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A Novel Distributed Approach for Frequent Subgraphs
Mining Across Cloud Computing System (DistFsm)
M. Elshrkawey 1 , Hosam E. Refaat 1,∗ and Hanan H. Amin 2
1 Dept.
2 Dept.
of Information System, Faculty of Computers and Informatics, Suez Canal University, Egypt.
of Computer Science, Faculty of Computers and Informatics, Sohag University, Egypt.
Received: 2 Aug. 2019, Revised: 12 Oct. 2019, Accepted: 25 Oct. 2019
Published online: 1 Mar. 2020
Abstract: In this paper, a novel approach known as DistFSM presented for the FSM on a single graph. The DistFSM operation
performed on a cloud computing system that framed on a set of heterogeneous clusters. Each cluster is a set of homogenous nodes. The
input graph converted into a sparse matrix. This matrix partitioned horizontally into a sequence of non-equivalents chunks. Each chunk
size is computed to be appropriate to the available worker-resources in one of the clusters. In each cluster, the chunk is partitioned
vertically into equivalent tasks. Each task assigned to one of the worker nodes. The proposed partitioning method defined as the Hori-
Vertical partition and aims to accomplish the load balancing among the different nodes in the different clusters. Each node performs its
operation individually without any communication with other nodes. The non-equivalent chunks assigned to the different clusters allow
them to finish their operation simultaneously. This strategy increases the resource usage by prohibiting or reducing the waiting time of
the high-performance clusters. Finally, the results of all clusters are summarized and submitted to a distributed shared memory of the
orchestration node to perform the required aggregation operations.