Abstract
Fair resource allocation is usually studied in a static context, in which a fixed amount of resources is to be shared. In dynamic resource allocation one usually tries to assign resources instantaneously so that the average share of each user is split fairly. The exact definition of the average share may depend on the application, as different applications may require averaging over different time periods or time scales. Our main contribution is to introduce new refined definitions of fairness that take into account the time over which one averages the performance measures. We examine how the constraints on the averaging durations impact the amount of resources that each user gets. We also address how the spatial component, which arises due to mobility of users, influences resource sharing under different fairness criteria. We demonstrate these new concepts via example applications.
Highlights
Let us consider some set S of resource that we wish to distribute among I users by assigning user i a subset Si of it
We have introduced T -scale fairness and multiscale fairness
The notion of multiscale fairness allows one to use a single optimization criterion for resource allocation when different applications are present in the network
Summary
Let us consider some set S of resource that we wish to distribute among I users by assigning user i a subset Si of it. We adopt the idea that fair allocation should not be defined in terms of the object that is split but in terms of the utility that corresponds to the assignments. This is in line with the axiomatic approach for defining the Nash bargaining solution for example. With this in mind, we may discover that the set of N slots cannot always be considered as a resource to be assigned fairly. The utility of the application is defined as a function of the instantaneous rate, i.e. the number of slots it receives during each period of 100 msec.
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