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Reducing Multicast Traffic Load for Cellular Networks using Ad Hoc Networks

Reducing Multicast Traffic Load for Cellular Networks using Ad Hoc Networks. Li Lao (UCLA) Jun-Hong Cui (UCONN). Background. Hybrid cellular/ad hoc networks for unicast applications Increase the coverage of base stations Avoid dead spots

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Reducing Multicast Traffic Load for Cellular Networks using Ad Hoc Networks

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  1. Reducing Multicast Traffic Load for Cellular Networks using Ad Hoc Networks Li Lao (UCLA) Jun-Hong Cui (UCONN)

  2. Background • Hybrid cellular/ad hoc networks for unicast applications • Increase the coverage of base stations • Avoid dead spots • Re-direct traffic from congested cells to non-congested • Improve system throughput • Hybrid cellular/ad hoc networks for multicast applications • Enhance network performance, especially for heterogeneous receivers (Park & Kasera, WCNC’05) • Focus on individual groups only and do not consider QoS when multiple groups co-exist in the network QShine 2005

  3. Our Focus • A base station handles multiple multicast groups simultaneously • Cellular mode: base station may be overloaded • NOTE: we use point to point link for multicast • Ad hoc mode: ad hoc net may be congested • NOTE: broadcast is not assumed • Our approach: to balance between two modes • Goal: • Minimize the workload on the base station while maximizing the utilization of the ad hoc network (without exceeding its capacity) QShine 2005

  4. The Problem • Group Selection Problem: • Base station determines: • How many groups? • Which groups? To be switched to ad hoc mode QShine 2005

  5. An Example T1 A B T2 T3 C D E H F G QShine 2005

  6. Roadmap • Problem Formulation • Network Model • Problem • Proposed Algorithms • Performance Evaluation • Conclusions QShine 2005

  7. Network Model • Network N(V, E) (for a cell) • |V| = m, |E| = n • For a node i, its capacity is Ci • Multicast groups G • |G| = ng • For a group gj G, its required data rate is rj • Bandwidth for gjin cellular mode is: • |gj|x rj • A multicast routing algorithm QShine 2005

  8. Wireless Interference • IEEE 802.11 uses CSMA/CA • RTS/CTS/DATA/ACK D X C A B E X G X F Observation I: Neither the sender’s neighbors nor the receivers’ neighbors can transmit or receive data Observation II: If we want to reserve a unit of bandwidth at two nodes, we must also reserve a unit of bandwidth at their neighbors QShine 2005

  9. Bandwidth Requirement of Multicast Groups • For a multicast group gj, • Compute its multicast tree tj • For each link on tj, compute the required bandwidth at corresponding nodes • Obtain a bandwidth vector bwj = (bw1j, bw2j, …, bwmj), where bwij represents the required bandwidth at node i for gj • For a set of multicast groups G’ • The required bandwidth at node i for these groups: QShine 2005

  10. Example D C A B E G F Bandwidth Vector for (A,B,C,D,E,F,G): (4,4,2,1,4,3,1) QShine 2005

  11. Problem Formulation • Multicast Group SelectionProblem • Input: Ad hoc network with Ci (iV), a set of multicast groupsG with bwj and rj(gjG) • Output: a subset G’ G to maximize the bandwidth savings • Constraint: (iV) • Essentially a Multi-dimensional Knapsack Problem • Input: A knapsack with m-dimensional size (b1, …, bm), and a set of itemsS = 1, …, n, each having a size rj = (r1j, …, rmj) and a value vj • Output: A subset S’  S that maximizes the values • Constraint: (i[1,m]) Group  Item Ad hoc network  Knapsack QShine 2005

  12. Roadmap • Problem Formulation • Proposed Algorithms • Integer Linear Program • Dynamic Algorithm • Naive Dynamic Algorithm • Performance Evaluation • Conclusions QShine 2005

  13. Integer Linear Program • Define: • Objective: maximize bandwidth savings • Constraint: node capacity QShine 2005

  14. Dynamic Algorithm • Utility function for each group gjG • Group g join: O(mn+mng) • Admit g in ad hoc mode and reserve bandwidth if enough resource • Otherwise, try to swap g with an existing group g’ in ad hoc mode such that • u(g’) < u(g) • If g’ releases its bandwidth, g can be admitted • If there are more than one such groups, the one with the smallest utility should be selected as g’ • Group g leave: O(mnng) • Release bandwidth • Try to select a group g’to be swapped in  Bandwidth savings if the group is selected  Total amount of required bandwidth QShine 2005

  15. Naive Dynamic Algorithm • Group join • If enough resource in the ad hoc network, admit this group in ad hoc mode and reserve bandwidth • Otherwise use cellular mode • O(mn) • Group leave • If ad hoc mode, release bandwidth • O(m) QShine 2005

  16. Roadmap • Problem Formulation • Proposed Algorithms • Performance Evaluation • Conclusions QShine 2005

  17. Simulation Settings • Wireless network • Up to 120 nodes • A cell of 500*500 m2 • Communication range: 115m • Channel capacity: 100~500 units • Multicast groups • Group size uniformly distributed (mean: 20~100) • Group members randomly distributed in the network and one member randomly selected as source • Group arrivals follow a Poisson distribution and lifetime follows an exponential distribution • Each group requires 1 unit of bandwidth • 80 active groups QShine 2005

  18. Metrics • Number of admitted members • Number of admitted groups QShine 2005

  19. Impact of Network Density Average group size: 20, Channel capacity: 500 QShine 2005

  20. Impact of Channel Capacity Network nodes: 120, Average group size: 20 QShine 2005

  21. Impact of Group Size Network nodes: 120, Channel capacity: 100 QShine 2005

  22. Roadmap • Problem Formulation • Proposed Algorithms • Performance Evaluations • Conclusions QShine 2005

  23. Conclusions • Developed a simple and effective model for computing bandwidth requirement of multicast groups in wireless networks • Formulated the multicast group selection problem as a multi-dimensional knapsack problem • Proposed an ILP formulation and a utility-based dynamic algorithm • Simulation study has shown that the dynamic algorithm can achieve near-optimal solutions • Future Work: • Member dynamics • Distributed implementation QShine 2005

  24. Questions? Thank you! QShine 2005

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