For the problem of online real-time scheduling of jobs on a single processor, previous work presents matching upper and lower bounds on the competitive ratio that can be achieved by a deterministic algorithm. However, these results only apply to the non-strategic setting in which the jobs are released directly to the algorithm. Motivated by emerging areas such as grid computing, we instead consider this problem in an economic setting, in which each job is released to a separate, self-interested agent. The agent can then delay releasing the job to the algorithm, inflate its length, and declare an arbitrary value and deadline for the job, while the center determines not only the schedule, but the payment of each agent. For the resultin...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
We propose a new approach to competitive analysis in online scheduling by introducing the novel conc...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
For the problem of online real-time scheduling of jobs on a single processor, previous work presents...
We study the online version of the classical parallel machine scheduling problem to minimize the tot...
We study the online version of the classical parallel machine scheduling problem to minimize the tot...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Abstract We study the online version of the classical parallel machine scheduling problem to minimiz...
We explore the machine-minimizing job scheduling problem, which has a rich history in the line of re...
We study the online version of the scheduling problem View the MathML source involving selfish agent...
AbstractWe study the online version of the scheduling problem Q∥Cmax involving selfish agents, consi...
We consider the problem of scheduling a maximum profit selection of jobs on m identical machines. Jo...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
We propose a new approach to competitive analysis in online scheduling by introducing the novel conc...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
For the problem of online real-time scheduling of jobs on a single processor, previous work presents...
We study the online version of the classical parallel machine scheduling problem to minimize the tot...
We study the online version of the classical parallel machine scheduling problem to minimize the tot...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Abstract We study the online version of the classical parallel machine scheduling problem to minimiz...
We explore the machine-minimizing job scheduling problem, which has a rich history in the line of re...
We study the online version of the scheduling problem View the MathML source involving selfish agent...
AbstractWe study the online version of the scheduling problem Q∥Cmax involving selfish agents, consi...
We consider the problem of scheduling a maximum profit selection of jobs on m identical machines. Jo...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...
We propose a new approach to competitive analysis in online scheduling by introducing the novel conc...
Traditional optimization models assume a central decision maker who optimizes a global system perfor...