Truthful algorithms for scheduling selfish tasks on parallel machines

Truthful algorithms for scheduling selfish tasks on parallel machines

We consider the problem of designing truthful mechanisms for scheduling selfish tasks (or agents)—whose objective is the minimization of their completion times—on parallel identical machines in order to minimize the makespan. A truthful mechanism can be easily obtained in this context (if we, of course, assume that the tasks cannot shrink their lengths) by scheduling the tasks following the inc...

Randomized Truthful Algorithms for Scheduling Selfish Tasks on Parallel Machines

Scheduling Selfish Tasks: About the Performance of Truthful Algorithms

This paper deals with problems which fall into the domain of selfish scheduling: a protocol is in charge of building a schedule for a set of tasks without directly knowing their length. The protocol gets these informations from agents who control the tasks. The aim of each agent is to minimize the completion time of her task while the protocol tries to minimize the maximal completion time. When...

Truthful Mechanisms for Scheduling Selfish Related Machines Using ACO

Task scheduling is a major challenge in parallel and distributed systems. Task scheduling techniques in distributed systems are usually based on trusting the Accuracy of the information about the status of resources. In a commercial multiCloud environment, individual providers are focused towards increasing their own profits and do not care about the utility of users and other providers. In suc...

Preemptive Scheduling on Selfish Machines

We consider the problem of scheduling on parallel uniformly related machines, where preemptions are allowed and the machines are controlled by selfish agents. Our goal is to minimize the makespan, whereas the goal of the agents is to maximize their profit. We show that a known algorithm is monotone and can therefore be used to create a truthful mechanism for this problem which achieves the opti...