LCN 2007, Dublin 1 Non-bifurcated Routing in Wireless Multi- hop Mesh Networks by Abdullah-Al Mahmood and Ehab S. Elmallah Department of Computing Science University of Alberta Ahmed Kamal Department of Electrical and Computer Engineering Iowa State University Research supported by NSERC

LCN 2007, Dublin 2 Outline Introduction Problem Formulation Solution Approach Some Related Work Simulation Results Concluding Remarks

LCN 2007, Dublin 3 Introduction General Objectives  Fixed wireless broadband access  Support applications with different service requirements (e.g., high data rate, low delay jitter etc.)

LCN 2007, Dublin 4 Introduction Mesh BS Mesh BS (y) Mesh BS (x) Mesh BS Internet Gateway Subscribers d1(x)d1(x) d2(x)d2(x) d |D(x)| (x) … Demand D(x)

LCN 2007, Dublin 5 Introduction Mesh BS Mesh BS (y) Mesh BS (x) Mesh BS Internet Gateway Subscribers s1(x)s1(x) s2(x)s2(x) s |D(x)| (x) … Accepted Demand S(x) flow f(x, y)

LCN 2007, Dublin 6 Problem with Splitting Flows Example: Routing streaming data End user experiences poor stream quality or unusual delay Packets 1,2, … 7 3,4 1,2,5,6,7

LCN 2007, Dublin 7  Non-bifurcated Flows A sequence of uniquely identifiable packets Indivisibly follows the same path without rerouting  Routers do not need synchronization  Interference follows protocol model (conforming to RTS-CTS-DATA-ACK sequence in IEEE family of standards) System Model

LCN 2007, Dublin 8 Problem Formulation with Single Channel Notations  f(X,Y): aggregate flow between sets of routers X and Y  f(D(x)), f(S(x)): sum of flow values in the vectors D(x) and S(x) respectively  E int T (x): set of edges having one end within interference range of x  f(E int T (x)): sum of flow values along edges in E int T (x)  C(x): Available channel capacity at router x

LCN 2007, Dublin 9 Problem Formulation with Single Channel Objective: Subject to: Channel capacity constraint: l(x) = f(x, V) + f(V, x) + E int T (x) Maximizef(V, GW) sum of all flows from V to gateway x f(V, x)f(x, V) E int T (x ) C(x)C(x) ≤

LCN 2007, Dublin 10 Flow conservation constraint: Flow indivisibility constraint: d i (x) Î D(x) is assigned a single route from x to a gateway in G Problem Formulation with Single Channel f(x, V) Outgoing Flows f(V, x) + f(S(x)) Incoming Flows and Accepted Flows = g y x di(x)di(x) di(x)di(x) di(x)di(x)

LCN 2007, Dublin 11 Remarks We seek assignment of flows to edges Implementation: we use source routing in order to realize a set of computed flows Challenges  Achieved flow values = planned flows?  Any improvement over a sophisticated (ad-hoc) routing protocol (e.g. DSR)?

LCN 2007, Dublin 12 Solution Approach Flow augmenting paths (FAP) are used in classical network flow problems Example: Our problem under certain constraints is NP-complete Traditional FAPs do not work for our problem sbat sbat 3/84/4 1/9 7/80/4 5/9

LCN 2007, Dublin 13 Solution Approach We propose the use of Interference Constrained FAPs (IC-FAP) IC-FAPs take into account interference in system model Challenges  Finding IC-FAPs efficiently (i.e., in polynomial time?)  Suitability of using IC-FAPs for finding near optimal solutions (i.e. Are IC-FAPs sufficient?)

LCN 2007, Dublin 14 IC-FAP: An Example

LCN 2007, Dublin 15 An IC-FAP Search Heuristic Idea  Forward to nodes closer to gateways  Keep track of interference and consider alternative paths

LCN 2007, Dublin 16 An Example j kih dfe a bc g (3,5):  g  (4,4):  g,f  (4,0):  g,f  (0,0):  g,f,c,b  (3,0):  g,f,c 

LCN 2007, Dublin 17 Some Related Work [Draves et al.: MobiCom 2004]: “Routing in multi-radio, multi-hop wireless mesh networks”  Proposed a metric based on transmission delays  Chooses channel that is likely to decrease delay

LCN 2007, Dublin 18 Some Related Work [Raniwala and Chiueh.: INFOCOM 2005]: “Architecture and algorithms for an IEEE based multi-channel wireless mesh network”  A heuristic solution  Three stages : tree construction, node to interface binding and interface to channel binding  Key idea is balancing traffic load

LCN 2007, Dublin 19 Some Related Work [Kodialam and Nandagopal: MobiCom 2005]: “Characterizing the capacity region in multi-radio multi- channel wireless mesh networks”  Models the problem as a linear program  Provides a framework for estimation of capacity region  Flows are allowed to split among multiple paths  Assumes synchronous operation of routers

LCN 2007, Dublin 20 Some Related Work [Alicherry et al.: Journal on Selected Areas of communication 2006]: “Joint channel assignment and routing for throughput optimization in multiradio wireless mesh networks”  Assumes a synchronous model  Formulates solution as a linear programming relaxation  The algorithm works in stages of solution refinement  The final solution allows bifurcation of flows

LCN 2007, Dublin 21 Simulation Results Topology WMN Parameters Channel Capacity 100 units Radio Range of Mesh Router 112 m Radio Range of Subscriber Units 29 m Maximum Subscriber per Router 10 Flow Demand per Subscriber 1 unit Traffic Parameters 1 Unit of flow 40 Kbps (Application Data) Application-level Packet Size Uniform: [200, 300] bytes Packet Inter-arrival Time Uniform: [30, 50] ms

LCN 2007, Dublin 22  Findings: The average throughput is higher at different traffic loads. Simulation Results Comparison with DSR : Average throughput

LCN 2007, Dublin 23  Findings: The minimum throughput is also higher at different traffic loads. Simulation Results Comparison with DSR : Minimum throughput

LCN 2007, Dublin 24  Findings: The delay jitter is comparatively less Simulation Results Comparison with DSR : Delay Jitter

LCN 2007, Dublin 25 Simulation Results: Insights One source of improvement from DSR results from route stability DSR is not designed for (max-min) fairness

LCN 2007, Dublin 26 Concluding Remarks The