340 likes | 485 Views
Wireless Data Networking Research: From Concept to Practice. Songwu Lu UCLA. Drivers for Wireless Networking Research. New Services, Architectures, Requirements. Top. Up. Transport Layer. Network Layer. Down. Link Layer. Bottom. New Wireless Communications Technology.
E N D
Wireless Data Networking Research: From Concept to Practice Songwu Lu UCLA
Drivers for Wireless Networking Research New Services, Architectures, Requirements Top Up Transport Layer Network Layer Down Link Layer Bottom New Wireless Communications Technology
Key Driver: Wireless Communications • Many examples of them: • Sector Antenna, antenna arrays, Smart antennas • Adaptive modulation, MIMO, OFDM, UWB, .. • Cognitive radio, software radio, spectrum sharing, channel management • Multiple radios, device heterogeneity • … • many orthogonal dimensions • RF spectrum, antenna, data processing, … • main goal: improve performance in terms of spectral efficiency • Challenge: How to exploit these new PHY communication capabilities in the protocols?
Root Cause of Problems two largely disconnected communities • speak different terminologies • wireless communications: • Symbols, signals • probabilistic terms: • information theoretic bounds • confidence factor on symbol reception, … • wireless networking • Packets, bits • deterministic terms • Correct/wrong binary reception
Root Cause of Problems (2) Two largely disconnected communities • different methodologies • wireless communications • solid theoretic foundation on information theory • a set of well known assumptions: noises, interferences, etc. • Theory Design-->Analysis-->prototype in chips-->experiments • wireless networking • mostly on heuristics • network setting “ad hoc”: no agreed benchmarks/base settings • Heuristic Design-->Simulations--Network Prototype-->Experiments
Perspective From Wireless Networking • We are not on the driver’s seat so far • communication has driven the technology so far • we are followers • No need to be sad • still plenty of space • the direct communication almost NEVER works in reality at the 1st place! • other brothers also facing similar situations sometime • Internet: PC/hardware industry • Cellular: mobile phones
Research Life Cycle in Traditional Wireless Networking Researcher • wait for new radio communication tech. to come to life • be the 1st to design networking solution to it • not so lucky? • understand the problem better • check other aspects/components in the system • apply the set of tricks in your bag • claim credit/declare failure • Experiments!!!! • Positive success: insights learned • Negative failure: lessons learned
Two Design Guidelines 2 most popular design principles used in the research community • Adaptation high-dimension dynamics • Coordination coherent system
Bag of Tricks in Adaptation • Model-referenced design • Ideal model to capture expected behaviors under idealized situation • e.g., error-free, static settings • Track the reference model under realistic conditions/scenarios • Mobility, wireless channel dynamics, … • Opportunistic design approach • Make each perform under peak conditions • Exploit the system population • Leverage system diversity • Multiple receivers, multiple devices, multiple applications/flows, …
Bag of Tricks in Coordination • Cross-Layer design • not integrated design cross layers • information sharing, informed decision at other layers • … • Coordination via “indirection” • Adaptation-aware proxy provides indirection: act as converter/translator
54Mbps Signal is good Signal becomes weaker Receiver Illustration Case: Rate Adaptation in Wi-Fi Problem: Adapt transmission rate to channel quality 12Mbps Sender • The 802.11 a/b/g/n standards allow for multiple rates based on adaptive modulation • 802.11b: 4 rate options (1,2,5.5,11Mbps) • 802.11a: 8 options (6,9,12,18,24,36,48,54) • 802.11g: 12 options (11a set + 11b set) • unspecified by the IEEE 802.11 standard
As the Lucky, 1st Guy • Driver: adaptive modulation • Good news: SNR based feedback not there! • Opportunity: packet-level information available • Solution: • Hypothesis: packet loss indicates channel quality change • Tricks: • Decrease transmission rate upon severe packet loss • 10 consecutive successes → increase rate
Rules For Not So Lucky? Understand the problem better • if a problem is not better understood, it is probably best not to provide a new solution at all • no rush for quick solutions • incremental improvement is #1 enemy in research! • do not improve on flawed design!! • adding gas into fire
Experiments to Discover (No) Problems • Case:packetcollisionscenario? Hidden Station Receiver Sender The sender performs worse with Rate Adaptation!
Decrease Tx rate Increase Tx time Severe loss Increase collision Prob. Find Root Cause • The sender should not decrease the rate upon collision losses • Decreasing rate increases collisions ! Fail to handle hidden-station!
Solution? • Straightforward idea: RTS/CTS • more thinking: makeRTS/CTS adaptive • reduce overhead • infer collision levels • Performance: ~80% throughput gain Software 802.11 MAC RRAA Loss Estimation Rate Selection send Adaptive RTS RTS Option feedback Hardware PHY
NowMIMO Case? • Driver: 802.11-pre-n MIMO • Good/Bad News: SNR feedback to some extent • more direct & timely information on channel quality? • Loss-based design obsolete?
SNR vs Rate vs Throughput • SNR vs rate vs thruput are non-monotonic in fine grain • main trend can still be correct • RF Chamber experiments
Solution in MiRA • using SNR pre-selects a range of rates • determine a rate window [minRate, maxRate]. • Loss-based best rate choice within the window • play old tricks using loss-based design
Experiments on Static Clients: UDP Gains in blue arrows refer to MiRA vs. Atheros RA
Static Clients Scenario: TCP Gains in blue arrows refer to MiRA vs. Atheros RA
Broader View on Well-Known Areas • look at other systems component the design works with • illustrative example: Network Coding • hot topics • several papers on top conferences, from groups @ MIT, Microsoft Research, … • what can I do?
a b Bob Alice aXORb Network Coding in Reality: Wi-Fi Nets • Multicast/broadcast (a XOR b) @ 6Mbps • Base rate without RA • Used in COPE, Wi-Fi broadcast • NC is worse ! • Xmit time w/o NC • 2L/54 + 2L/24 • Xmit time with NC • L/54 +L/24+L/6 • Conclusion: NC works but loses without any RA! 54Mbps 24Mbps Native NC (@ base rate) May NOT gain at all !
a b Bob Alice aXORb NC Gain May Vanish • Simple multicast RA solution: • multicast = min (rate_receiver) • NC gain reduces • NC: 25% (4 tx ->3 tx) • In the literature • Actual gain (11a): 5% • NC tx time: 2*L/6+L/54 • No NC: 2*L/54+2*L/6 • 802.11b: 1/24 (11M&1M) • Root cause: NC cannot exploit rate diversity! 54Mbps 6Mbps NC gain (@ optimal rate) may reduce in rate diversity case!
My View on New Frontiers • no need to get squeezed in crowded traditional areas • bag of tricks grow much slower! • problem space is wild wide west!
Wireless Networking on a Chip • 1000sof cores Systems on a Chip • wired interconnect: latency, physical wiring constraints • High-speed wireless shortcuts
Composable Wireless Networking • composable & modular from radio to networking • Radios become dynamically loadable modules • no clear separation of multi-radios • Software Defined Radios platforms
“Green” Wireless Infrastructure • infrastructure is power hungry • asymmetric design in cellular network • more complexity @ base stations • from radio communication, to signaling, to higher layers • lots of energy-saving proposals @client side • no on the infrastructure
Resilience-Oriented Design • mostly performance driven for wireless networking so far • resilience as the 1st principle • not as patches • learn the success from the Internet • still early to have a nice try
Still Unhappy? Looking Up • New requirements • Security, privacy, robustness/dependability, distributed management • New applications and services • MMS, P2P image/video sharing, IP TV streaming, … • (Location-based, context-aware, personalized, pervasive) services
messages preferences news contacts calendar investments mailing lists maps e-mails phone numbers photo music MyViewonPervasiveCloudComputing • Data stored in the “Cloud” • Data follows you & your devices • Data accessible anywhere • Data can be shared with others “Anytime, Anywhere, Any device” Data Service
Research Sub-areas • Data Center Networking: Improving the Cloud Infrastructure • New Services For Mobile Devices • Security: Virus detection • Location-based Service, • social networking,… • Better Access for the Client • ImprovingWi-Fi, 3G+, … for user access • Opportunistic Client-Client Service
Final Words • Life can be good or bad in wireless networking research • It is more about your choice • You are part of inventing the artifact for wireless networking
Acknowledgments • most real work is done by the real heroes in projects: • Students: • Innaois Yannis, Suk-Bok Lee, Starsky Wong, Hao Yang, Haiyun Luo,… • Colleagues: • Lixia Zhang, Mario Gerla, Chuanxiong Guo, Jacky Shen, Yongguang Zhang, Shugong Xu, …