Diffusive Algorithms for Dynamic Load Balancing in Massively Parallel Architectures

The paper investigates the area of dynamic load balancing with the specific target of massively parallel architectures. The lack of centralisation makes the architectures cost effective and scalable but requires suitable simple system policies without centralisation and with decisions based on a limited amount of information. The paper analyses the class of load balancing policies inspired to diffusion and shows how they can lead a system to a load balanced configuration. The paper evaluates and compares the effectiveness of several diffusion-based policies depending both on the external environment (i.e., the properties of the system load) and on the internal parameters. All presented policies show a robust and scalable behaviour: they are able to reach a good load balancing quality with promptness, low intrusion and little dependence on the system size. Moreover, the paper shows that the enlargement of the scope of one diffusive policy can be effective only in case of slow load dynamicity. In any other case, policies with a limited scope are to be preferred.