Makespan scheduling on uniformly related machines
n tasks with weights w1,…,wn
m parallel mach in es with speeds s1,…,sm
The load of machine j∈[m] under the assignment A is:
Objective: minimize the make span, aka the maximum load overall machines
i
A
An assignment A is a pure Nash equilibrium if for all players i ∈ [n] and all machines j ∈ [m]:
Start with empty assignment: lj := 0 for all j ∈ [m]
Sort task in non-increasing order w1 ≥ w2 ≥ ··· ≥ wn
For i from 1 to n do
returnA
function LPTAlgorithm(arr) {
var res = [];
arr.forEach((val) => {});
}
Every instance of the load balancing game admits a pure Nash equilibrium. // 所有负载平衡游戏的实例都可以使用纯纳什均衡
Improvement step: change to best response
Single player moves his task to the machine that minimizes his cost. // 减少花销
Example:
Best response sequences
take the strategic nature of the players into account
model convergence
Theorem 2.3
For every instance of the load balancing game with
related machines
every best response sequence terminates.
Remark
Theorem 2.4
Theorem 2.5
Lemma 2.6
worst case ratio
between the social cost in some Nash equilibrium (NE) and the optimum social cost.Goal: Find the exact PoA for a class of games and type of equilibria.
Upper bound α: show that for all such instances and all such equilibria the PoA is at most α.
Lower bound α: find such an instance and such an equilibrium where the PoA is at least α.
Form=2,theexampleonpreviousslideprovesthelowerbound in blue.
Exercise:
Generalise this example to match the bound for all m.