1. CPSC 689: Discrete Algorithms for Mobile and Wireless Systems Spring 2009 Prof. Jennifer Welch

2. Discrete Algs for Mobile Wireless Sys2 Lecture 26  Topic: Maximal Independent Set  Sources: Luby Schneider & Wattenhofer Linial MIT 6.885 Fall 2008 slides

3. Discrete Algs for Mobile Wireless Sys3 Overview  Recall that a minimum connected dominating set is a useful substructure of a graph representing a network: routing medium access control coverage  Computing a MCDS in a general graph is NP-complete  What about special-case graphs that still reflect the reality of wireless networks? UDG too restrictive QUDG still too restrictive let's try growth-bounded graphs (GBG), a.k.a. bounded independence graphs (BIG)

4. Discrete Algs for Mobile Wireless Sys4 Overview  In BIG model, a maximal independent set is a constant approximation of a MCDS A MIS is an independent subset S of the nodes of a graph (none of the nodes in S are neighbors), and no superset of S is independent  [SW] paper gives an O(log*n) time algorithm for MIS in BIG model log*n is number of times you can take the log of n until reaching 1 algorithm is distributed, deterministic, and does not require location information  Running time is optimal (cf. paper by Linial)

5. Discrete Algs for Mobile Wireless Sys5 Unit Disk Graphs R R Wireless networks often modeled as unit disk graphs

6. Discrete Algs for Mobile Wireless Sys6 More Realistic Graphs

7. Discrete Algs for Mobile Wireless Sys7 Bounded Independence Graph  Even more general than quasi unit disk graphs  No links between far-away nodes  Close nodes tend to be connected  In particular: Densely covered area  many connections  bounded neighborhood  bounded independent set

8. Discrete Algs for Mobile Wireless Sys8 Bounded Independence Graphs (BIGs)  Definition: Given a function f(r), a graph G=(V,E) is f(r)-independence bounded if for all nodes v in V and all r ≥ 0, the size of a maximum IS in the r-neighborhood of v is at most f(r).  Note that f is only a function of r and in particular independent of the number of nodes n.

9. Discrete Algs for Mobile Wireless Sys9 Bounded Independence Graphs (BIGs)  Typically require that f(r) = poly(r). It can never be more than exponential.  UDGs and QUDGs are independence- bounded with f(r) = O(r 2 ).

10. Discrete Algs for Mobile Wireless Sys10 Maximal vs. Maximum IS a maximum independent seta maximal independent set

11. Discrete Algs for Mobile Wireless Sys11 MIS and DS  A MIS is a dominating set (DS) If S is an IS but does not dominate some node, then the undominated node can be added to S while maintaining the independence property  But a DS is not necessarily independent two dominators are allowed to be neighbors (not independent)

12. Discrete Algs for Mobile Wireless Sys12 MIS and MDS  Theorem: On an f(r)-independence bounded graph G, a MIS is a f(1)-approximation of an MDS.  Proof: Consider any maximal IS S of G. Suppose T is a minimum DS of G. Every node in S is either in T or is a neighbor of some dominator t in T Since G is a f(r)-BIG, t has at most f(1) elements of S as its neighbors So |S| ≤ f(1) |T|

13. Discrete Algs for Mobile Wireless Sys13 Distributed MIS Algorithm  For general graphs [Luby]: A simple parallel algorithm for the MIS problem (similar algorithm in [Alon,Babai,Itai])  Randomized algorithm  Runs in O(log n) rounds in expectation and with high probability  Can we do better in special-case graphs?

14. Discrete Algs for Mobile Wireless Sys14 Log-Star MIS Algorithm for BIGs  Assumptions: Every node has a unique ID between 1 and n For simplicity, assume that all nodes know f(r) and n (not necessary) For simplicity, synchronous model (not necessary)  Main result of [SW]: O(log*n) time MIS algorithm for bounded independence graph

15. Discrete Algs for Mobile Wireless Sys15 Algorithm: Basic Structure  During the algorithm, each node is always in one of 5 states: competitor: Node actively competes to be in MIS dominator: Node has joined the MIS dominated: Node has a neighbor in the MIS, will definitely not join MIS ruler: Node not actively in competition, will compete again actively if there are no neighboring competitors left ruled: Neighbor of ruler, does not start competing again before all neighboring rulers become ruled themselves.

16. Discrete Algs for Mobile Wireless Sys16 Algorithm: Basic Structure  Algorithm consists of f(f(2) + 3) stages Each stage consists of f(2) + 1 phases  Each phase consists of log*n + 2 competitions Each competition needs a constant number of rounds  So total number of rounds is O(1)*(log*n + 2)*(f(2)+1)*f(f(2)+3) which is O(log*n) since f(c) = O(1) when c = O(1)

17. Discrete Algs for Mobile Wireless Sys17 Competitions  Every competitor v starts a competition with a number r v and computes new r v ’ initially r v = ID(v)  Computation of r v ’: u: neighboring competitor with minimal r u if r u > r v then r v ’ = 0 else, r v ’ is computed from the base-2 representations of r v and r u : r v ’ is position of highest bit that is 1 in r v and 0 in r u (position of least significant bit is 1)

18. Discrete Algs for Mobile Wireless Sys18 Competitions  r v ’ is position of highest bit that is 1 in r v and 0 in r u position of least significant bit is 1  Examples: r v = (10100010) 2, r u = (10010110) 2  r v ’ = 6 r v = (00101000) 2, r u = (00100101) 2  r v ’ = 4

19. Discrete Algs for Mobile Wireless Sys19 Competition: New State  Compute new r v ’ based on r v and min r u among neighboring competitors  Update state based on new values of v and neighbors: If r v ’ < r u ’ for all neighboring competitors  v becomes dominator Else if neighbor of v becomes dominator  v becomes dominated Else if r v ’ · r u ’ for all neighboring competitors  v becomes ruler Else if v has neighboring ruler  node becomes ruled Else v stays competitor

20. Discrete Algs for Mobile Wireless Sys20 Competition: New State  Lemma: Dominators always form an independent set. No 2 adjacent nodes can become dominator together. Nodes that are dominated do not compete any further. Only competing nodes can become dominator.

21. Discrete Algs for Mobile Wireless Sys21 Reducing the Competitors  Lemma: After log*n + 2 competitions, no node is a competitor any more.  Proof: Initially, r v = ID(v), hence, r v uses at most log n bits Hence, r v ’ uses at most log log n bits After log*n + 2 competitions, r v is in {0,1} All nodes v with r v =0 become dominator or ruler Neighbors become dominated or ruled If r v =1 and all neighboring competitors u have r u =1, v becomes ruler

22. Discrete Algs for Mobile Wireless Sys22 Phase  log*n+2 competitions are called a phase  For next phase: All rulers become competitors again All r v are set back to ID(v)

23. Discrete Algs for Mobile Wireless Sys23 Stage  Main technical lemma: No node becomes a ruler in the (f(2)+1) st phase. Thus, after f(2)+1 phases there are only nodes that are dominators, dominated, or ruled.  Proof: Read the paper.  f(2)+1 phases are called a stage.  In new stage, ruled nodes become competitors again (note: there are no rulers any more…)

24. Discrete Algs for Mobile Wireless Sys24 Proof of Progress  Lemma: Let v be a competitor at the beginning of a stage. During the stage, a node at distance at most f(2)+1 becomes dominator.  Proof: At the end of a stage, each node is ruled, dominated, or a dominator Show that after i phases, there is a node at distance at most i that is not ruled

25. Discrete Algs for Mobile Wireless Sys25 Proof of Progress  Show that after i phases, there is a node at distance at most i that is not ruled  Induction on i: Clear for i=0 (v is not ruled) Let w be node that is not ruled at distance at most i after i phases If w does not become ruled in (i+1) st phase, ok. If w becomes ruled in a competition of the (i+1) st phase, some neighbor w’ becomes a ruler (w’ is at distance at most i+1). w’ remains a ruler until the end of the phase and then becomes a competitor.

26. Discrete Algs for Mobile Wireless Sys26 Proof of Progress  After f(2) phases, there is a ruler at distance at most f(2) or a dominator at distance at most f(2)+1.  If it is a ruler, itself or a neighbor of it becomes dominator in phase f(2)+1.  Thus if v is a competitor at the beginning of a stage, then during the stage, a node at distance at most f(2)+1 becomes a dominator.

27. Discrete Algs for Mobile Wireless Sys27 Proof of Progress  Theorem: The algorithm terminates with a MIS after at most f(f(2)+1) stages.  Proof: The algorithm terminates as soon as there are no ruled nodes at the end of a stage (i.e., all nodes are dominators or dominated) Suppose in contradiction there is still a ruled node v after stage f(f(2)+1). v was a competitor in all f(f(2)+1) stages. In every stage, a node in (f(2)+1)-neighborhood of v joins the MIS At most f(f(2)+1) nodes in (f(2)+1)-neighborhood of v can join an ind. set (because of BIG model) Hence, the ind. set is maximal and v cannot be a competitor any more.

28. Discrete Algs for Mobile Wireless Sys28 Comments  In the paper, the algorithm is described in a way that does not require knowledge of f(r) and n stages and phases need to be locally synchronized algorithm works for all graphs, time complexity depends on graph  Algorithm is asymptotically optimal: Result in [Linial]: Any deterministic algorithm needs at least  (log*n) rounds to color a ring with O(1) colors. From a c-coloring, a MIS can be computed in c rounds. Since rings are bounded independence graphs, algorithm is asymptotically tight.