An allocation of resources to a virtual machine specifies the maximum amount of each individual element of each resource type that will be utilized, as well as the aggregate amount of each resource of each type. In this paper, we present an new approach to improve the deadlock detection algorithm, to schedule the policies of resource supply for allocating multiple resources to competing services running in virtual machines on a heterogeneous distributed platform. We introduce the matrix representation of a deadlock detection problem and some essential features can be mapped into a cloud architecture which can handle multiple requests/grants simultaneously and can detect multiple deadlocks in linear time, hence, significantly improving performance. Our algorithm proposed has a run time complexity of O(min(m,n)), where m is the number of resources and n is the number of processes. The experiments also compare the performance of our algorithm proposed approach with other related works.