Selfish Load Balancing and Atomic Congestion Games
Algorithmica
(Almost) optimal coordination mechanisms for unrelated machine scheduling
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Modern Operating Systems
Efficient coordination mechanisms for unrelated machine scheduling
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Coordination mechanisms for selfish scheduling
Theoretical Computer Science
Intrinsic robustness of the price of anarchy
Proceedings of the forty-first annual ACM symposium on Theory of computing
Weighted congestion games: price of anarchy, universal worst-case examples, and tightness
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part II
Inner product spaces for MinSum coordination mechanisms
Proceedings of the forty-third annual ACM symposium on Theory of computing
Local smoothness and the price of anarchy in atomic splittable congestion games
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Preemptive coordination mechanisms for unrelated machines
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Congestion games with capacitated resources
SAGT'12 Proceedings of the 5th international conference on Algorithmic Game Theory
Coordination mechanisms from (almost) all scheduling policies
Proceedings of the 5th conference on Innovations in theoretical computer science
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We study coordination mechanisms for Scheduling Games (with unrelated machines). In these games, each job represents a player, who needs to choose a machine for its execution, and intends to complete earliest possible. In the paper, we focus on a general class of ℓk-norm (for parameter k) on job completion times as social cost, that permits to balance overall quality of service and fairness. Our goal is to design scheduling policies that always admit a pure Nash equilibrium and guarantee a small price of anarchy for the ℓk-norm social cost. We consider strongly-local and local policies (the policies with different amount of knowledge about jobs). First, we study the inefficiency in ℓk-norm social costs of a strongly-local policy SPT that schedules the jobs non-preemptively in order of increasing processing times. We show that the price of anarchy of policy SPT is $O(k^{\frac{k+1}{k}})$ and this bound is optimal (up to a constant) for all deterministic, non-preemptive, strongly-local and non-waiting policies (non-waiting policies produce schedules without idle times). Second, we consider the makespan (ℓ∞-norm) social cost by making connection within the ℓk-norm functions. We present a local policy Balance. This policy guarantees a price of anarchy of O(logm), which makes it the currently best known policy among the anonymous local policies that always admit a pure Nash equilibrium.