A fast distributed shortest path algorithm for a class of hierarchically clustered data networks

Antonio, John K.; Huang, G.; Tsai, W.K.

doi:10.1109/12.144623

Cited by 52 publications

(19 citation statements)

References 14 publications

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“…The algorithm by Kanchi and Vineyard [29] is fast (runs in O(n) time) but involves using large messages, hence does not apply in the CONGEST model. The algorithm of Antonio et al [2] uses short (i.e., O(log n) bits) messages, hence it can be executed in the CONGEST model, but it requires O(n log n) time, and moreover, it applies only to the special family of BHC graphs, which are graphs structured as a balanced hierarchy of clusters. Most of the distributed algorithms for the APSP problem aim at minimizing the message complexity, rather than the time; for instance, the algorithm of Haldar [23] requires O(n 2 ) time.…”

Section: Distributed Algorithms For Exact All-pairs Shortest-pathsmentioning

confidence: 99%

“…The exact all-pairs shortest path (APSP) problem has been studied extensively in the sequential setting, and was also given several solutions in the distributed setting [2,13,23,29,51]. The algorithm by Kanchi and Vineyard [29] is fast (runs in O(n) time) but involves using large messages, hence does not apply in the CONGEST model.…”

Section: Distributed Algorithms For Exact All-pairs Shortest-pathsmentioning

confidence: 99%

“…Letting S be a random sample of nodes of that size, long paths are broken down into subpaths ofÕ( √ n) hops between skeleton nodes with high probability. 2 Having information about the distances of skeleton nodes hence usually implies that we can keep h ∈Õ( √ n) when applying source detection. A skeleton spanner can be used to concisely represent the global distance structure of the graph and make it available to all nodes in a number of rounds comparable to the lower bound ofΩ( √ n + D).…”

Section: Skeleton Spannersmentioning

confidence: 99%

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Distributed distance computation and routing with small messages

2018

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We consider shortest paths computation and related tasks from the viewpoint of network algorithms, where the n-node input graph is also the computational system: nodes represent processors and edges represent communication links, which can in each time step carry an O(log n)-bit message. We identify several basic distributed distance computation tasks that are highly useful in the design of more sophisticated algorithms and provide efficient solutions. We showcase the utility of these tools by means of several applications.

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Section: Distributed Algorithms For Exact All-pairs Shortest-pathsmentioning

confidence: 99%

Section: Distributed Algorithms For Exact All-pairs Shortest-pathsmentioning

confidence: 99%

Section: Skeleton Spannersmentioning

confidence: 99%

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Distributed distance computation and routing with small messages

2018

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“…The all-pairs shortest path (APSP) problem has been studied extensively in the sequential setting, and was also given several solutions in the distributed setting [3,8,14,16,23]. The algorithm of [16] is fast (O(n) time) but involves using large messages, hence does not apply in the CONGEST model.…”

Section: Related Workmentioning

confidence: 99%

“…The algorithm of [16] is fast (O(n) time) but involves using large messages, hence does not apply in the CONGEST model. The algorithm of [3] uses short (O(log n) bits) messages, hence it can be executed in the CONGEST model, but it requires time O(n log n), and moreover, it applies only to the special family of BHC graphs, which are graphs structured as a balanced hierarchy of clusters. Most of the distributed algorithms for the APSP problem aim at minimizing the message complexity, rather than the time.…”

Section: Related Workmentioning

confidence: 99%

Efficient distributed source detection with limited bandwidth

Lenzen

Peleg

2013

Proceedings of the 2013 ACM Symposium on Principles of Distributed Computing

140

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Given a simple graph G = (V, E) and a set of sources S ⊆ V , denote for each node v ∈ V by L (∞) v the lexicographically ordered list of distance/source pairs (d(s, v), s), where s ∈ S. For integers d, k ∈ N∪{∞}, we consider the source detection,Solutions to this problem provide natural generalizations of concurrent breadth-first search (BFS) tree constructions. For example, the special case of k = ∞ requires each source s ∈ S to build a complete BFS tree rooted at s, whereas the special case of d = ∞ and S = V requires constructing a partial BFS tree comprising at least k nodes from every node in V .In this work, we give a simple, near-optimal solution for the source detection task in the CONGEST model, where messages contain at most O(log n) bits, running in d + k rounds. We demonstrate its utility for various routing problems, exact and approximate diameter computation, and spanner construction. For those problems, we obtain algorithms in the CONGEST model that are faster and in some cases much simpler than previous solutions.

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Domain clustering for inter‐domain path computation speed‐up

et al. 2017

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We consider a multi‐domain network scenario and we study the Inter‐Domain Path Computation problem under the Domain Uniqueness constraint (IDPC‐DU), that is, a path cannot visit a domain twice. It is known that hierarchical Path Computation Element (h‐PCE) architecture, that is commonly used to solve IDPC‐DU, shows poor scalability with respect to the number of domains. For this reason, we devise a new domain clustering concept allowing one to artificially reduce the number of domains in an offline phase, in order to solve IDPC‐DU with lower complexity at run‐time. More specifically, we first prove the NP‐completeness of the feasibility problem associated with IDPC‐DU and the inapproximability of IDPC‐DU itself. Yet, we show that the number of domains is the real computational bottleneck for the solution of IDPC‐DU. Then we provide a necessary and sufficient condition for a domain clustering to be proper, that is, without loss of optimality. Such a condition can be verified offline on the inter‐domain graph. We finally show via numerical experiments the impact of the inter‐domain treewidth on the computational speed‐up brought by proper clustering.

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A fast distributed shortest path algorithm for a class of hierarchically clustered data networks

Cited by 52 publications

References 14 publications

Distributed distance computation and routing with small messages

Distributed distance computation and routing with small messages

Efficient distributed source detection with limited bandwidth

Domain clustering for inter‐domain path computation speed‐up

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