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Alice Chen - One of the best experts on this subject based on the ideXlab platform.
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Link Weight assignment and loop free routing table update for Link state routing protocols in energy aware internet
Future Generation Computer Systems, 2012Co-Authors: Po-kai Tseng, Alice ChenAbstract:In order to lessen the greenhouse effects and diminish environmental pollution, reducing energy usage is important in designing next generation networks. Shutting down the network devices that carry light load and redirecting their traffic flows to other routes is the most common way to reduce network energy consumption. Since traffic demands among node pairs vary in different time periods, an energy efficient network has to dynamically determine the optimal active Links to adapt itself to network traffic changes. However, in current IP networks, shutting down and/or turning on Links would trigger Link state routing protocols to reconverge to a new topology. Since the convergence time would take tens of seconds, routing table inconsistencies among routers would result in network disconnection and even worse, generating traffic loops during the convergence interval. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not considered in the green network design yet. The contribution of the paper is presented in two parts. First, we propose a comprehensive approach to determine a network topology and a Link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy-aware network are within a predetermined percentage of the Link capacity such that no congestion occurs in a statistical manner. Second, to avoid transient loops during time period changes, we propose a Distributed Loop-free Routing Update (DLRU) scheme to determine the correct sequence for updating the routing table. A scrupulous proof was also presented to ensure the loop-free property of the DLRU. In this paper, we formulate an integer linear programming to determine this multi-topology and Link Weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangian Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LRHS approach outperforms the other approaches on several benchmark networks and random networks by providing up to 35%-50% additional energy saving in our experimental cases.
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Multi-Topology design and Link Weight assignment for green IP networks
2011 IEEE Symposium on Computers and Communications (ISCC), 2011Co-Authors: Po-kai Tseng, Alice ChenAbstract:In order to reduce the greenhouse effects and environmental pollution, energy saving has become important in designing next the generation networks. Shutting down the network devices carrying light loads and redirecting the traffic flows to other routes is a way to decrease network energy consumption. Since traffic demands among node pairs vary in different time periods, the energy efficient network design is to determine the optimal network topologies for them. However, in current IP network, flows are governed by shortest path routing, thus purely determining the network topology is not enough. A set of Link Weight metric has to be derived in company with the network topology such that the flows on the active Links can meet the physical capacity constraints. Although applying adaptive network topology could save energy consumption, however, the lack of stringent synchronization among routers would cause undesired loops during the transient period of topology changes. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not yet considered in the green network design. In this paper, we propose a comprehensive approach that determines network topology and Link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy aware network are within a predetermined percentage of the Link capacity such that no congestion occurs in a statistical manner. To avoid accurate synchronization among routers, we propose using RFC 4915 Multi-Topology Routing, to resolve the transient loop problem. By controlling the update sequence in MTR, there is no transient loop during the period of topology changes. We formulate an integer linear programming to jointly determine this multi-topology and Link Weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangean Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LR&HS approach outperforms the other approaches on four benchmark networks and provides up to 35%-50% energy saving in our experimental cases.
Piet Van Mieghem - One of the best experts on this subject based on the ideXlab platform.
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betweenness centrality in a Weighted network
Physical Review E, 2008Co-Authors: Huijuan Wang, Javier Martin Hernandez, Piet Van MieghemAbstract:When transport in networks follows the shortest paths, the union of all shortest path trees G union or logical sum SPT can be regarded as the "transport overlay network." Overlay networks such as peer-to-peer networks or virtual private networks can be considered as a subgraph of G union or logical sum SPT. The traffic through the network is examined by the betweenness Bl of Links in the overlay G union or logical sum SPT. The strength of disorder can be controlled by, e.g., tuning the extreme value index alpha of the independent and identically distributed polynomial Link Weights. In the strong disorder limit (alpha-->0), all transport flows over a critical backbone, the minimum spanning tree (MST). We investigate the betweenness distributions of wide classes of trees, such as the MST of those well-known network models and of various real-world complex networks. All these trees with different degree distributions (e.g., uniform, exponential, or power law) are found to possess a power law betweenness distribution Pr[Bl=j] approximately j(-c). The exponent c seems to be positively correlated with the degree variance of the tree and to be insensitive of the size N of a network. In the weak disorder regime, transport in the network traverses many Links. We show that a Link with smaller Link Weight tends to carry more traffic. This negative correlation between Link Weight and betweenness depends on alpha and the structure of the underlying topology.
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phase transition in the Link Weight structure of networks
Physical Review E, 2005Co-Authors: Piet Van Mieghem, Serena M MagdalenaAbstract:When transport in networks follows the shortest paths, the Link Weights are shown to play a crucial role. If the underlying topology with $N$ nodes is not changed and if the Link Weights are independent from each other, then we show that, by tuning the Link Weights, a phase transition occurs around a critical extreme value index ${\ensuremath{\alpha}}_{c}$ of the Link Weight distribution. If the extreme value index of the Link Weight distribution $\ensuremath{\alpha}g{\ensuremath{\alpha}}_{c}$, transport in the network traverses many Links whereas for $\ensuremath{\alpha}l{\ensuremath{\alpha}}_{c}$, all transport flows over a critical backbone consisting of $N\ensuremath{-}1$ Links. For connected Erd\"os-R\'enyi random graphs ${G}_{p}(N)$ and square lattices, we have characterised the phase transition and found that ${\ensuremath{\alpha}}_{c}\ensuremath{\simeq}b{N}^{\ensuremath{-}\ensuremath{\beta}}$ with ${\ensuremath{\beta}}_{{G}_{p}(N)}\ensuremath{\approx}0.63$ and ${\ensuremath{\beta}}_{\text{lattice}}\ensuremath{\approx}0.62$.
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influence of the Link Weight structure on the shortest path
Physical Review E, 2005Co-Authors: Piet Van Mieghem, Stijn Van LangenAbstract:The shortest path tree rooted at a source to all other nodes is investigated in a graph with polynomial Link Weights tunable by the power exponent alpha. By varying alpha, different types of shortest path trees, in short alpha trees, appear. Especially, the alpha --> 0 regime that corresponds to heavily fluctuating Link Weights possesses a peculiar type of tree. The most important properties of this alpha --> 0 tree are derived in the asymptotic limit for large N. The application of the theoretical insights to real networks (such as the Internet) are discussed: steering flow by adjusting Link Weights (traffic engineering), sensitivity of Link Weights and modeling of the network by alpha trees.
Tai Kubo - One of the best experts on this subject based on the ideXlab platform.
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biogeographical network analysis of cretaceous terrestrial tetrapods a phylogeny based approach
Systematic Biology, 2019Co-Authors: Tai KuboAbstract:Network methods are widely used to represent and analyze biogeography. It is difficult, however, to convert occurrence data of fossil vertebrates to a biogeographical network, as most species were known from a single locality. A new method for creating a biogeographical network that can incorporate phylogenetic information is proposed in this study, which increases the number of edges in the network of fossil vertebrates and enables the application of various network methods. Using ancestral state reconstruction via maximum parsimony, the method first estimates the biogeographical regions of all internal nodes of a given phylogeny using biogeographical information on the terminal taxa. Then, each internal node in the phylogenetic tree is converted to an edge in the biogeographical network that connects the region(s), if unambiguously estimated, of its two descendants. The new method was applied to phylogenetic trees generated by a birth-death model. Under all conditions tested, an average of $CDATA[$CDATA[$>$$70% of the internal nodes in phylogenetic trees were converted into edges. Three network indices-Link density, average Link Weight, and endemism index (EI)-were evaluated for their usefulness in comparing different biogeographical networks. The EI reflects the rate of dispersal; the other indices reflect nonbiogeographical parameters, the number of taxa and regions, which highlights the importance of evaluating network indices before applying them to biogeographical studies. Multiple Cretaceous biogeographical networks were constructed from the phylogenies of five tetrapod taxa: terrestrial crocodyliforms, terrestrial turtles, nonavian dinosaurs, avians, and pterosaurs. The networks of avians and pterosaurs showed similar topologies and a strong correlation, and unexpectedly high endemism indices. These similarities were probably a result of shared taphonomic biases (i.e., the Lagerstatten effect) for volant taxa with fragile skeletons. The crocodyliform network was partitioned into the Gondwanan and Laurasian continents. The dinosaur network was partitioned into three groups of continents: 1) North America, Asia, and Australia; 2) Europe and Africa; and 3) India, Madagascar, and South America. When Early and Late Cretaceous dinosaurs were analyzed separately, the dinosaur networks were divided into 1) North America, Asia, and Australia; and 2) Europe, Africa, India, and South America for the Early Cretaceous and 1) North America, Asia, and Europe; and 2) India, Madagascar, and South America for the Late Cretaceous. This partitioning of dinosaur and crocodyliform networks corroborates the results of previous biogeographical studies and indicates that the method introduced here can retrieve biogeographical signals from a source phylogeny when sufficient data are available for most targeted biogeographical regions.
Po-kai Tseng - One of the best experts on this subject based on the ideXlab platform.
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near optimal Link on off scheduling and Weight assignment for minimizing ip network energy consumption
Computer Communications, 2012Co-Authors: Po-kai Tseng, Weiho ChungAbstract:The rationale behind a green network is that it should effectively reduce energy consumption, while maintaining the level of services for data communications. In this paper, we propose an efficient approach, called the Compression Algorithm (CA), which is designed to solve the Link on/off and Weight assignment problems jointly so as to minimize a network's energy consumption. The problem is formulated as a mixed integer non-linear optimization problem. Because the problem is NP-hard, the CA utilizes a genetic algorithm to determine the Link on/off schedule. In addition, it exploits the simulated annealing technique for Link Weight assignment so that the routing paths satisfy the Link capacity constraints. By solving the Link on/off and Weight assignment problems sequentially, the CA scheme reduces the uncertainty about network energy consumption and yields a near optimal solution. To observe the relationship between network energy consumption and Link load distributions, performance evaluations were conducted on three schemes, namely, the proposed CA, route construction without considering power savings, and route construction using minimum power saving without Link capacity constraints. Numerical results demonstrate that the CA outperforms the other approaches on a network embedded with both uniform and non-uniform demand distributions.
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Link Weight assignment and loop free routing table update for Link state routing protocols in energy aware internet
Future Generation Computer Systems, 2012Co-Authors: Po-kai Tseng, Alice ChenAbstract:In order to lessen the greenhouse effects and diminish environmental pollution, reducing energy usage is important in designing next generation networks. Shutting down the network devices that carry light load and redirecting their traffic flows to other routes is the most common way to reduce network energy consumption. Since traffic demands among node pairs vary in different time periods, an energy efficient network has to dynamically determine the optimal active Links to adapt itself to network traffic changes. However, in current IP networks, shutting down and/or turning on Links would trigger Link state routing protocols to reconverge to a new topology. Since the convergence time would take tens of seconds, routing table inconsistencies among routers would result in network disconnection and even worse, generating traffic loops during the convergence interval. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not considered in the green network design yet. The contribution of the paper is presented in two parts. First, we propose a comprehensive approach to determine a network topology and a Link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy-aware network are within a predetermined percentage of the Link capacity such that no congestion occurs in a statistical manner. Second, to avoid transient loops during time period changes, we propose a Distributed Loop-free Routing Update (DLRU) scheme to determine the correct sequence for updating the routing table. A scrupulous proof was also presented to ensure the loop-free property of the DLRU. In this paper, we formulate an integer linear programming to determine this multi-topology and Link Weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangian Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LRHS approach outperforms the other approaches on several benchmark networks and random networks by providing up to 35%-50% additional energy saving in our experimental cases.
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Multi-Topology design and Link Weight assignment for green IP networks
2011 IEEE Symposium on Computers and Communications (ISCC), 2011Co-Authors: Po-kai Tseng, Alice ChenAbstract:In order to reduce the greenhouse effects and environmental pollution, energy saving has become important in designing next the generation networks. Shutting down the network devices carrying light loads and redirecting the traffic flows to other routes is a way to decrease network energy consumption. Since traffic demands among node pairs vary in different time periods, the energy efficient network design is to determine the optimal network topologies for them. However, in current IP network, flows are governed by shortest path routing, thus purely determining the network topology is not enough. A set of Link Weight metric has to be derived in company with the network topology such that the flows on the active Links can meet the physical capacity constraints. Although applying adaptive network topology could save energy consumption, however, the lack of stringent synchronization among routers would cause undesired loops during the transient period of topology changes. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not yet considered in the green network design. In this paper, we propose a comprehensive approach that determines network topology and Link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy aware network are within a predetermined percentage of the Link capacity such that no congestion occurs in a statistical manner. To avoid accurate synchronization among routers, we propose using RFC 4915 Multi-Topology Routing, to resolve the transient loop problem. By controlling the update sequence in MTR, there is no transient loop during the period of topology changes. We formulate an integer linear programming to jointly determine this multi-topology and Link Weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangean Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LR&HS approach outperforms the other approaches on four benchmark networks and provides up to 35%-50% energy saving in our experimental cases.
Jose M F Moura - One of the best experts on this subject based on the ideXlab platform.
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distributed consensus algorithms in sensor networks quantized data and random Link failures
IEEE Transactions on Signal Processing, 2010Co-Authors: Soummya Kar, Jose M F MouraAbstract:The paper studies the problem of distributed average consensus in sensor networks with quantized data and random Link failures. To achieve consensus, dither (small noise) is added to the sensor states before quantization. When the quantizer range is unbounded (countable number of quantizer levels), stochastic approximation shows that consensus is asymptotically achieved with probability one and in mean square to a finite random variable. We show that the mean-squared error (mse) can be made arbitrarily small by tuning the Link Weight sequence, at a cost of the convergence rate of the algorithm. To study dithered consensus with random Links when the range of the quantizer is bounded, we establish uniform boundedness of the sample paths of the unbounded quantizer. This requires characterization of the statistical properties of the supremum taken over the sample paths of the state of the quantizer. This is accomplished by splitting the state vector of the quantizer in two components: one along the consensus subspace and the other along the subspace orthogonal to the consensus subspace. The proofs use maximal inequalities for submartingale and supermartingale sequences. From these, we derive probability bounds on the excursions of the two subsequences, from which probability bounds on the excursions of the quantizer state vector follow. The paper shows how to use these probability bounds to design the quantizer parameters and to explore tradeoffs among the number of quantizer levels, the size of the quantization steps, the desired probability of saturation, and the desired level of accuracy ? away from consensus. Finally, the paper illustrates the quantizer design with a numerical study.
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distributed consensus algorithms in sensor networks quantized data and random Link failures
arXiv: Multiagent Systems, 2007Co-Authors: Soummya Kar, Jose M F MouraAbstract:The paper studies the problem of distributed average consensus in sensor networks with quantized data and random Link failures. To achieve consensus, dither (small noise) is added to the sensor states before quantization. When the quantizer range is unbounded (countable number of quantizer levels), stochastic approximation shows that consensus is asymptotically achieved with probability one and in mean square to a finite random variable. We show that the meansquared error (m.s.e.) can be made arbitrarily small by tuning the Link Weight sequence, at a cost of the convergence rate of the algorithm. To study dithered consensus with random Links when the range of the quantizer is bounded, we establish uniform boundedness of the sample paths of the unbounded quantizer. This requires characterization of the statistical properties of the supremum taken over the sample paths of the state of the quantizer. This is accomplished by splitting the state vector of the quantizer in two components: one along the consensus subspace and the other along the subspace orthogonal to the consensus subspace. The proofs use maximal inequalities for submartingale and supermartingale sequences. From these, we derive probability bounds on the excursions of the two subsequences, from which probability bounds on the excursions of the quantizer state vector follow. The paper shows how to use these probability bounds to design the quantizer parameters and to explore tradeoffs among the number of quantizer levels, the size of the quantization steps, the desired probability of saturation, and the desired level of accuracy $\epsilon$ away from consensus. Finally, the paper illustrates the quantizer design with a numerical study.