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Exploiting Idle Communication Power to Improve Network Performance and Energy Efficiency Lei Guo, Xiaoning Ding, Haining Wang, Qun Li, Songqing Chen, Xiaodong Zhang
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Exploiting Idle Communication Power to Improve Network Performance and Energy Efficiency Lei Guo, Xiaoning Ding, Haining Wang, Qun Li, Songqing Chen, Xiaodong Zhang Proceedings of the 25th IEEE Annual Conference on Computer Communications (IEEE INFOCOM 2006), Barcelona, Spain, April 23-29, 2006. Presented by Michael Putnam (Some images and slides taken from INFOCOM presentation - http://www.cse.ohio-state.edu/~lguo/ )
Author Bio’s OUTLINE BIOGRAPHIES Introduction Related Work Motivation System Models Channel Allocation System Design Experiments Conclusion • Ohio State University • Lei Guo • Ph.D. candidate in CSE • Member of High Performance Computing and Software Lab • Researches: • Internet measurements and modeling • Streaming media delivery over the Internet • Wireless systems and networking • Xiaoning Ding • Ph.D. candidate in CSE • Researches: • Operating Systems • Computer architecture • Wireless systems and networking • Xiaodong Zhang • Chairman of the Department of CSE • Researches: • Fast Data Accesses • Resource Sharing
Author Bio’s OUTLINE BIOGRAPHIES Introduction Related Work Motivation System Models Channel Allocation System Design Experiments Conclusion • College of William and Mary • Haining Wang • Assistant Professor Department of CS • Researches: • Network QoS • Internet architecture • Wireless and sensor networks • Qun Li • Assistant Professor Department of CS • Researches: • Wireless and Sensor Networks • Embedded Systems
Author Bio’s OUTLINE BIOGRAPHIES Introduction Related Work Motivation System Models Channel Allocation System Design Experiments Conclusion • George Mason University • Songqing Chen • Assistant Professor Department of CS • Researches: • Distributed Systems • High Performance Computing • P2P Systems • Internet Systems
Challenges in Wireless System Design OUTLINE Biographies INTRODUCTION Related Work Motivation System Models Channel Allocation System Design Experiments Conclusion • Energy saving is not easy • Limited battery capacity in wireless devices • High power consumption in wireless communication • High performance costs energy and fairness • Wireless users demand high throughput, but … • A high throughput device needs less sleep. • A channel allocation mechanism can favor some but degrade performance of others. • Can we win both instead of addressing the trade-off?
Power Consumption for Mobile Devices OUTLINE Biographies INTRODUCTION Related Work Motivation System Models Channel Allocation System Design Experiments Conclusion • Energy consumption • A simple way to save energy • Put the WNI into sleep mode when idle (for a 5 V device) up to 10% total energy > 50% total energy high power mode 450 mA low power mode 15 mA
Access point Buffer data for sleeping stations Broadcast beacon with TIM periodically (100 ms) Sleeping station Wake up periodically to receive beacon Poll access point to receive data Sleep again 802.11 Power Saving Mechanism Traffic Indication Map (TIM) wake up poll receive data OUTLINE Biographies Introduction RELATED WORK Motivation System Models Channel Allocation System Design Experiments Conclusion Internet AccessPoint sleeping station
Observations of IEEE 802.11 Protocol OUTLINE Biographies Introduction RELATED WORK Motivation System Models Channel Allocation System Design Experiments Conclusion • A client/server model • Each station independently communicates with AP • AP serves a station one at a time via the channel. • The saving mode affects TCP traffic • Increasing RTT and decreasing throughput. • Performance anomaly (Infocom’03) • Non-uniform transfer rates between different stations to AP due to distance and obstacle condition differences. • A low speed station has low channel utilization rate. • Waste energy while a station is waiting for its turn. • Idle communication power due to strong dependency
Performance Anomaly in WLAN OUTLINE Biographies Introduction RELATED WORK Motivation System Models Channel Allocation System Design Experiments Conclusion • Multiple channel rates in PHY • Larger coverage • Varying channel conditions • Same MAC control for all channel rates • Same opportunity to get channel • Different channel holding time for sending frame • Performance anomaly (INFOCOM’03) • All stations have the same flow rate • Unfair to high channel rate stations • Low channel utilization
Existing Solutions to address the Limits OUTLINE Biographies Introduction RELATED WORK Motivation System Models Channel Allocation System Design Experiments Conclusion • Reducing idle communication power by • Traffic prediction: bounded slowdown (MOBICOM’02) • Self-tuning with application hints (MOBICOM’03) • Limits: case by case, and accuracy can vary. • Address the performance anomaly • Time-based fairness scheduling: a constant time unit is given to each device (USENIX 04) • Limits: poorly conditioned devices suffer: fast is faster, and slow is slower. • Purpose of this paper: to win both performance and energy
While the channel is used by one station, idle communication power is wasted in many other stations Source of Idle Communication Power AP Wireless performance anomaly makes this power waste worse, but also with an opportunity. OUTLINE Biographies Introduction Related Work MOTIVATION System Models Channel Allocation System Design Experiments Conclusion
To help low channel rate stations to Increase throughput and extend network coverage Multi-hop Relay AP X OUTLINE Biographies Introduction Related Work MOTIVATION System Models Channel Allocation System Design Experiments Conclusion
Multi-hop Relays Leverage Strong Dependency OUTLINE Biographies Introduction Related Work MOTIVATION System Models Channel Allocation System Design Experiments Conclusion • Slow stations become faster • Completing the data transfer ahead of the unit time. • Equivalent to move the station closer to AP or improve the station’s communication condition. • Faster stations serve as proxies for slow stations • Performance improvement of slow stations reduced the waste of idle communication powers of fast stations --- shortening the waiting time. • Effective P2P coordination among stations is the key.
Incentive and Fairness to Fast Stations OUTLINE Biographies Introduction Related Work MOTIVATION System Models Channel Allocation System Design Experiments Conclusion • Why not sleep or wait, but proxy/relay for others? • Sleep lowers throughput, and wait wastes energy. • Idle communication energy can be used • The saved time in slow stations should be contributed. • How much service is fair in a shared radio channel? • A proxy should be paid for its service • For either proxy or client, the throughput and energy utilization should be improved.
Rationale OUTLINE Biographies Introduction Related Work MOTIVATION System Models Channel Allocation System Design Experiments Conclusion • Energy efficiency: what does a user care about? • Energy per second • Energy per bit:time is energy • Self-incentive multi-hop relay with TBF • Use channel time to pay the relay service • A win-win solution
Time based fairness in shared radio channel Principle of proxy forwarding Proxy: throughput Þ idle time ¯ Þ energy/bit ¯ Client: channel rate Þ throughput System Model ti=Dt = 1/n Sp S0 Sq S1 S2 … Si … Sn AP Proxy Client 1 round OUTLINE Biographies Introduction Related Work Motivation SYSTEM MODELS Channel Allocation System Design Experiments Conclusion idle idle
Analytic Definitions OUTLINE Biographies Introduction Related Work Motivation SYSTEM MODELS Channel Allocation System Design Experiments Conclusion • Power Consumption – P(Si) • Joules / sec • Throughput – T(Si) • The number or effective bits a station transmits per unit time (not including retransmissions, or forwarding data for other stations) • Energy Utility – E(Si) • Average number of effective bits per unit energy
Analytic Definitions OUTLINE Biographies Introduction Related Work Motivation SYSTEM MODELS Channel Allocation System Design Experiments Conclusion • Throughput Gain • Energy Gain
Channel Time Allocation (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion
Lemma 1 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Time utilization of a client Sq when it pays the cost price to its proxy Sp for the forwarding service is
Lemma 1 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Rewarding time of a client Sq when it pays the cost price to its proxy Sp for the forwarding service are • Amount needed to keep energy utility of proxy unchanged • Cost for the proxy to listen to the client and talk to the AP
Lemma 1 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Throughput gain of a client Sq when it pays the cost price to its proxy Sp for the forwarding service are • Energy Utility gain of a client Sq when it pays the cost price to its proxy Sp for the forwarding service is
Lemma 1 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Relaying is only useful when the Throughput Gain • Since U(Sq) < 1, Note that Which Implies • Relaying can increase the Energy Utility of a client station as long as its Throughput can be improved
Lemma 2 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Assume station Sp provides forwarding services to k client stations, Sq1 , Sq2 , ..., Sqk (k > 1), and these client stations independently contribute their rewarding time to Sp to keep the energy utility of Sp unchanged, we have • U(Sp) = 1 and = 1: “…easy to see…” – authors
Lemma 2 (single-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Throughput Gain • The effective time of Sp is • Thus,
Channel Time Allocation (multi-hop) S0 S1 Si-1 Si OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion
Lemma 3 (multi-hop) OUTLINE Biographies Introduction Related Work Motivation System Models CHANNEL ALLOCATION System Design Experiments Conclusion • Assume each station has at most one immediate relaying station in a WLAN, and each station rewards its relaying stations independently to keep their energy utilities unchanged. For station Si that is relayed by i – 1 (i ≥ 1) stations along the path S0 → S1 → ... → Si – 1 → Si, and Si has mi indirect or direct clients (Sq1 , Sq2 , ..., Sqmi), we have Where and
Selfish Forwarding - SFW HELP! OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Proxy discovery and selection • A poorly conditioned client broadcasts a request to relay his packets • AP assigns a relaying station for clients based on the game theory (second price auction) to provide fairness for competition among proxy candidates AP
Selfish Forwarding - SFW HELP! OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Proxy discovery and selection • AP collects the bids within a bidding time window • AP selects winner based on “second price sealed bid” rule • (highest bidder wins, but only pays second highest price) • Client sends a request to the proxy • Proxy ACKs, and notifies the AP of the association
Selfish Forwarding - SFW OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Channel allocation and scheduling • Easy to do under PCF • - but since most commercial products only support DCF, • there is a need for a scheduling algorithm • AP distributes tokens for fairness without any enforcement. • The relaying actions are determined by token exchanges among stations.
Basic Idea of Token-based Channel Scheduling OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • A token is a ticket for a data transfer (RX/TX) in one time unit • AP initially distributes an equal amount of tokens to each station (fairness). • A pair of RX & TX consumes one token. • Token bucket model to fully use transmission channel. • Multi-hop forwarding to increase throughput • Incentive rewards to proxies
Token and Token Bucket Model OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion tokens from AP Overflow! Re-allocate to other stations by AP Token Bucket Transmitter 1 token per packet packets Packet Queue
Multi-hop Forwarding OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion S1 AP S2 S4 S3
Multi-hop Forwarding STA Proxy Rate S1 --- R(0,1) S1 AP S2 --- R(0,2) S3 S2 R(0,3) S4 S2 R(0,4) Hop Station Rate 1 Self R(0,2) S2 2 S3 R(2,3) S4 R(2,4) S4 Hop Station Rate S3 1 S2 R(0,2) 2 Self R(2,3) OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Each frame has Src / Dest MAC address • Upon receipt of frame, node looks up Dest in table to see who to send to next • Puts that addy in the Dest field and forwards the frame • Then updates its channel rate field for the link received on to compute cost price of forwarding service.
Multi-hop Path Maintenance OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Channel rates vary due to mobility or changes in the environment conditions – possible broken paths • Each client periodically re-evaluates the forwarding service • If the service quality is degraded, looks for a new proxy • ( What threshold determines significantly degraded service? )
Multi-hop Power Management OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation SYSTEM DESIGN Experiments Conclusion • Power saving mode (no clients) • notify the AP directly • Power saving mode (with clients) • Notify immediate children • Children recursively notify their children • After receiving all ACK’s – notify the AP • Clients look for new proxies
Implementation and Experiments OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion • AP • NetGear MA311 802.11b PCI wireless adaptor • Linux kernel 2.4.20 • HostAP linux driver v0.1.3 • Wireless Stations (6) • NetGear MA401 802.11b PCMCIA wireless adaptor • ORiNOCO Linux driver v0.15rc2 • Traffic • FTP (presented in the paper) • Web (results in tech report)
Implementation OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion • Bidding time – 50 ms • Token distribution interval – 100 ms • Token value – 20 µs channel time • Host AP distributes tokens evenly based on number of stations, then transfers rewarding tokens from clients to proxies
Protocols Compared OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion • DCF • Most widely used protocol in 802.11b network • Distributed Coordination Function • TBF • Time-based Fairness (proposed USENIX 2004) • SFW • Selfish Forwarding (authors’ homebrew)
Single Client Experiment 11Mbps AP 11Mbps 1Mbps OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion • Large file download from AP to proxy / clients • Throughput measured at each hop • Energy consumption computed (not measured) • Tx time * power consumption • (as provided by the manufacturer)
Performance Evaluation Channel allocation scheme Channel allocation scheme 1 proxy (P), 1 client (Q) OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion
Multi-clients Experiment 11Mbps AP 1Mbps OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion
Performance Evaluation 1 proxy (P), 5 clients (Q) OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion
Performance Evaluation OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design EXPERIMENTS Conclusion 1 proxy, multiple clients Proxy throughput gain
Conclusion OUTLINE Biographies Introduction Related Work Motivation System Models Channel Allocation System Design Experiments CONCLUSION • Address throughput degradation caused by low-rate stations (Performance Anomaly ’03) • Utilize energy waste in idle channel listening • High Channel-rate station forwards data for low-rate station • Clients reward proxy with additional channel time • Everyone’s throughput can increase without suffering energy efficiency