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The paper considers the problem of parallel external sorting in the context of a form of heterogeneous clusters. We introduce two algorithms and we compare them to another one that we have previously developed. Since most common sort algorithms assume high-speed random access to all intermediate memory, they are unsuitable if the values to be sorted don't fit in main memory. This is the case for cluster computing platforms which are made of standard, cheap and scarce components. For that class of computing resources a good use of I/O operations compatible with the requirements of load balancing and computational complexity are the key to success. We explore three techniques and show how they can be deployed for clusters with processor performances related by a multiplicative factor. We validate the approaches in showing experimental results for the load balancing factor.