Best path in mountain environment based on parallel A algorithm and Apache Spark

Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or optimal path. Pathfinding problem deals with a large amount of data since it considers every point located in 2D or 3D scenes. The number of...

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Vydáno v:	The Journal of supercomputing Ročník 78; číslo 4; s. 5075 - 5094
Hlavní autoři:	Alazzam, Hadeel, AbuAlghanam, Orieb, Sharieh, Ahmad
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.03.2022 Springer Nature B.V
Témata:	Algorithms Compilers Computer Science Datasets Interpreters Mountain environments Processor Architectures Programming Languages Shortest-path problems Virtual environments Cluster Parallel A algorithm Apache Spark Pathfinding problem
ISSN:	0920-8542, 1573-0484
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Abstract	Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or optimal path. Pathfinding problem deals with a large amount of data since it considers every point located in 2D or 3D scenes. The number of possibilities in such a problem is huge. Moreover, it depends on determining standards of best path definition. In this paper, we introduce a parallel A* algorithm to find the optimal path using Apache Spark. The proposed algorithm is evaluated in terms of runtime, speedup, efficiency, and cost on a generated dataset with different sizes (small, medium, and large). The generated dataset considers real terrain challenges, such as the slope and obstacles. Hadoop Insight cluster provided by Azure has been used to run the application. The proposed algorithm reached a speedup up to 4.85 running on six worker nodes.
AbstractList	Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or optimal path. Pathfinding problem deals with a large amount of data since it considers every point located in 2D or 3D scenes. The number of possibilities in such a problem is huge. Moreover, it depends on determining standards of best path definition. In this paper, we introduce a parallel A* algorithm to find the optimal path using Apache Spark. The proposed algorithm is evaluated in terms of runtime, speedup, efficiency, and cost on a generated dataset with different sizes (small, medium, and large). The generated dataset considers real terrain challenges, such as the slope and obstacles. Hadoop Insight cluster provided by Azure has been used to run the application. The proposed algorithm reached a speedup up to 4.85 running on six worker nodes.
Author	Alazzam, Hadeel AbuAlghanam, Orieb Sharieh, Ahmad
Author_xml	– sequence: 1 givenname: Hadeel orcidid: 0000-0002-6768-9696 surname: Alazzam fullname: Alazzam, Hadeel email: hdy9160095@ju.edu.jo organization: Department of Computer Science, University of Jordan – sequence: 2 givenname: Orieb surname: AbuAlghanam fullname: AbuAlghanam, Orieb organization: Department of Networks and Information Security, Al-Ahliyya Amman University – sequence: 3 givenname: Ahmad surname: Sharieh fullname: Sharieh, Ahmad organization: Department of Information Technology, University of Jordan
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Snippet	Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or...
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SubjectTerms	Algorithms Compilers Computer Science Datasets Interpreters Mountain environments Processor Architectures Programming Languages Shortest-path problems Virtual environments
Title	Best path in mountain environment based on parallel A algorithm and Apache Spark
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