Modified hypercubes (MHs) have been proposed as building blocks for hypercube-based parallel systems that support the application of incremental growth techniques. In contrast, implementing the standard hypercube cannot be expanded in practice. However, processor allocation for MHs is a more difficult task due to a slight deviation in their topology from that of the standard hypercube. The paper proposes two strategies to solve the processor allocation problem for MHs. The proposed strategies are characterised by perfect subcube recognition ability and superior performance. Furthermore, two existing processor allocation strategies for standard hypercube networks, namely the buddy and free-list strategies, are shown to be ineffective for MHs, in the light of their inability to recognise many available subcubes. A comparative analysis that involves the buddy strategy and the new strategies is carried out using simulation results.