TY - JOUR
AU1 - Chakaravarthy, Venkatesan
AU2 - Choudhury, Anamitra
AU3 - Gupta, Shalmoli
AU4 - Roy, Sambudha
AU5 - Sabharwal, Yogish
AB - We consider the problem of scheduling a set of jobs on a system that offers certain resource, wherein the amount of resource offered varies over time. For each job, the input specifies a set of possible scheduling instances, where each instance is given by starting time, ending time, profit and resource requirement. A feasible solution selects a subset of job instances such that at any timeslot, the total requirement by the chosen instances does not exceed the resource available at that timeslot, and at most one instance is chosen for each job. The above problem falls under the well-studied framework of unsplittable flow problem on line. The generalized notion of scheduling possibilities captures the standard setting concerned with release times and deadlines. We present improved algorithms based on the primalâ€“dual paradigm, where the improvements are in terms of approximation ratio, running time and simplicity.
TI - Improved algorithms for resource allocation under varying capacity
JF - Journal of Scheduling
DO - 10.1007/s10951-017-0515-3
DA - 2017-02-16
UR - https://www.deepdyve.com/lp/springer-journals/improved-algorithms-for-resource-allocation-under-varying-capacity-HJxiwybiF8
SP - 313
EP - 325
VL - 21
IS - 3
DP - DeepDyve