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In this paper, we address distributed convergence to fair allocations of CPUresources for time-sensitive applications. We propose a novel resourcemanagement framework where a centralized objective for fair allocations isdecomposed into a pair of performance-driven recursive processes for updating:(a) the allocation of computing bandwidth to the applications (resourceadaptation), executed by the resource manager, and (b) the service level ofeach application (service-level adaptation), executed by each applicationindependently. We provide conditions under which the distributed recursivescheme exhibits convergence to solutions of the centralized objective (i.e.,fair allocations). Contrary to prior work on centralized optimization schemes,the proposed framework exhibits adaptivity and robustness to changes both inthe number and nature of applications, while it assumes minimum informationavailable to both applications and the resource manager. We finally validateour framework with simulations using the TrueTime toolbox in MATLAB/Simulink.

Design and Implementation of Distributed Resource Management for Time Sensitive Applications