We provide a new approach to the on-line load balancing problem in the case of restricted assignment of temporary weighted tasks. The approach is very general and allows us to derive on-line algorithms whose competitive ratio is characterized by some combinatorial properties of the underlying graph G representing the problem: in particular, the approach consists in applying the greedy algorithm to a suitably constructed subgraph of G. In the paper, we prove the NP-hardness of the problem of computing an optimal or even a c-approximate subgraph, for some constant c > 1. Nevertheless, we show that, for several interesting problems, we can easily compute a subgraph yielding an optimal on-line algorithm. As an example, the effectiveness of this...
AbstractWe study load balancing problems of temporary jobs (i.e., jobs that arrive and depart at unp...
We study an online assignment problem where the offline servers have capacities, and the objective i...
In this paper we study the problem of assigning unit-size tasks to related machines when only limite...
AbstractWe provide a new approach to the on-line load balancing problem in the case of restricted as...
We provide a new approach to the on-line load balancing problem in the case of restricted assignment...
We provide a new simpler approach to the on-line load balancing problem in the case of restricted as...
AbstractThe setup for our problem consists of n servers that must complete a set of tasks. Each task...
AbstractWe consider the on-line load balancing problem where there are m identical machines (servers...
The setup for our problem consists of n servers that must complete a set of tasks. Each task can be ...
We consider load-balancing in the following setting. The on-line algorithm is allowed to use $n$ mac...
We consider the on-line load balancing problem where there are m identical machines (servers) and a ...
This paper considers the non-preemptive on-line load balancing problem where tasks have limited dura...
We consider the problem of scheduling permanent jobs on related machines in an on-line fashion. We d...
We consider load balancing in the following setting. The on-line algorithm is allowed to use n machi...
We investigate a semi-online variant of load balancing with restricted assignment. In this problem, ...
AbstractWe study load balancing problems of temporary jobs (i.e., jobs that arrive and depart at unp...
We study an online assignment problem where the offline servers have capacities, and the objective i...
In this paper we study the problem of assigning unit-size tasks to related machines when only limite...
AbstractWe provide a new approach to the on-line load balancing problem in the case of restricted as...
We provide a new approach to the on-line load balancing problem in the case of restricted assignment...
We provide a new simpler approach to the on-line load balancing problem in the case of restricted as...
AbstractThe setup for our problem consists of n servers that must complete a set of tasks. Each task...
AbstractWe consider the on-line load balancing problem where there are m identical machines (servers...
The setup for our problem consists of n servers that must complete a set of tasks. Each task can be ...
We consider load-balancing in the following setting. The on-line algorithm is allowed to use $n$ mac...
We consider the on-line load balancing problem where there are m identical machines (servers) and a ...
This paper considers the non-preemptive on-line load balancing problem where tasks have limited dura...
We consider the problem of scheduling permanent jobs on related machines in an on-line fashion. We d...
We consider load balancing in the following setting. The on-line algorithm is allowed to use n machi...
We investigate a semi-online variant of load balancing with restricted assignment. In this problem, ...
AbstractWe study load balancing problems of temporary jobs (i.e., jobs that arrive and depart at unp...
We study an online assignment problem where the offline servers have capacities, and the objective i...
In this paper we study the problem of assigning unit-size tasks to related machines when only limite...