Modified hypercubes (MHs) have been proposed by Ziavras as the building blocks of hypercube-based parallel systems that support incremental growth techniques. In contrast, systems comprising the standard hypercube network can not be expanded in practice. However, processor allocation on MHs is a more difficult task due to a slight deviation in their topology from that of the standard hypercube network. This paper addresses the processor allocation problem for MHs and proposes two strategies that are based, partially or entirely, on a table look-up approach. The proposed strategies are characterized by a perfect subcube recognition ability and a superior performance. Further, two existing processor allocation strategies for pure hypercube networks, namely the buddy and free list strategies, are shown to be ineffective for MHs, in the light of their inability to recognize many available subcubes.
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