptation (Trial And Error) – It constantly ‘tries’ to support higher rates – Backs up when loss is detected • Available Bandwidth (AB Probe) eg. TCPW – Av. Bdw. estimated from inter-packet intervals – Can distinguish error loss from congestion • Network Feedback – Link channel quality and bdw info piggybacked on routing pkts – Gives accurate picture of network path state to source Network feedback • Goal: dynamic estimation of available bandwidth AB from source to destination • Approach: MAC and network layer cooperation • At the MAC layer: – estimate the permissible throughput from a node to each of its neighbors – estimate the “available bandwidth” AvBd for a node • At the network layer: – Finally, propagate the AvBd estimate to source using routing control packets MAC layer computation (a) Estimate link throughput: Throughput = S / (Tack - Ttx) where: S = packet size (bits) Ttx : time when packet tx is first attempted Tack : time when ACK is received This estimate accounts for collision avoidance, retransmissions, backoffs etc The estimate is averaged over a measurement window (b) Measure node utilization u = fraction of time node is busy (ie, it has packets in the queue) Available Bdw = (1 – u) x Throughput Measurement Example 11Mbps 802.11 links 10Mbps Throughput Permissible Throughput A Node utilization=80% 6Mbps AB AC AD 10Mbps(<11) 7Mbps (<11) 6Mbps (<11) B Hidden Terminals 7Mbps 2Mbps 1.4Mbps 1.2Mbps D Hidden Terminals C Hidden Terminals Link Assisted/Network Feedback channel fading server MPEG internal interference H263 Multi-hop noise ..... Network Link server Application external interference client (jamming, environment noise) Network Link Measure() client LOSS FROM ERROR LOSS FROM CONGESTION Propagate() mobility Network Link Measure() Network Link Network Link Measure() Measure() API Network Link Network QoS Feedback Accurate Available Bandwidth Measurement and Advertising How to propagate to sources? QM-AODV • Q-AODV – extension of AODV for QoS 1 RREQ routing Update Reverse Route with AB(1) • Finds routes given: minimum bandwidth and maximum delay MREP(AB(4)) 2 constraint If Bhop=2 or minimum • Does not deal with measurement 3 Update aggregation RREP (min(inf,AB(5),0 or 1) • Does not have to propagate Significant measurements AB Change • AvBd propagation - QM-AODV 4 – Use Q-AODV packet format RREP – Add bottleneck hop information (inf,0) – Use an MREP special reply packet 5 – Use Measurement Relay Factor to trigger Measurement updates 802.11 Multi-hop – Loss Rates Loss Rates - Network of 64 100% 80% % 60% 40% 20% 0 10 20 30 40 50 60 70 0% Connections Net • AB-probe AB RTP High L PP Low L. performs best initially, then worse than RTP when load is high • RTP adaptation works better than direct PP (Packet Pair) method • Network Feedback is best Real-Time Protocol (RTP) • Provides standard packet format for real-time applications - a sublayer of the transport layer • Typically runs over UDP • Specifies header fields (see below) • Payload Type: 7 bits, providing 128 possible different types of encoding; eg PCM, MPEG2 video, etc. • Sequence Number: 16 bits; used to detect packet loss • Timestamp: 32 bytes; gives the sampling instant of the first audio/video byte in the packet; used to remove jitter introduced by the network • Synchronization Source identifier (SSRC): 32 bits; an ID for the stream; assigned randomly by the source