Network (tree) topology inference based on Prüfer sequence
15 Mar 2010-pp 1-5
TL;DR: A novel approach to discover network characteristics, in particular, tree topology from the hop count metric (distance) between OD (Origin — Destination) pairs is proposed, based on Prüfer encoding and decoding techniques of trees using this metric.
Abstract: Network topology discovery is the basis for any network management application. The problem of estimating internal structure and link-level performance from end-to-end measurements is known as network tomography. This paper proposes a novel approach to discover network characteristics, in particular, tree topology from the hop count metric (distance) between OD (Origin — Destination) pairs. The proposed method is based on Prufer encoding and decoding techniques of trees using this metric. The method also has the potential to minimize and avoid reliance on ICMP.
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TL;DR: The simulation results show that MWST outperforms the minimum spanning tree (MST), one of the representative spanning trees used in many routing protocols for sensor networks, in terms of energy efficiency and packet delay.
46 citations
Cites methods from "Network (tree) topology inference b..."
...Among several ways to represent the spanning tree such as Prüfer encoding (Chellappan and Krithivasan, 2010), we have chosen the predecessor encoding scheme to denote spanning trees, solutions of the problem....
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...Among several ways to represent the spanning tree such as Prüfer encoding (Chellappan and Krithivasan, 2010), we have chosen the predecessor encoding scheme to denote spanning trees, solutions of the problem....
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01 Jun 2017
TL;DR: In this article, the authors proposed a methodology for estimating radial distribution grid topologies with the use of smart meter data, where power and voltage measurements from smart meters installed in consumer point of common coupling to the distribution grid can be used for calculating the voltage sensitivity matrix.
Abstract: This paper proposes a methodology for estimating radial distribution grid topologies with the use of smart meter data. Power and voltage measurements from smart meters installed in consumer point of common coupling to the distribution grid can be used for calculating the voltage sensitivity matrix. The authors argue that this matrix can be utilized for estimating the distribution grid topology. The distribution grid sensitivity approach followed is first presented. Next the authors describe a simple method for identifying the voltage sensitivity matrix given a set of appropriate smart meter power and voltage measurements and without full knowledge of the distribution grid topology. After identifying the voltage sensitivity matrix an algorithm is presented for the estimation of the distribution grid topology. Since GIS is not yet supported for MV and especially LV networks, this methodology can enhance the optimal distribution grid planning and operation.
13 citations
Cites background or methods from "Network (tree) topology inference b..."
...The algorithm used for this purpose uses work conducted in [6] and is briefly described next....
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...The algorithm stops when there are exactly two nodes with path length 1 in ′ which concludes the “Extract Prüfer Sequence” part of the algorithm (readers may refer to [6] for a more detailed description of this process)....
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...As described in [6] leaf nodes are denoted by a set R and labeled by 1,2,3,....
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01 Jan 2013
TL;DR: A multi level group key management technique for multicast security in MANET in a hierarchical model such that cluster heads are prioritized over cluster members and the secure keys are generated using one-way function chain.
Abstract: In Mobile AdHoc Networks (MANETs), data transmission is speeded up by means of multicasting. Though multicast transmission lessens overhead, collision and congestion, it persuades new challenges towards security management. This challenge must be conquered to bring better throughput of the network. In this paper, we introduce a multi level group key management technique for multicast security in MANET. Our technique works in a hierarchical model such that cluster heads are prioritized over cluster members. The secure keys are generated using one-way function chain. In addition to secure key management, the issue of mobility is also handled. By simulation results, we prove the proficiency of our proposed technique. Our secure key management technique incurs low overhead and delay and significantly increases the throughput.
1 citations
13 Jul 2020
TL;DR: An indirect network topology estimation method called TOPFLOW (network TOPology inference from FLOW sets), which estimates the topology of the entire network from the limited number of flow sets observed at measurement nodes in the network is proposed.
Abstract: Acquisition and estimation of the topology of evolving and large-scale networks such as communication networks and social networks are not trivial because of their scale, complexity, and dynamics. In general, the topology of a communication network can be represented as a graph composed of many vertices and edges, and the estimation problem of the network topology can be handled as a topology estimation problem of the topology from limited knowledge on the graph. The network topology estimation problem covers a wide range of variations depending on the available data, constraints, and the objective function. Variants of the network topology estimation problem can be classified into two categories: direct and indirect. In the indirect network topology estimation problem, only information regarding the network topology to be estimated is known. In this paper, we propose an indirect network topology estimation method called TOPFLOW (network TOPology inference from FLOW sets), which estimates the topology of the entire network from the limited number of flow sets observed at measurement nodes in the network. Furthermore, we extensively investigate the effectiveness of TOPFLOW through a number of experiments with diverse networks with different structures and scales. Our findings include that the estimation accuracy grows almost linearly as the ratio of measurement nodes increases in some network topologies.
1 citations
Cites background from "Network (tree) topology inference b..."
...In the literature, several network tomography techniques have been proposed for estimating the routing and the traffic flows inside the network from indirect information observed from outside the communication network [1, 8, 9]....
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TL;DR: A unique encoding algorithm and a unique decoding algorithm, which when properly parameterized, can be used for all Dandelion-like codes, are designed and are optimal in the sequential setting.
1 citations
Cites background from "Network (tree) topology inference b..."
...This leads to a provably correct algorithm for this problem [36]....
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References
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Additional excerpts
...Refer [1]....
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TL;DR: In this article, the problem of estimating the node-to-node traffic intensity from repeated measurements of traffic on the links of a network is formulated and discussed under Poisson assumptions and two types of traffic-routing regimens: deterministic (a fixed known path between each directed pair of nodes) and Markovian (a random path between a pair of vertices, determined according to a known Markov chain fixed for that pair).
Abstract: The problem of estimating the node-to-node traffic intensity from repeated measurements of traffic on the links of a network is formulated and discussed under Poisson assumptions and two types of traffic-routing regimens: deterministic (a fixed known path between each directed pair of nodes) and Markovian (a random path between each directed pair of nodes, determined according to a known Markov chain fixed for that pair). Maximum likelihood estimation and related approximations are discussed, and computational difficulties are pointed out. A detailed methodology is presented for estimates based on the method of moments. The estimates are derived algorithmically, taking advantage of the fact that the first and second moment equations give rise to a linear inverse problem with positivity restrictions that can be approached by an EM algorithm, resulting in a particularly simple solution to a hard problem. A small simulation study is carried out.
801 citations
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27 Jan 2004TL;DR: This chapter discusses Spanning Trees, a system for maximizing the efficiency of the Spanning Tree Algorithm by minimizing the number of components.
Abstract: SPANNING TREES Counting Spanning Trees MINIMUM SPANNING TREES Introduction Bor Degreesuvka's Algorithm Prim's Algorithm Kruskal's Algorithm Applications Summary Bibliographic Notes and Further Reading Exercises SHORTEST-PATHS TREES Introduction Dijkstra's Algorithm The Bellman-Ford Algorithm Applications Summary Bibliographic Notes and Further Reading Exercises MINIMUM ROUTING COST SPANNING TREES Introduction Approximating by a Shortest-Paths Tree Approximating by a General Star A Reduction to the Metric Case A Polynomial Time Approximation Scheme Applications Summary Bibliographic Notes and Further Reading Exercises OPTIMAL COMMUNICATION SPANNING TREES Introduction Product-Requirement Sum-Requirement Multiple Sources Applications Summary Bibliographic Notes and Further Reading Exercises BALANCING THE TREE COSTS Introduction Light Approximate Shortest-Paths Trees Light Approximate Routing Cost Spanning Trees Applications Summary Bibliographic Notes and Further Reading Exercises STEINER TREES AND SOME OTHER PROBLEMS Steiner Minimal Trees Trees and Diameters Maximum Leaf Spanning Trees Some Other Problems Bibliographic Notes and Further Reading Exercises REFERENCES INDEX
300 citations