This paper investigates a zero-sum game played on a weighted connected graph $G$ between two players, the tree player and the edge player. At each play, the tree player chooses a spanning tree $T$ and the edge player chooses an edge $e$. The payoff to the edge player is $cost(T,e)$, defined as follows: If $e$ lies in the tree $T$ then $cost(T,e)=0$; if $e$ does not lie in the tree then $cost(T,e) = cycle(T,e)/w(e)$, where $w(e)$ is the weight of edge $e$ and $cycle(T,e)$ is the weight of the unique cycle formed when edge $e$ is added to the tree $T$. The main result is that the value of the game on any $n$-vertex graph is bounded above by $\exp(O(\sqrt{\log n \log\log n}))$. It is conjectured that the value of the game is $O(\log n)$.
The game arises in connection with the $k$-server problem on a road network; i.e., a metric space that can be represented as a multigraph $G$ in which each edge $e$ represents a road of length $w(e)$. It is shown that, if the value of the game on $G$ is $Val(G,w)$, then there is a randomized strategy that achieves a competitive ratio of $k(1 + Val(G,w))$ against any oblivious adversary. Thus, on any $n$-vertex road network, there is a randomized algorithm for the $k$-server problem that is $k\cdot\exp(O(\sqrt{\log n \log\log n}))$ competitive against oblivious adversaries.
At the heart of the analysis of the game is an algorithm that provides an approximate solution for the simple network design problem. Specifically, for any $n$-vertex weighted, connected multigraph, the algorithm constructs a spanning tree $T$ such that the average, over all edges $e$, of $cost(T,e)$ is less than or equal to $\exp(O(\sqrt{\log n \log\log n}))$. This result has potential application to the design of communication networks. It also improves substantially known estimates concerning the existence of a sparse basis for the cycle space of a graph.
[1]
Fan Chung Graham,et al.
Some intersection theorems for ordered sets and graphs
,
1986,
J. Comb. Theory, Ser. A.
[2]
Julio Michael Stern,et al.
Nested Dissection for Sparse Nullspace Bases
,
1993
.
[3]
Baruch Awerbuch,et al.
Complexity of network synchronization
,
1985,
JACM.
[4]
David Peleg,et al.
An optimal synchronizer for the hypercube
,
1987,
PODC '87.
[5]
Allan Borodin,et al.
On the power of randomization in online algorithms
,
1990,
STOC '90.
[6]
Jose Augusto Ramos Soares,et al.
Graph Spanners: a Survey
,
1992
.
[7]
Lyle A. McGeoch,et al.
Competitive algorithms for on-line problems
,
1988,
STOC '88.
[8]
Allan Borodin,et al.
An optimal online algorithm for metrical task systems
,
1987,
STOC.
[9]
Jan Karel Lenstra,et al.
The complexity of the network design problem
,
1978,
Networks.
[10]
Yuval Rabani,et al.
Competitive k-server algorithms
,
1990,
Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.
[11]
T. C. Hu.
Optimum Communication Spanning Trees
,
1974,
SIAM J. Comput..
[12]
David P. Dobkin,et al.
Generating Sparse Spanners for Weighted Graphs
,
1990,
SWAT.
[13]
Marek Chrobak,et al.
An Optimal On-Line Algorithm for k-Servers on Trees
,
1991,
SIAM J. Comput..