Abstract: Large-scale sensor networks, monitoring an environment at close range with high spatial and temporal resolutions are expected to play an important role in various applications, e.g., assessing the ``health'' of machines; environmental, medical, food-safety, and habitat monitoring; inventory control, building automation, etc. Ensuring the security of these complex and yet resource-constrained systems has emerged as one of the most pressing challenges for researchers. In this paper (i) we present the major threats and some characteristic countermeasures, (ii) we propose a way to classify existing systems for intrusion detection in wireless sensor networks and (iii) we present a new approach for decentralized energy efficient intrusion detection that can be used to improve security from both external and internal adversaries.

Abstract: In this work, we study the propagation of influence and computation in dynamic networks that are possibly disconnected at every instant. We focus on a synchronous message passing communication model with broadcast and bidirectional links. To allow for bounded end-to-end communication we propose a set of minimal temporal connectivity conditions that bound from the above the time it takes for information to make progress in the network. We show that even in dynamic networks that are disconnected at every instant information may spread as fast as in networks that are connected at every instant. Further, we investigate termination criteria when the nodes know some upper bound on each of the temporal connectivity conditions. We exploit our termination criteria to provide efficient protocols (optimal in some cases) that solve the fundamental counting and all-to-all token dissemination (or gossip) problems. Finally, we show that any protocol that is correct in instantaneous connectivity networks can be adapted to work in temporally connected networks.

Abstract: In this work, we study the propagation of influence and computation in dynamic distributed computing systems that are possibly disconnected at every instant. We focus on a synchronous message-passing communication model with broadcast and bidirectional links. Our network dynamicity assumption is a worst-case dynamicity controlled by an adversary scheduler, which has received much attention recently. We replace the usual (in worst-case dynamic networks) assumption that the network is connected at every instant by minimal temporal connectivity conditions. Our conditions only require that another causal influence occurs within every time window of some given length. Based on this basic idea, we define several novel metrics for capturing the speed of information spreading in a dynamic network. We present several results that correlate these metrics. Moreover, we investigate termination criteria in networks in which an upper bound on any of these metrics is known. We exploit our termination criteria to provide efficient (and optimal in some cases) protocols that solve the fundamental counting and all-to-all token dissemination (or gossip) problems.

Abstract: In this chapter, our focus is on computational network analysis from a theoretical point of view. In particular, we study the \emph{propagation of influence and computation in dynamic distributed computing systems}. We focus on a \emph{synchronous message passing} communication model with bidirectional links. Our network dynamicity assumption is a \emph{worst-case dynamicity} controlled by an adversary scheduler, which has received much attention recently. We first study the fundamental \emph{naming} and \emph{counting} problems (and some variations) in
networks that are \emph{anonymous}, \emph{unknown}, and possibly dynamic. Network dynamicity is modeled here by the \emph{1-interval connectivity model}, in which communication is synchronous and a (worst-case) adversary
chooses the edges of every round subject to the condition that each instance is connected. We then replace this quite strong assumption by minimal \emph{temporal connectivity} conditions. These conditions only require that \emph{another causal influence occurs within every time-window of some given length}. Based on this basic idea we define several novel metrics for capturing the speed of information spreading in a dynamic network. We present several results that correlate these metrics. Moreover, we investigate \emph{termination criteria} in networks in which an upper bound on any of these metrics is known. We exploit these termination criteria to provide efficient (and optimal in some cases) protocols that solve the fundamental \emph{counting} and \emph{all-to-all token dissemination} (or \emph{gossip}) problems. Finally, we propose another model of worst-case temporal connectivity, called \emph{local
communication windows}, that assumes a fixed underlying communication network and restricts the adversary to allow communication between local neighborhoods in every time-window of some fixed length. We prove some basic properties and provide a protocol for counting in this model.

Abstract: In this article, we present a detailed performance
evaluation of a hybrid optical switching (HOS)
architecture called Overspill Routing in Optical Networks
(ORION). The ORION architecture combines
(optical) wavelength and (electronic) packet switching,
so as to obtain the individual advantages of both switching
paradigms. In particular, ORION exploits the possible insertions/extractions, to reduce the necessary
interfaces, do not deteriorate performance and thus the
use of traffic concentrators assure ORION’s economic
viability.
idle periods of established lightpaths to transmit
packets destined to the next common node, or even
directly to their common end-destination. Depending
on whether all lightpaths are allowed to simultaneously
carry and terminate overspill traffic or overspill is restricted
to a sub-set of wavelengths, the architecture
limits itself to constrained or un-constrained ORION. To
evaluate both cases, we developed an extensive network
simulator where the basic features of the ORION architectureweremodeled,
including suitable edge/core node
switches and load-varying sources to simulate overloading
traffic conditions. Further, we have assessed various
aspects of the ORION architecture including two
basic routing/forwarding policies and various buffering
schemes. The complete network study shows that
ORION can absorb temporal traffic overloads, as intended,
provided sufficient buffering is present.We also
demonstrate that the restriction of simultaneous packet

Abstract: This research further investigates the recently introduced
(in [4]) paradigm of radiation awareness in ambient environments with abundant heterogeneous wireless networking
from a distributed computing perspective. We call radiation
at a point of a wireless network the total amount of electromagnetic quantity the point is exposed to; our denition incorporates the eect of topology as well as the time domain
and environment aspects. Even if the impact of radiation to
human health remains largely unexplored and controversial,
we believe it is worth trying to understand and control, in
a way that does not decrease much the quality of service
oered to users of the wireless network.
In particular, we here focus on the fundamental problem
of ecient data propagation in wireless sensor networks, try-
ing to keep latency low while maintaining at low levels the
radiation cumulated by wireless transmissions. We rst propose greedy and oblivious routing heuristics that are radiation aware. We then combine them with temporal back-o
schemes that use local properties of the network (e.g. number of neighbours, distance from sink) in order to spread" radiation in a spatio-temporal way. Our proposed radiation
aware routing heuristics succeed to keep radiation levels low,
while not increasing latency.

Abstract: In this paper we address the problem of capturing and pro-
cessing certain spatiotemporal, social characteristics of hu-
man interactions with the use of Wireless Sensor Networks.
Using TelosB motes, we basically monitor the binary prox-
imity within a group of people. The collected data give an
insight of how people interact with each other (how often,
for how much time, in which room) and provide a novel tool
(which can be further enhanced) to study (quantitatively, in
an automated manner) human social networks.

Abstract: In this paper we address the problem of capturing and pro-
cessing certain spatiotemporal, social characteristics of hu-
man interactions with the use of Wireless Sensor Networks.
Using TelosB motes, we basically monitor the binary prox-
imity within a group of people. The collected data give an
insight of how people interact with each other (how often,
for how much time, in which room) and provide a novel tool
(which can be further enhanced) to study (quantitatively, in
an automated manner) human social networks.

Abstract: In this work we consider temporalnetworks, i.e. networks defined by a labeling $\lambda$ assigning to each edge of an underlying graph G a set of discrete time-labels. The labels of an edge, which are natural numbers, indicate the discrete time moments at which the edge is available. We focus on path problems of temporalnetworks. In particular, we consider time-respecting paths, i.e. paths whose edges are assigned by $\lambda$ a strictly increasing sequence of labels. We begin by giving two efficient algorithms for computing shortest time-respecting paths on a temporalnetwork. We then prove that there is a natural analogue of Menger’s theorem holding for arbitrary temporalnetworks. Finally, we propose two cost minimization parameters for temporalnetwork design. One is the temporality of G, in which the goal is to minimize the maximum number of labels of an edge, and the other is the temporal cost of G, in which the goal is to minimize the total number of labels used. Optimization of these parameters is performed subject to some connectivity constraint. We prove several lower and upper bounds for the temporality and the temporal cost of some very basic graph families such as rings, directed acyclic graphs, and trees.