DocumentCode
2990564
Title
MapReduce algorithm for finding st-connectivity
Author
Feher, Peter ; Vajk, Tamas ; Charaf, Hassan ; Lengyel, Laszlo
Author_Institution
Dept. of Autom. & Appl. Inf., Budapest Univ. of Technol. & Econ., Budapest, Hungary
fYear
2013
fDate
2-5 Dec. 2013
Firstpage
759
Lastpage
764
Abstract
In recent years the MapReduce framework has become one of the most popular parallel computing platform for processing big data. It is frequently used by companies such as Facebook, IBM, and Google. Moreover, more and more universities adopt this approach for their academic purposes. Since the MapReduce computing framework is designed for distributed computing on massive data sets, with the help of new algorithms, it can be a suitable platform for processing graphs with billions of vertices and edges. The st-connectivity, that is, the existence of at least one path between any two vertices s and t, is a fundamental graph theory problem. This paper introduces a new algorithm, which is capable of finding st-connectivity in arbitrary graphs, designed for the MapReduce framework. The paper also defines the data structure, which might be suitable in case of other graph processing algorithms.
Keywords
data structures; graph theory; parallel processing; social networking (online); Facebook; Google; IBM; MapReduce algorithm; MapReduce computing framework; arbitrary graphs; big data processing; data structure; distributed computing; graph processing algorithms; graph theory problem; massive data sets; parallel computing platform; st-connectivity; Algorithm design and analysis; Clustering algorithms; Conferences; Data structures; Distributed databases; Educational institutions; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Infocommunications (CogInfoCom), 2013 IEEE 4th International Conference on
Conference_Location
Budapest
Print_ISBN
978-1-4799-1543-9
Type
conf
DOI
10.1109/CogInfoCom.2013.6719201
Filename
6719201
Link To Document