Chengzhi Li Department of Computer Science University of Virginia

1. Coordinated Multi-Node Scheduling: A Mechanism for End-to-End Service in Wired and Wireless Networks Chengzhi Li Department of Computer Science University of Virginia http://www.cs.virginia.edu/~cl4v

2. My Biography Research Scientist in the University of Virginia since 2001 Postdoctoral Fellow in Rice University from 1999 to 2001 Ph. D in Computer Engineering from Texas A&M University in 1999 M.S. degree in Operations Research from Xiamen University in 1985 B.S. degree in Applied Mathematics from Fuzhou University in 1982 Research areas encompass wired and wireless networking

3. My Publications related computer networking • Mobile Computing and Wireless Networking • ACM Wireless Networks Journal (WINET), 8(6), November 2002 • Proceedings of ACM MOBIHOC 2002 • Proceedings of ACM MOBICOM 2001 • Coordinated Multihop Scheduling • IEEE/ACM Transactions on Networking, 10(6), December 2002 • Proceedings of the 17th ITC • Proceedings of IEEE ICNP 2000 • Scalable Admission Control • Journal of Real-Time System 2003 (24) • Proceedings of IEEE ICDCS 2000 • Proceedings of IEEE ICPP2000 • Real-Time Systems • Proceedings of IEEE MILCOM 1999 • Proceedings of IEEE ICPP 1998 • Deterministic QoS Guarantees • Journal of Communications and Networks, Vol. 1, Number 3, September 1999 • Proceedings of IEEE ICPP 1999 • Proceedings of IEEE RTSS 1997 • Proceedings of IEEE INFOCOM 1997

4. Outline • Quality-of-Service Provisioning • Coordinated Multi-Hop Scheduling • Future Work

5. Sender A E B C F D Receiver Part 1. Quality-of-Service Provisioning Scheduling EDF WFQ Static Priority FIFO • Deterministic QoS • Delay  d • Statistical QoS • Pr[ Delay  d ]   • or • Pr[ Loss ]   Deterministic Deterministic traffic Stochastic traffic Statistical Traffic Characterization Service/ Admission Control

6. Deterministic QoS Guarantees (Texas A&M) Motivation: Provide deterministic QoS guarantee for real-time applications, e.g. Voice over IP, military applications, etc. Problem:Admission control can be time-consuming Admission Request Computation of the worst case delay (D) yes no D<d admitted rejected Goal:Devise scalable admission control algorithms

7. Achievement (Texas A&M) • Utilization-based Admission Control: • Determine safe utilization bounds for each link • Turns delay bound check into utilization bound check • Use fixed point theory to solve nonlinear equations for delay bounds At RunTime At ConfigurationTime Verification of Safe Utilization U := U + Unew Delay Computation for Path Delay D Add a flow Yes No No Yes U ≤α? D<d? admitted rejected Utilization bound α

8. Wireless Network Sender Sender A A C E E B B B D C C F F D D A Receiver Receiver E Coordinated Multi-Hop Scheduling (Rice U.) Wired Network • Applications need end-to-end service • Currently, each network node forwards packets independently • Question: Can end-to-end QoS be improved if network nodes coordinate their scheduling decisions?

9. Statistical Network Calculus(UVa) • Statistical QOS:Pr[ Delay  d ]   • Motivation: Statistical services can exploit statistical multiplexing gain • Goal:Develop a simple, yet rigorous, framework for statistical traffic provisioning Statistical Network Calculus

10. Approach: Use large deviation theory to turn probabilistic problems into deterministic optimization problems Devised simple expressions for delay distribution in a network … for various scheduling algorithms: FIFO, SP, WFQ, EDF …. for various traffic models: regulated (“leaky bucket”), fractional Brownian motion, On-off Scheduling EDF WFQ SP FIFO Deterministic traffic Deterministic FBM Regulated Statistical On-off Traffic Characterization Admission Control Achievements(UVa)

11. Selected Publications Deterministic QoS • B. Choi, D. Xuan, C. Li, R. Bettati, and W. Zhao, "Utilization-Based Admission Control for Scalable Real-Time Communications," Journal of Real-Time Systems, Vol. 24, 2003. • C. Li, R. Bettati, and W. Zhao, "Static Priority Scheduling for ATM Networks," in Proceedings of IEEE RTSS 1997, December 1997. Coordinated Multi-hop Scheduling (CMS) • C. Li and E. Knightly, "Coordinated Multihop Scheduling: A Framework for End-to-End Services," IEEE/ACM Transactions on Networking, 10(6), December 2002. • V. Kanodia, C. Li, A. Sabharwal, B. Sadeghi, and E. Knightly, "Distributed Multi-Hop Scheduling and Medium Access with Delay and Throughput Constraints, " in Proceedings of ACM MOBICOM 2001, Rome, Italy, July 2001. Statistical Network Calculus • C. Li, A. Burchard, J. Liebeherr, “A Network Calculus with Effective Bandwidth,” submitted to ACM Sigmetrics 2003.

12. Part 2. Coordinated Multi-Hop Scheduling in Wireless Networks • Motivation • Coordinated Multi-hop Scheduling (CMS) in Wired Networks • Principles of CMS • Summary of findings • CMS in Wireless Networks • Distributed priority-driven MAC protocol to support CMS • Coordination improves the performance • Conclusions

13. A E B C C F D B D A E Motivation Provide better end-to-end service in wired and wireless networks

14. Main Idea of CMS • Piggybacking information in packet headers allows network nodes to cooperate to provide better end-to-end service • Downstream nodes decide service order for arriving packets based on how packets were treated at upstream nodes • Implications: • Late packets receive increased priority downstream • Early packets have priorities reduced downstream

15. Scheduler 3 9 5 8 Arrival 14 packet Index priorityindex D Priority Scheduling • Each packet is assigned a priority index • Scheduler selects packets with smallest priority index first • Priority index assignment is a function of the QoS requirements • Example: Earliest Deadline First (EDF) • Priority index is deadline • Deadline = arrival time + delay bound

16. Priority scheduling in a multi-hop network • Calculation of priority index at i-th hop: • Without coordination: Deadlinei = arrival timei + delay boundi • Coordinate scheduling: Deadlinei = Deadlinei-1 + delay boundi • Coordinated assignment of deadlines allows packets to “catch up” if they miss the deadline at a node

17. Example: Coordinated Scheduling • End-to-end delay bound: 20 msec • Per-node delay bound: 5msec Arrival time: 17  No end-to-end delay bound violation arrival time: tdeadline: t+5 departure: t+3 arrival time: t+3deadline: t+5+5departure: t+12  Delay bound violation at node arrival time: t+14deadline: t+5+5+5+5departure: 17 arrival time: t+12deadline: t+5+5+5departure: t+14

18. Coordinated Multi-hop scheduling can be applied to many types of scheduling algorithms: Rate-oriented CMS: priority index depends on reserved bandwidth Delay-oriented CMS: priority index depends on delay bound CMS Properties

19. Other results on CMS for wired networks • CMS can outperform existing scheduling algorithms (in particular: WFQ) • Statistical performance analysis • Derived end-to-end delay distribution for CMS • Derived deterministic end-to-end schedulability criterion that allows local deadline violation

20. dC dB dD C dA B D A E B , c , D dB = dA + B dc = db + c dD = dC + D Can we take advantage of CMS in wireless networks? Priority index at first hop: dA = tA + A tA: arrival time A: priority index increment : priority index increments

21. Input Port Output Port Scheduler 3 9 5 8 14 packet priority Router 5 8 2 4 Additional Challenges in Wireless Multi-Hop Networks • No centralized controller • Only local info available at each node • Random medium access Need distributed priority-driven MAC

22. CTS RTS RTS: Request To Send CTS: Clear To Send DATA ACK Review of IEEE 802.11 • Carrier sense and packet sense random access medium • IEEE 802.11: data transmission part of four-way handshake destination source

23. Review of IEEE 802.11

24. Exploit broadcast nature Piggyback the priorityof Head Of Line (HOL) packet Nodes will collect information about other nodes’ queues in a Scheduling Table 6 5 8 5 CTS Node C (dest.) B 5 A 6 B 5 A 6 Node B (source) 5 RTS Node A Our Approach Scheduling table of node A Source Priority A 6

25. 6 8 8 Node C (dest.) DATA Node B (source) B 5 A 6 B 8 Node A Our Approach • Exploit broadcast nature • Piggyback the priorityof Head Of Line (HOL) packet • Nodes will collect information about other nodes’ queues in a Scheduling Table Scheduling table of node A Source Priority

26. 6 8 8 Node C (dest.) ACK Node B (source) B 5 A 6 B 8 Node A Our Approach • Exploit broadcast nature • Piggyback the priorityof Head Of Line (HOL) packet • Nodes will collect information about other nodes’ queues in a Scheduling Table Scheduling table of node A Source Priority

27. B 5 A 6 C 8 B 5 A 6 C 8 CW DIFS Scheduling table of Node A Scheduling table of Node B CW CW Source Source Priority Priority primary contention window secondary contention window Distributed Priority-Driven MAC Protocol Basic mechanisms: • Piggyback information • Maintain scheduling tables (maybe incomplete) • Map the scheduling table info into backoff policy • Rank=1  0+ rand[0,2mCW] • Rank>1 & first tx attempt  CW + rand[0,CW] • Rank>1 & m-th tx attempt  0 + rand[0,2m+1CW]

28. Only one node believes it has the highest priority packet Primary contention window Secondary contention window • Several nodes believe they have the highest priority packet Primary contention window Secondary contention window • Every nodes believe it has the highest priority packet Primary contention window Secondary contention window IEEE 802.11 Several Scenarios The highest priority packet will capture the channel The higher priority packet will capture the channel with higher probability in primary contention window

29. 1 2 n 1 2 n Simulation Scenario • ns-2 simulations • n exponential on-off traffic sources, traversing 4 hops • uniform priority index increment 60 ms per hop Channel capacity=2 Mb/s, data pkt size=1000 bytes, mean on time=mean off time = 500 ms traffic peak rate = 78 kb/s

30. Simulation Results for Multiple Broadcast Regions • Load>80%: IEEE 802.11 performs worst • Load>90%: CMS outperforms single hop scheduling by up to 50% IEEE 802.11 Single hop sched. Multi-hop coord.

31. Conclusions • CMS provides an mechanism for efficient multi-node communication • Piggybacking information in packet header to allow distributed notes cooperate to provide end-to-end service • In wired networks • Can outperform WFQ • In wireless networks • Improve end-to-end performance

32. 3. Future Work • Long term research plan • QoS provisioning in wireless networks • Short term research topics • Energy-Efficient Distributed Priority-Driven MAC • Reliable MAC Protocol for Multicast in Wireless Networks • Statistical Multiplexing in wireless networks

33. Future Work 1 • Energy consumption of a receiver overhearing the transmission of a packet from other nodes consumes 10% of the energy of transmitting a packet • Mobile nodes’ battery life time is limited • Problem: Derive an algorithm that allows mobile nodes to save energy, while maintaining a distributed priority-driven MAC protocol Energy Efficient Distributed Priority-Driven MAC

34. Future Work 2 • Multicast is an efficient mean to support group communication • Wireless Networks are suitable for multicast • Inherent local broadcast nature of wireless medium • Current reliable MAC protocols are designed for unicast not for multicast • IEEE 802.11 MAC can support multicast, but not reliable • Problem: Drive a MAC Protocol to support reliable multicast in wireless networks Reliable MAC Protocol for Multicast in Wireless Networks

35. Thank you!

36. total traffic needed to be serviced in total service capacity of the j-th hop during I time s-I t s Local Deadline Violation Distribution Consider a target packet of flow i arriving at its j-th hop at time t with priority index s Let Y be the departure of the target packet from its j-th hop

37. total traffic needed to be serviced in total service capacity of node m during Deterministic Schedulability Criterion Consider node m and flow i, let be a bound of deadline violation experienced by flow i at node m

38. C B D A E Motivation Provide better end-to-end service in wired and wireless networks

39. flow 2 flow 3 flow 2 Server 1 Server 2 flow 1 C C A Numerical Example  CMS can be better!

40. Future Work 2 • Mobile nodes play two roles in Ad-Hoc networks • Router • Host • Some mobile nodes may be selfish and refuse to provide service to others • Most routing protocols assume all mobile nodes are cooperative • Problem: How to combine the principle of incentive game with mobile node activities? • Possible approach: Incentive game theory may play a role in this issue An Incentive Routing Algorithm for Ad-Hoc Wireless Networks

41. Future Work 1 • Multicast is an efficient mean to support group communication • Content distribution • Teleconferencing • Wireless Networks are suitable for multicast • Inherent local broadcast nature of wireless medium • Current random access MAC protocols are designed for unicast not for multicast • IEEE 802.11 MAC can support multicast, but not reliable • Problem: Drive a MAC Protocol to support reliable multicast in wireless networks Reliable MAC Protocol for Multicast in Wireless Networks