Title
Resource Allocation with Stochastic Demands
Abstract
Resources in modern computer systems include not only CPU, but also memory, hard disk, bandwidth, etc. To serve multiple users simultaneously, we need to satisfy their requirements in all resource dimensions. Meanwhile, their demands follow a certain distribution and may change over time. Our goal is then to admit as many users as possible to the system without violating the resource capacity more often than a predefined overflow probability. In this paper, we study the problem of allocating multiple resources among a group of users/tasks with stochastic demands. We model it as a stochastic multi-dimensional knapsack problem. We extend and apply the concept of effective bandwidth in order to solve this problem efficiently. Via numerical experiments, we show that our algorithms achieve near-optimal performance with specified overflow probability.
Year
DOI
Venue
2012
10.1109/DCOSS.2012.16
DCOSS
Keywords
Field
DocType
multiple resource allocation,effective bandwidth,hard disk,stochastic demands,multiple resource,stochastic multi-dimensional knapsack problem,resource allocation,stochastic demand,certain distribution,resource dimension,multiple user,modern computer systems,resource capacity,stochastic multidimensional knapsack problem,knapsack problems,cpu,predefined overflow probability,specified overflow probability,probability,knapsack problem,vectors,satisfiability,upper bound,bandwidth,approximation algorithms,mathematical model
Approximation algorithm,Mathematical optimization,Computer science,Upper and lower bounds,Bandwidth (signal processing),Resource allocation,Knapsack problem,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4673-1693-4
2
0.42
References 
Authors
7
3
Name
Order
Citations
PageRank
Fangfei Chen1655.48
Thomas La Porta280191.33
Mani Srivastava3130521317.38