A Pragmatic Definition of Elephants in Internet Backbone Traffic

Studies of the Internet traffic at the level of network prefixes, fixed length prefixes, TCP flows, AS’s, and WWW traffic, have all shown that a very small percentage of the flows carries the largest part of the information. This behavior is commonly referred to as “the elephants and mice phenomenon”. Traffic engineering applications, such as re-routing or load balancing, could exploit this property by treating elephant flows differently. In this context, though, elephants should not only contribute significantly to the overall load, but also exhibit sufficient persistence in time. The challenge is to be able to examine a flow’s bandwidth and classify it as an elephant based on the data collected across all the flows on a link. In this paper, we present a classification scheme that is based on the definition of a separation threshold, that elephants have to exceed. We introduce two single-feature classification schemes, and show that the resulting elephants are highly volatile. We then propose a two-feature classification scheme that incorporates temporal characteristics and show that this approach is more successful in isolating elephants that exhibit consistency thus making them more attractive for traffic engineering applications

Optimal transport on supply-demand networks

Previously, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grid and supply chain networks, show a far different scenario in which the nodes are classified into two categories: the supply nodes provide some kinds of services, while the demand nodes require them. In this paper, we propose a general transport model for those supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogenous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the optimal configuration of supply nodes, which remarkably enhances the transport capacity, and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.Comment: 5 pages, 1 table and 4 figure

Identifiability of flow distributions from link measurements with applications to computer networks

We study the problem of identifiability of distributions of flows on a graph from aggregate measurements collected on its edges. This is a canonical example of a statistical inverse problem motivated by recent developments in computer networks. In this paper (i) we introduce a number of models for multi-modal data that capture their spatio-temporal correlation, (ii) provide sufficient conditions for the identifiability of nth order cumulants and also for a special class of heavy tailed distributions. Further, we investigate conditions on network routing for the flows that prove sufficient for identifiability of their distributions (up to mean). Finally, we extend our results to directed acyclic graphs and discuss some open problems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58107/2/ip7_5_004.pd

The ACM SIGCOMM 2009 Technical Program Committee Process

Selecting a technical program for a conference, and running the process so that decisions are well received by authors and participants, is a challenging task. We report our experience in running the SIGCOMM 2009 Technical Program Committee (TPC). The purpose of this article is to document the process that we followed, and discuss it critically. This should let authors get a better understanding of what led to the final acceptance or rejection of their work, and hopefully let other colleagues in charge of similar tasks make use of our experience

Characteristics of indoor flood fatalities: Evidence from Greece

Despite the important advances in flood forecasting and protection, floods remain one of the most lethal types of natural hazards. Previous works have explored several factors influencing the risks of flooding to human life and health. However, there is limited research and understanding on indoor flood fatalities and the circumstances under which they occur. This study explores victim-, building-, and situation-related characteristics in order to provide a better understanding of the conditions that lead to flood-related indoor deaths, exploiting a fatality database developed for Greece (1960–2020). The correlation analysis showed that indoor victims, compared with outdoor ones, tend to be older individuals, with high percentages of disabilities. A significant statistical association of the building material, roof type, and distance from the river with the building collapse was also found. The profile of the buildings in which flood fatality occurred was further compared with that of neighboring non-fatal buildings that were inhabited during the flood events. The statistical results indicated that the buildings with a fatality occurrence are mostly single-storey structures, made from masonry as the main building material. The findings have practical implications in risk communication and mitigation in terms of identifying the specific populations, circumstances, settings, and mechanisms that lead to dangerous indoor situations during flooding events. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

A database of high-impact weather events in Greece: a descriptive impact analysis for the period 2001–2011

This paper introduces the development of a database of high-impact weather events that occurred in Greece since 2001. The selected events are related to the occurrence of floods, flash floods, hail, snow/frost, tornados, windstorms, heat waves and lightning with adverse consequences (excluding those related to agriculture). The database includes, among others, the geographical distribution of the recorded events, relevant meteorological data, a brief description of the induced impacts and references in the press. This paper further offers an extensive analysis of the temporal and spatial distribution of high-impact weather events for the period 2001–2011, taking into account the intensity of weather conditions and the consequent impact on the society. Analysis of the monthly distribution of high-impact weather events showed that they are more frequent during October and November. More than 80 people lost their lives, half of which due to flash floods. In what concerns the spatial distribution of high-impact weather events, among the 51 prefectures of the country, Attica, Thessaloniki, Elia and Halkidiki were the most frequently affected areas, mainly by flash floods. Significant was also the share of tornados in Elia, of windstorms in Attica, of lightning and hail events in Halkidiki and of snow/frost events in Thessaloniki