Delay Efficient Wireless Networking Darpa IT-Manet Project meeting -- Nov. 9, 2006 l1 S1(t) {ON, OFF} l2 S2(t) lN SN(t) Michael J. Neely University of Southern California http://www-rcf.usc.edu/~mjneely/

Outline: My research area -- Stochastic Network Optimization Recent DARPA IT-MANET results since Summer 2006: a. Order Optimal Delay for Opportunistic Scheduling [Allerton Sept. 2006] b. Non-Equilibrium Capacity and Delay analysis for mobile ad-hoc networks [USC CSI Tech Report Oct. 2006] c. Simulations for Delay Enhanced Diversity Backpressure Routing (E-DIVBAR)

Background on Stochastic Network Optimization: -Wireless Networks -Time Varying Channels -Adaptive Transmission Rates -Mobility -Dynamic Power Allocation, Routing, Scheduling for Maximum Throughput [2003, 2005] -Fairness and Utility Optimization [2003, 2005] -Energy Minimization, Average Energy Constraints [2005, 2006] -General Utility Optimization [2006] Online Book: (NOW Publishers) L. Georgiadis, M. J. Neely, L. Tassiulas, “Resource Allocation And Cross-Layer Control in Wireless Networks,” Foundations And Trends in Networking, Vol. 1, No. 1, pp. 1-144, 2006.

Cross-Layer Networking 1 2 3 Node 1 Node 2 Transport Layer Transport Layer Network Layer Network Layer scheduling Multi-Access And PHY Layers Multi-Access And PHY Layers modulation and coding

Cross-Layer Networking 1 2 3 Node 1 Node 2 Transport Layer Transport Layer optimize Exogenous green data Network Layer Network Layer scheduling Multi-Access And PHY Layers Multi-Access And PHY Layers R1(c)(t) node 1 modulation and coding

Cross-Layer Networking 1 2 3 Node 1 Node 2 Transport Layer Transport Layer optimize Networking, Multiple Access, PHY Layers Network Layer Network Layer scheduling Multi-Access And PHY Layers Multi-Access And PHY Layers optimize optimize modulation and coding

Cross-Layer Networking 1 2 3 Node 1 Node 2 Transport Layer Transport Layer optimize Networking, Multiple Access, PHY Layers Network Layer Network Layer scheduling Multi-Access And PHY Layers Multi-Access And PHY Layers modulation and coding

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 l2

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 l2

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Example: Utility Optimization (Utility/Delay Tradeoffs) 1 2 3 4 5 6 7 8 9 l93 l91 l48 l42 Un(c)(t) Rn(c)(t) ln(c) sensor network wired network wireless A general heterogeneous network l1 Av. Delay l2 shrinking radius

Pav X(t) Example: Virtual Power Queues P(t) Average Power Constraint: A wireless device within a network P(t) t=1 t 1 Pav lim virtual power queue P(t) X(t) Pav X(t+1) = max[X(t) - Pav, 0] + P(t) Stabilizing the virtual power queue ==> Ensures Avg. Power Constraints Satisfied

Optimal Tradeoff Theory: Capacity and Delay Tradeoffs for Ad-Hoc Mobile Networks [CISS March 2003, IT June 2005]: -Optimal Tradeoffs via Redundant Packet Transfers Energy/Delay Tradeoffs for Multi-User Wireless Downlinks [INFOCOM March 2006]: -Extends Berry-Gallager Square Root Law to Multi-User systems Utility/Delay Tradeoffs for Wireless Networks [INFOCOM March 2006, JSAC August 2006]: -Establishes a “super-fast” Logarithmic Tradeoff Law.

Recent Results: Order Optimal Delay for Opportunistic Scheduling in Multi-User Wireless Uplinks and Downlinks [Allerton Sept. 2006] l1 S1(t) {ON, OFF} l2 S2(t) prev. bound New bound (LCG) lN SN(t) Simulation (LCG) Previous Result: Avg. Delay <= O(N) New Result: Avg. Delay = O(1) (independent of N) [Longest Connected Group Algorithm (LCG)]

2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Recent Results: 2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Wireless Mesh Networks [CSI Tech Report, Oct. 2006] L(1) 1 2 8 7 4 6 3 5 input rate 9 Arbitrary (perhaps non-ergodic) user mobility. Channel States iid given the current topology. Instantaneous Capacity Region L(t) (assuming users maintain current locations, i.e., fixed topology)

2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Recent Results: 2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Wireless Mesh Networks [CSI Tech Report, Oct. 2006] L(1) 1 2 L(2) 8 7 4 6 3 5 input rate 9 Arbitrary (perhaps non-ergodic) user mobility. Channel States iid given the current topology. Instantaneous Capacity Region L(t) (assuming users maintain current locations, i.e., fixed topology)

2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Recent Results: 2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Wireless Mesh Networks [CSI Tech Report, Oct. 2006] L(1) 1 2 L(2) 8 7 4 L(3) 6 3 5 input rate 9 Arbitrary (perhaps non-ergodic) user mobility. Channel States iid given the current topology. Instantaneous Capacity Region L(t) (assuming users maintain current locations, i.e., fixed topology)

2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Recent Results: 2. Non-Equilibrium Capacity and Delay Analysis for Ad-Hoc Wireless Mesh Networks [CSI Tech Report, Oct. 2006] L(1) 1 2 L(2) 8 7 4 L(3) 6 3 5 input rate 9 Arbitrary (perhaps non-ergodic) user mobility. If input rates within intersection of all L(t): Achieve full throughput with end-to-end average delay that is independent of the timescales of the user mobility process. (can also treat case when rates are not within this intersection)

Halfway through the simulation, node 0 moves (non-ergodically) Communiation Pairs: 0 1, 2 3, … , 8 9 Halfway through the simulation, node 0 moves (non-ergodically) from its initial location to its final location. Node 9 takes a Markov Random walk. 1 2 8 7 4 6 3 5 9 Full throughput is maintained throughout, with noticeable delay increase (at “new equilibrium”), but which is independent of mobility timescales.

More simulation results for the mesh network: Flow control included (determined by parameter V)

Recent Results: 3. Delay Enhanced Diversity Backpressure Routing (E-DIVBAR) [CSI Tech Report, Oct. 2006] 3 2 error 1 broadcasting (conference version: DIVBAR: CISS March 2006)

“Upside Down Layering”: Perform Routing after Transmission Transport Layer Network Multi-Access And PHY Layers Node 1 Node 2 1 2 3 scheduling modulation and coding Networking, Multiple Access, optimize

ExOR [Biswas, Morris 05] DIVBAR, E-DIVBAR [Neely, Urgaonkar 2006]

DIVBAR almost doubles throughput over ExOR. E-DIVBAR achieves capacity (as DIVBAR) but also gets delay that is better than both ExOR and DIVBAR.