View
221
Download
2
Tags:
Embed Size (px)
Citation preview
1
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
A self-stabilizing algorithm for the maximum flow
problem
Presented ByNiranjan
Sukumar Ghosh, Arobinda Gupta and Sriram V. Pemmaraju
6th May 2004
2
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Paper Outline
• Introduction to maximum flow problem
• Model of computation• Maximum flow algorithm for acyclic
graphs• Proof of correctness• Experimental Evaluation• Conclusion – Failure Model,
Algorithm for arbitrary graph
3
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Algorithms for Max Flow
• Sequential Algorithms– Ford and Fulkerson : Picks augmented paths
arbitrarily– Edmonds and Karp : Use BFS to construct augmented
paths– Goldmerg and Tarjan : Works in localized manner -
O(ne log(n2/e))
• Parallel Algorithms– Shiloach and Vishkin : O(n2logn) using O(n) processors
• Distributed Algorithms– Based mainly on the Glodmerg and Tarjan
• Self-Stabilized Algorithms– Distributed Algorithms
• Fault Tolerant• Adjust to dynamic changes in the network topology
4
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Self-Stabilization
• Introduced by Dijkstra [1974]• S is self-stabilizing with respect to
predicate P if it satisfies the following two properties:– Closure: P is closed under the execution of S.– Convergence: Starting from an arbitrary
global state, S is guaranteed to reach a global state satisfying P within a finite number of state transitions
• Failure Model : Transient Failure– An event that may the change the state of
the system, but not its behavior
5
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Preliminaries
• Skew Symmetry• Capacity Constraint• Residual Graph• Residual Capacity• Feasible flow• Max-flow, Min-cut
theorem
These terms are used in the same context
6
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Model of Computation
• Each node i in G corresponds to a process called process i that executes a program asynchronously
• Each edge (i, j) corresponds to a bidirectional link b/w process i and process j
• Process i local variables can be read by its neighbors but written only by process i
• Program Model (expressed using guarded commands [Dijkstra 1975])
7
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Maximum Flow Algorithm for Acyclic Graphs
• G is a acyclic digraph• For each edge (i,j), f(i,j): current flow
from node i to node j
• Both process i and process j can read from and write into the variable f(i,j)
• Each node i contains a single variable d(i): length of the shortest path form s to i in the residual graph Gf D(i): [0…n]
8
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Key Idea…
• For any node i ,– Demand(i) = Of(i) – If(i)
• Demand(t) = Infinity
• Each node i tries to restore the flow conservation constraint demand(i)=0 by– Reducing its inflow if demand(i) < 0– Increasing its inflow and or reducing its
outflow if demand(i) > 0
• Each node with positive demand attempts to pull flow via a shortest path from s to itself in Gf
• Use BFS to keep track of shortest paths from s to all nodes in Gf
9
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Notation
• Distinguished Nodes Node s remains idle with d(s) = 0 Node t executes the same program as other processes with demand(t) = INFINITY
i
bc
ay
x
Residual Graph
d = 5
d = 3d = 4
d = 5
IN(i) = {a, b, c}
D(i) = {4, 5, 6}
10
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Algorithm
• S1: Each node i, computes its d-value by examining the values d(j) for all (j,i)=Ef. d(i) = min{D[i], n}
• S2: If demand(i)<0, then total flow along incoming edges in G is reduced irrespective of d-values
• S3: if demand(i)>0 and d(i)<n, then i pulls flow along an incoming edges (j,i)=Ef and d(j)=d(i)-1
• S4: if demand(i) and d(i)=n, then there is no path from s to i in Gf and it reduces the outflow.
11
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Algorithm
• Assumption: f(i,j) never exceeds C(i,j) - New action (A5) that appropriately reduces the flow on an incident edge that has flow in excess of capacity
12
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Example
Node: a Guard: S2
Node: b Guard: S1
Node: t Guard: S3
Node: b Guard: S3
C(s,a) = C(b,t) = 2
C(a,b) = 1
13
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Example …
Node: a Guard: S3
Node: b Guard: S1
Node: b Guard: S4
Node: t Guard: S1
C(s,a) = C(b,t) = 2
C(a,b) = 1
14
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Results
15
Outline
Max Flow Algorithm
Model of Computation
Proposed Algorithm
Self Stabilization
Contribution
Contribution of this paper
• First distributed self-stabilizing algorithm for max-flow
• Inherently tolerant to transient faults• Automatically adjust to topology
changes– Arbitrary addition or deletion of edges– Addition and deletion of nodes provided that
#nodes in the network is bounded– Arbitrary changes in the capacities of the
edges
• Requires O(n2) in average case settings