Managing the performance of distributed and parallel computing systems is a challenge, because of their inherent complexity and the diversity of new applications. LYDIA proposes to contribute to the effort of adaptive resource management and load balancing of complex parallel and distributed systems by:

enhancing the understanding of the basic issues in load balancing of parallel and distributed systems: trade-off between balancing the processor load versus locality of reference, the need for load-balancing at various abstraction levels of a parallel system; the necessity to take into account both long-term (eg data access patterns) and short-term (eg bursts of random unit of work arrivals) workload characteristics.

devising, analysing, experimenting and evaluating a wide range of load balancing algorithms that draw on expertise from various fields: parallel and distributed systems design expertise, adaptive/stochastic control, decision theory, neural networks, scheduling theory and performance analysis.
designing and demonstrating the use of an Interface Definition Language (IDL) to model hardware and software interfaces that provide the necessary environment information for load balancing decisions.

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