Abstract: Many efforts have been done in the last years to model public transport timetables in order to
find optimal routes. The proposed models can be classified into two types: those representing the
timetable as an array, and those representing it as a graph. The array-based models have been
shown to be very effective in terms of query time, while the graph-based models usually answer
queries by computing shortest paths, and hence they are suitable to be used in combination with
speed-up techniques developed for road networks.
In this paper, we focus on the dynamic behavior of graph-based models considering the case
where transportation systems are subject to delays with respect to the given timetable. We
make three contributions: (i) we give a simplified and optimized update routine for the wellknown
time-expanded model along with an engineered query algorithm; (ii) we propose a new
graph-based model tailored for handling dynamicupdates; (iii) we assess the effectiveness of
the proposed models and algorithms by an experimental study, which shows that both models
require negligible update time and a query time which is comparable to that required by some
array-based models.

Abstract: In this book chapter we will consider key establishment protocols for wireless sensor networks.
Several protocols have been proposed in the literature for the establishment of a shared group key for wired networks.
The choice of a protocol depends whether the key is established by one of the participants (and then transported to the other(s)) or agreed among the participants, and on the underlying cryptographic mechanisms (symmetric or asymmetric). Clearly, the design of key establishment protocols for sensor networks must deal with different problems and challenges that do not exist in wired networks. To name a few, wireless links are particularly vulnerable to eavesdropping, and that sensor devices can be captured (and the secrets they contain can be compromised); in many upcoming wireless sensor networks, nodes cannot rely on the presence of an online trusted server (whereas most standardized authentication and key establishment protocols do rely on such a server).
In particular, we will consider five distributed group key establishment protocols. Each of these protocols applies a different algorithmic technique that makes it more suitable for (i) static sensor networks, (ii) sensor networks where nodes enter sleep mode (i.e. dynamic, with low rate of updates on the connectivity graph) and (iii) fully dynamic networks where nodes may even be mobile. On the other hand, the common factor for all five protocols is that they can be applied in dynamic groups (where members can be excluded or added) and provide forward and backward secrecy. All these protocols are based on the Diffie-Hellman key exchange algorithm and constitute natural extensions of it in the multiparty case.

Abstract: We consider information aggregation as a method for reducing the information exchanged in a Grid network and used by the resource manager in order to make scheduling decisions. In this way, information is summarized across nodes and sensitive or detailed information can be kept private, while resources are still publicly available for use. We present a general framework for information aggregation, trying to identify issues that relate to aggregation in Grids. In this context, we describe a number of techniques, including single point and intra-domain aggregation, define appropriate grid-specific domination relations and operators for aggregating static and dynamic resource information, and discuss resource selection optimization functions. The quality of an aggregation scheme is measured both by its effects on the efficiency of the scheduler¢s decisions and also by the reduction it brings on the amount of resource information recorded, a tradeoff that we examine in detail. Simulation experiments demonstrate that the proposed schemes achieve significant information reduction, either in the amount of information exchanged, or in the frequency of the updates, while at the same time maintaining most of the value of the original information as expressed by a stretch factor metric we introduce.

Abstract: We consider the problem of preprocessing an n-vertex digraph with real edge weights so that
subsequent queries for the shortest path or distance between any two vertices can be efficiently answered. We
give algorithms that depend on the treewidth of the input graph. When the treewidth is a constant, our algorithms
can answer distance queries in O ({\'a}(n) ) time after O.n/ preprocessing. This improves upon previously known
results for the same problem.We also give a dynamic algorithm which, after a change in an edge weight, updates
the data structure in time O.n¯ /, for any constant 0 < ¯ < 1. Furthermore, an algorithm of independent interest
is given: computing a shortest path tree, or finding a negative cycle in linear time.

Abstract: We consider the problem of preprocessing an n-vertex digraph with real edge weights so that subsequent queries for the shortest path or distance between any two vertices can be efficiently answered. We give parallel algorithms for the EREW PRAM model of computation that depend on the treewidth of the input graph. When the treewidth is a constant, our algorithms can answer distance queries in O({\'a}(n)) time using a single processor, after a preprocessing of O(log2n) time and O(n) work, where {\'a}(n) is the inverse of Ackermann's function. The class of constant treewidth graphs contains outerplanar graphs and series-parallel graphs, among others. To the best of our knowledge, these are the first parallel algorithms which achieve these bounds for any class of graphs except trees. We also give a dynamic algorithm which, after a change in an edge weight, updates our data structures in O(log n) time using O(n{\^a}) work, for any constant 0 < {\^a} < 1. Moreover, we give an algorithm of independent interest: computing a shortest path tree, or finding a negative cycle in O(log2n) time using O(n) work.