SERIAL AND PARALLEL IMPLEMENTATION OF SHORTEST PATH ALGORITHM IN THE OPTIMIZATION OF PUBLIC TRANSPORT TRAVEL Serial and Parallel Implementation of Shortest Path Algorithm in the Optimization of Public Transport Travel 73 (original) (raw)
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International Journal of Engineering Research and Technology (IJERT), 2013
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Parallel Computing, 2001
Shortest path algorithms are required by several transportation applications; furthermore, the shortest path computation in these applications can account for a large percentage of the total execution time. Since these algorithms are very computationally intense, parallel processing can provide the compute power and memory required to solve large problems quickly. Therefore, good parallel shortest algorithms are critical for ecient parallel implementations of transportation applications. The experimental work related to parallel shortest path algorithms has focused on the development of parallel algorithms; however, very little work has been done with analyzing and understanding the performance impact of various implementation issues. In this paper, we conduct a thorough experimental analysis of parallel shortest path algorithms for sparse networks, concentrating on three implementation issues: (1) choice of shortest path algorithm, (2) termination detection and (3) network decomposition. The paper focuses on the choice of shortest path algorithm and network decomposition since the work on termination detection was published previously. We determine that all three issues aect the communication and convergence of the shortest path algorithm. Furthermore, we ®nd that communicating the most information at a time results in the best convergence; this is contrary to most scienti®c applications where it is optimal to minimize communication. Ó 2001 Published by Elsevier Science B.V. (M.R. Hribar), taylor@ece.nwu.edu (V.E. Taylor), DBoyce @uic.edu (D.E. Boyce). 0167-8191/01/$ -see front matter Ó 2001 Published by Elsevier Science B.V. PII: S 0 1 6 7 -8 1 9 1 ( 0 1 ) 0 0 1 0 5 -3
Performance Study of a Parallel Shortest Path Algorithm
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Single source shortest path (SSSP) calculation is a common prerequisite in many real world applications such as traveler information systems, network routing table creation etc., where basic data are depicted as a graph. To fulfill the requirements of such applications, SSSP calculation algorithms should process their data very quickly but these data are actually very large in size. Parallel implementation of the SSSP algorithm could be one of the best ways to process large data sets in real time. This paper proposes two different ways of parallel implementation of SSSP calculation on a CPU-GPU (Graphics Processing Unit)-based hybrid machine and demonstrates the impact of the highly parallel computing capabilities of today’s GPUs. We present parallel implementations of a modified version of Dijkstra’s famous algorithm of SSSP calculation, which can settle more than one node at any iteration. This paper presents a comparative analysis between both implementations. We evaluate the results of our parallel implementations for two Nvidia GPUs; the Tasla C2074 and the GeForce GTS 450. We compute the SSSP on graph having 5.1 million edges in 191 milliseconds. Our modified parallel implementation shows the three-fold improvement on the parallel implementation of simple Dijkstra’s algorithm. https://sites.google.com/site/ijcsis/
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In road networks, it is imperative to discover a shortest way to reach the final destination. When an individual is new to a place, lots of time is wasted in finding the destination. With the advancement of technology, various navigation applications have been developed for guiding private vehicles, but few are designed for public transportation. This study is solely concentrated on finding the possible shortest path in terms of minimum time and cost to reach specific destination for an individual. It requires an appropriate algorithm to search the shortest path. With the implementation of Dijkstra’s algorithm, the shortest path with respect to minimum travel time and travel cost was computed. Public transportation network of Pokhara city was taken for the case study of this research. The results of this analysis indicated that when the “time” impedance was used by the algorithm, it generated the shortest path between the origin and destination along with the path to be followed. Th...
Performance of Dijkstra, Floyd and Astar Algorithms for Urban Transport Lines
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The study of the existing street network built without a layout is very difficult problem (almost insoluble problem). A detailed study needs to be solved a similar problem. It also needs traffic statistics, and various surveys for traffic participants. To make sure the necessary records for an efficient analysis needs a lot of work and a long time to complete. After collecting the necessary data, then through various software such as GIS software, Traffic analysis etc. we can improve the level of services by adding or eliminating any of the problematic routes. The optimization of urban transport lines is a very important problem in bus network planning. Many researchers have been dealing with these phenomena over the years, but there has never been a general pattern applicable to any urban situation as each city is a case in itself and requires more specific approach. In this paper we present the performance of different algorithms for finding shortest route on a network.