Best effort strategy and virtual load for asynchronous iterative load balancing

Most of the time, asynchronous load balancing algorithms are extensively studied from a theoretical point of view. The Bertsekas and Tsitsiklis' algorithm [1] is undeniably the best known algorithm for which the asymptotic convergence proof is given. From a practical point of view, when a node needs to balance a part of its load to some of its neighbors, the algorithm's description is unfortunately too succinct, and no details are given on what is really sent and how the load balancing decisions are made. In this paper, we propose a new strategy called best effort which aims at balancing the load of a node to all its less loaded neighbors while ensuring that all involved nodes by the load balancing phase have the same amount of load. Moreover, since asynchronous iterative algorithms are less sensitive to communication delays and their variations [2], both load transfer and load information messages are dissociated. To speedup the convergence time of the load balancing process, we propose a clairvoyant virtual load heuristic. This heuristic allows a node receiving a load information message to integrate the future virtual load (if any) in its load's list, even if the load has not been received yet. This leads to have predictive snapshots of nodes' loads at each iteration of the load balancing process. Consequently, the notified node sends a real part of its load to some of its neighbors, taking into account the virtual load it will receive in the subsequent time-steps. Based on the SimGrid simulator, some series of test-bed scenarios are considered and several QoS metrics are evaluated to show the usefulness of the proposed algorithm. (C) 2018 Elsevier B.V. All rights reserved.