Dependability in Aggregation by Averaging

Aggregation is an important building block of modern distributed applications, allowing the determination of meaningful properties (e.g. network size, total storage capacity, average load, majorities, etc.) that are used to direct the execution of the system. However, the majority of the existing aggregation algorithms exhibit relevant dependability issues, when prospecting their use in real application environments. In this paper, we reveal some dependability issues of aggregation algorithms based on iterative averaging techniques, giving some directions to solve them. This class of algorithms is considered robust (when compared to common tree-based approaches), being independent from the used routing topology and providing an aggregation result at all nodes. However, their robustness is strongly challenged and their correctness often compromised, when changing the assumptions of their working environment to more realistic ones. The correctness of this class of algorithms relies on the maintenance of a fundamental invariant, commonly designated as "mass conservation". We will argue that this main invariant is often broken in practical settings, and that additional mechanisms and modifications are required to maintain it, incurring in some degradation of the algorithms performance. In particular, we discuss the behavior of three representative algorithms Push-Sum Protocol, Push-Pull Gossip protocol and Distributed Random Grouping under asynchronous and faulty (with message loss and node crashes) environments. More specifically, we propose and evaluate two new versions of the Push-Pull Gossip protocol, which solve its message interleaving problem (evidenced even in a synchronous operation mode).Comment: 14 pages. Presented in Inforum 200

Security Policy Consistency

With the advent of wide security platforms able to express simultaneously all the policies comprising an organization's global security policy, the problem of inconsistencies within security policies become harder and more relevant. We have defined a tool based on the CHR language which is able to detect several types of inconsistencies within and between security policies and other specifications, namely workflow specifications. Although the problem of security conflicts has been addressed by several authors, to our knowledge none has addressed the general problem of security inconsistencies, on its several definitions and target specifications.Comment: To appear in the first CL2000 workshop on Rule-Based Constraint Reasoning and Programmin

Spectra: Robust Estimation of Distribution Functions in Networks

Distributed aggregation allows the derivation of a given global aggregate property from many individual local values in nodes of an interconnected network system. Simple aggregates such as minima/maxima, counts, sums and averages have been thoroughly studied in the past and are important tools for distributed algorithms and network coordination. Nonetheless, this kind of aggregates may not be comprehensive enough to characterize biased data distributions or when in presence of outliers, making the case for richer estimates of the values on the network. This work presents Spectra, a distributed algorithm for the estimation of distribution functions over large scale networks. The estimate is available at all nodes and the technique depicts important properties, namely: robust when exposed to high levels of message loss, fast convergence speed and fine precision in the estimate. It can also dynamically cope with changes of the sampled local property, not requiring algorithm restarts, and is highly resilient to node churn. The proposed approach is experimentally evaluated and contrasted to a competing state of the art distribution aggregation technique.Comment: Full version of the paper published at 12th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS), Stockholm (Sweden), June 201

The Optimized Model of Multiple Invasion Percolation

We study the optimized version of the multiple invasion percolation model. Some topological aspects as the behavior of the acceptance profile, coordination number and vertex type abundance were investigated and compared to those of the ordinary invasion. Our results indicate that the clusters show a very high degree of connectivity, spoiling the usual nodes-links-blobs geometrical picture.Comment: LaTeX file, 6 pages, 2 ps figure

Oil prices assumptions in macroeconomic forecasts: should we follow futures market expectations?

In macroeconomic forecasting, in spite of its important role in prices and activity developments, oil prices are usually taken as an exogenous variable for which assumptions have to be made. This paper evaluates the forecasting performance of futures markets prices against other popular technical procedure, the carry-over assumption. The results suggest that it is almost indifferent to opt for the futures market prices or the carry over assumption for short-term forecasting horizons (up to 12 months), while, for longer-term horizons, they favour the use of futures market prices. However, as futures markets prices reflect the markets expectations for the world economic activity, futures oil prices should be adjusted whenever the market expectations for the world economic growth are different from the values underlying the macroeconomic scenarios in order to assure fully internal consistency of those scenarios.

Fast Distributed Computation of Distances in Networks

This paper presents a distributed algorithm to simultaneously compute the diameter, radius and node eccentricity in all nodes of a synchronous network. Such topological information may be useful as input to configure other algorithms. Previous approaches have been modular, progressing in sequential phases using building blocks such as BFS tree construction, thus incurring longer executions than strictly required. We present an algorithm that, by timely propagation of available estimations, achieves a faster convergence to the correct values. We show local criteria for detecting convergence in each node. The algorithm avoids the creation of BFS trees and simply manipulates sets of node ids and hop counts. For the worst scenario of variable start times, each node i with eccentricity ecc(i) can compute: the node eccentricity in diam(G)+ecc(i)+2 rounds; the diameter in 2*diam(G)+ecc(i)+2 rounds; and the radius in diam(G)+ecc(i)+2*radius(G) rounds.Comment: 12 page