Performance Comparison of Algorithms for the Dynamic Shortest Path Problem

Taoka, Satoshi; Takafuji, Daisuke; Iguchi, Takashi; Watanabe, Takahiro

doi:10.1093/ietfec/e90-a.4.847

Cited by 12 publications

(6 citation statements)

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“…The generator does not seem to be available any more. In [14] the algorithms SWSF-FP, RR, FMN, NARVÁEZ and full recomputation from scratch using DIJKSTRA, BELL-MAN FORD, D'ESOPO PAPE are evaluated with single-edge updates on Erdös-Rényi-like graphs. In [3] one algorithm of the NARVÁEZ-framework is evaluated on random single-edge updates on a graph representing the road-network of Western Europe.…”

Section: Introductionmentioning

confidence: 99%

Batch Dynamic Single-Source Shortest-Path Algorithms: An Experimental Study

Bauer

Wagner

2009

Experimental Algorithms

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Abstract. A dynamic shortest-path algorithm is called a batch algorithm if it is able to handle graph changes that consist of multiple edge updates at a time. In this paper we focus on fully-dynamic batch algorithms for singlesource shortest paths in directed graphs with positive edge weights. We give an extensive experimental study of the existing algorithms for the single-edge and the batch case, including a broad set of test instances. We further present tuned variants of the already existing SWSF-FP-algorithm being up to 15 times faster than SWSF-FP. A surprising outcome of the paper is the astonishing level of data dependency of the algorithms.

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Section: Introductionmentioning

confidence: 99%

Batch Dynamic Single-Source Shortest-Path Algorithms: An Experimental Study

Bauer

Wagner

2009

Experimental Algorithms

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“…The batch problem was considered in [7][8][9]. Comprehensive experiments on the comparison of different batch algorithms can be found in [9,10].…”

Section: A Shortest Path Problem In Graphsmentioning

confidence: 99%

Dynamic Shortest Path Algorithms for Hypergraphs

Gao

Zhao

Ren

et al. 2015

IEEE/ACM Trans. Networking

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Abstract-A hypergraph is a set V of vertices and a set of non-empty subsets of V , called hyperedges. Unlike graphs, hypergraphs can capture higher-order interactions in social and communication networks that go beyond a simple union of pairwise relationships. In this paper, we consider the shortest path problem in hypergraphs. We develop two algorithms for finding and maintaining the shortest hyperpaths in a dynamic network with both weight and topological changes. These two algorithms are the first addressing the fully dynamic shortest path problem in a general hypergraph. They complement each other by partitioning the application space based on the nature of the change dynamics and the type of the hypergraph. We analyze the time complexity of the proposed algorithms and perform simulation experiments for both random geometric hypergraphs and the Enron email data set. The latter illustrates the application of the proposed algorithms in social networks for identifying the most important actor based on the closeness centrality metric.

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“…[5] compares 26 different algorithms for solving the shortest path problem. That survey concludes that DSP algorithms perform much faster then repeating static ones (such as Dijkstra).…”

Section: Related Workmentioning

confidence: 99%

“…[6] is a similar comparison of dynamic shortest path algorithms, based on experimentation. [5] suggests that the algorithm that proves to be the fastest in the survey is [7] when using the same data structures as in Bellman-Ford. [7] -henceforth called NST+ by using the first letters of the three authors -is an incremental shortest path algorithm.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Using a Dynamic Shortest Path Algorithm in OLSRv2

Herberg

2010

2010 8th Annual Communication Networks and Services Research Conference

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MANET routing protocols are designed to scale up to thousands of routers with frequent changes of the topology. In preference, MANET routing protocols should also support constrained low-power devices. One of the bottlenecks of scalability in link-state routing protocols is the performance of the shortest path algorithm (e.g. Dijkstra). In this paper, we investigate the in-node performance of OLSRv2 and, in particular, study the benefits of using a dynamic shortest path (DSP) algorithm for this routing protocol. A DSP algorithm is an algorithm that adds or removes edges in the routing tree incrementally and calculates shortest paths, also incrementally. The performance in OLSRv2 with classic Dijkstra vs. DSP is evaluated, by comparing the CPU time for calculating paths in a large emulated network. Additionally, it is demonstrated that frequent topology changes due to mobility in MANETs lead to frequent routing table recalculations with only few routes updated each time. This property of MANETs makes the use of a DSP in OLSRv2 appropriate.

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Performance Comparison of Algorithms for the Dynamic Shortest Path Problem

Cited by 12 publications

References 0 publications

Batch Dynamic Single-Source Shortest-Path Algorithms: An Experimental Study

Batch Dynamic Single-Source Shortest-Path Algorithms: An Experimental Study

Dynamic Shortest Path Algorithms for Hypergraphs

Performance Evaluation of Using a Dynamic Shortest Path Algorithm in OLSRv2

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