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Mario Gerla Current Network Research Projects • Ad hoc, wireless networks (DARPA, NSF, ONR) • Wireless, mobile access to Internet (NSF, Intel) • Internet : QoS Routing and multicasting (CISCO, NASA, NSF) • Internet control models: TCP (EPRI,NASA) • Internet II: high speed traffic models and measurements (NSF, EPRI) www.cs.ucla.edu/NRL Cellular Vs Multihop Standard Base-Station Cellular Networks Base Base Base Ad Hoc, Multihop wireless Networks Challenging problem: multihop routing • • • • • • mobility need to scale to large numbers (100’s to 1000's) unreliable radio channel (fading etc) limited bandwidth limited power need to support multimedia (QoS) Conventional routing: Distance Vector 0 Routing table at node 5 : 1 Destination Next Hop Distance 0 1 … 2 2 … 3 2 … 3 2 4 5 Conventional wired routing limitations • Distance Vector (eg, Bellman-Ford, DSDV): – routing control O/H linearly increasing with net size – convergence problems (count to infinity); potential loops CONVENTIONAL ROUTING DOES NOT SCALE TO SIZE AND MOBILITY Fisheye State Routing • Routing information is periodically exchanged with neighbors (as in Distance Vector) • BUT: Routing update frequency decreases with distance to destination – Higher frequency updates within a small radius and lower frequency updates to remote destinations – Result: Highly accurate routing information about immediate neighborhood; progressively less detail for areas further away Scope of Fisheye 2 8 5 3 1 9 9 4 6 Hop=1 7 13 10 12 11 36 14 21 Hop>2 15 16 17 22 23 20 29 27 25 24 Hop=2 19 18 26 30 35 28 34 32 31 How to deal with remote destination inaccuracy? Landmark Routing Landmark Logical Subnet Snapshot LM3 LM1 P O J K L D C I H LM2 LM4 B A GloMoSim Simulation Layers Application Data Plane Control Plane Application Processing Application Setup RTP Wrapper Transport IP Network Link Layer MAC Layer Radio Channel Transport Wrapper IP Wrapper Packet Store/Forward Packet Store/Forward Frame Wrapper Frame Processing Propagation Model RCTP TCP/UDP Control RSVP IP/Mobile IP VC Handle Routing Flow Control Routing Clustering Ack/Flow Control RTS/CTS CS/Radio Setup Radio Status/Setup Mobility Clustering Ad Hoc, Personal Networking with Bluetooth headset PDA cell phone storage palmtop What Is Bluetooth? Landline Cable Replacement Data/Voice Access Points Personal Ad-hoc Networks UCLA Adaptive Speech Experiment Audio source adapts to QoS feedback Speech Recognition TTS Sync Multihop Testbed Wireless Network client server • Adjustable Parameters - sampling rate - packet size Increase in jitter Increase in Packet loss Audio(UDP) Piggybacked Text Stream(UDP) Control(TCP) AdaptatIon Strategy: network congested channel noise/interference • QoS Monitoring: - packet loss - jitter sampling rate is reduced packet size is reduced iMASH: Interactive Mobile Application Support for Heterogeneous clients CS: R. Bagrodia, M. Gerla, S. Lu, L. Zhang Medical School: D. Valentino, M. McCoy Campus Admin: A. Solomon UCLA Supported by NSF Diverse Display Devices Use of different devices for different components of medical care Imaging Workstation: high-quality medical imagery and multimedia patient records Physician’s PDA: for messaging and scheduling Mobile Medical Notes: for reviewing and taking medical notes Medical Workstation: multimedia patient records, including moderate-resolution images Hardware & Connectivity Middleware Servers High bandwidth Intranet Application Server Middleware Servers Middleware Servers iMASH: Components • Target application: Mobile physicians • Middleware infrastructure to support anytime, anywhere, any-device access to electronic multimedia data • Protocols to provide reliable QoS in a mobile, heterogeneous network • Simulation/emulation capability to evaluate scalability of system to many users over large geographic areas • Limited evaluation via deployment within UCLA medical school QoS Routing and Multicast in wired nets • Supported by CISCO and by NASA AMES • Intradomain environment • Quality of Service Routing/Multicast for Real Time traffic (IP telephony,video etc) • Call Admission Control • Traffic load balancing Example of QoS Routing A B Constraints: Delay (D) <= 25, Available Bandwidth (BW) >= 30 Multiple constraints QoS Routing Given: - a (real time) connection request with specified QoS requirements (e.g., Bdw, Delay, Jitter, packet loss, path reliability etc); examples: IP telephony, video streaming Find: - a min cost (typically min hop) path which satisfies such constraints - if no feasible path found, reject the connection 2 Hop Path --------------> Fails (Total delay = 55 > 25 and Min. BW = 20 < 30) 3 Hop Path ----------> Succeeds!! (Total delay = 24 < 25, and Min. BW = 90 > 30) 5 Hop Path ----------> Do not consider, although (Total Delay = 16 < 25, Min. BW = 90 > 30) A B Constraints: Delay (D) <= 25, Available Bandwidth (BW) >= 30 We look for feasible path with least number of hops Benefits of QoS Routing Without QoS routing: • must probe path & backtrack; non optimal path, control traffic and processing OH, latency With QoS routing: • optimal route; “focused congestion” avoidance • more efficient Call Admission Control (at the source) • more efficient bandwidth allocation (per traffic class) • resource renegotiation possible High Speed Networks Performance Measurement and Analysis Mario Gerla and Medy Sanadidi Project Focus • High speed : backbone links at 2.4 Gbps and above, as in Abilene and vBNS • Heterogeneous networks: wired and wireless • High performance distributed applications: processor intensive, large data bases, high traffic volume, low latency • Application performance : measure the network performance as perceived by network applications/users; tune protocols to improve performance Example: Urban Simulation (R. Muntz and B. Jepson) • Real-time visual simulation for design, urban planning, emergency response, and education • Built Virtual Los Angeles model • Challenge: remote/distributed access through high speed net Current Measurement Activities • TCP performance over wireless Internet access links (wireless LAN, satellite); wireless, lossy channel emulator; TCP Westwood • Characterization of long range dependent traffic in the Internet; traffic generators • Measure performance of dataView (3 D rendering of scientific data): impact of propagation time and network bottlenecks