Asymmetry of Information within Family Networks

This paper studies asymmetry of information and transfers within 712 extended family networks from Tanzania. Using cross-reports on asset holdings, we construct measures of mis-perception of living standards among households within the same network. We contrast altruism, pressure, exchange and risk sharing as motives to transfer in simple models with asymmetric information. Testing the model predictions in the data uncovers the active role played by recipients of transfers. Our findings suggest that recipients set the terms of the transfers, either by exerting pressure on donors or because they hold substantial bargaining power in their exchange relationships

Demystifying the Performance of Data Transfers in High-Performance Research Networks

High-speed research networks are built to meet the ever-increasing needs of data-intensive distributed workflows. However, data transfers in these networks often fail to attain the promised transfer rates for several reasons, including I/O and network interference, server misconfigurations, and network anomalies. Although understanding the root causes of performance issues is critical to mitigating them and increasing the utilization of expensive network infrastructures, there is currently no available mechanism to monitor data transfers in these networks. In this paper, we present a scalable, end-to-end monitoring framework to gather and store key performance metrics for file transfers to shed light on the performance of transfers. The evaluation results show that the proposed framework can monitor up to 400 transfers per host and more than 40, 000 transfers in total while collecting performance statistics at one-second precision. We also introduce a heuristic method to automatically process the gathered performance metrics and identify the root causes of performance anomalies with an F-score of 87 - 98%.Comment: 11 pages, 7 figures, 6 table

Energy-efficient bandwidth reservation for bulk data transfers in dedicated wired networks

International audienceThe ever increasing number of Internet connected end-hosts call for high performance end-to-end networks leading to an increase in the energy consumed by the networks. Our work deals with the energy consumption issue in dedicated network with bandwidth provisionning and in-advance reservations of network equipments and bandwidth for Bulk Data transfers. First, we propose an end-to-end energy cost model of such networks which described the energy consumed by a transfer for all the crossed equipments. This model is then used to develop a new energy-aware framework adapted to Bulk Data Transfers over dedicated networks. This framework enables switching off unused network portions during certain periods of time to save energy. This framework is also endowed with prediction algorithms to avoid useless switching off and with adaptive scheduling management to optimize the energy used by the transfers. 1 Introductio

On the flow-level stability of data networks without congestion control: the case of linear networks and upstream trees

In this paper, flow models of networks without congestion control are considered. Users generate data transfers according to some Poisson processes and transmit corresponding packet at a fixed rate equal to their access rate until the entire document is received at the destination; some erasure codes are used to make the transmission robust to packet losses. We study the stability of the stochastic process representing the number of active flows in two particular cases: linear networks and upstream trees. For the case of linear networks, we notably use fluid limits and an interesting phenomenon of "time scale separation" occurs. Bounds on the stability region of linear networks are given. For the case of upstream trees, underlying monotonic properties are used. Finally, the asymptotic stability of those processes is analyzed when the access rate of the users decreases to 0. An appropriate scaling is introduced and used to prove that the stability region of those networks is asymptotically maximized

Phylogenetic Networks Do not Need to Be Complex: Using Fewer Reticulations to Represent Conflicting Clusters

Phylogenetic trees are widely used to display estimates of how groups of species evolved. Each phylogenetic tree can be seen as a collection of clusters, subgroups of the species that evolved from a common ancestor. When phylogenetic trees are obtained for several data sets (e.g. for different genes), then their clusters are often contradicting. Consequently, the set of all clusters of such a data set cannot be combined into a single phylogenetic tree. Phylogenetic networks are a generalization of phylogenetic trees that can be used to display more complex evolutionary histories, including reticulate events such as hybridizations, recombinations and horizontal gene transfers. Here we present the new CASS algorithm that can combine any set of clusters into a phylogenetic network. We show that the networks constructed by CASS are usually simpler than networks constructed by other available methods. Moreover, we show that CASS is guaranteed to produce a network with at most two reticulations per biconnected component, whenever such a network exists. We have implemented CASS and integrated it in the freely available Dendroscope software