Efficient randomised broadcasting in random regular networks with applications in peer-to-peer systems

We consider broadcasting in random d-regular graphs by using a simple modification of the random phone call model introduced by Karp et al. (Proceedings of the FOCS ’00, 2000). In the phone call model, in every time step, each node calls a randomly chosen neighbour to establish a communication channel to this node. The communication channels can then be used bi-directionally to transmit messages. We show that, if we allow every node to choose four distinct neighbours instead of one, then the average number of message transmissions per node required to broadcast a message efficiently decreases exponentially. Formally, we present an algorithm that has time complexity O(logn) and uses O(nloglogn) transmissions per message. In contrast, we show for the standard model that every distributed algorithm in a restricted address-oblivious model that broadcasts a message in time O(logn) requires Ω(nlogn/logd) message transmissions. Our algorithm efficiently handles limited communication failures, only requires rough estimates of the number of nodes, and is robust against limited changes in the size of the network. Our results have applications in peer-to-peer networks and replicated databases. Preliminary version published in the Proceedings of the 27th Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing (PODC 2008)

Diameter and Rumour Spreading in Real-World Network Models

The so-called 'small-world phenomenon', observed in many real-world networks, is that there is a short path between any two nodes of a network, whose length is much smaller that the network's size, typically growing as a logarithmic function. Several mathematical models have been defined for social networks, the WWW, etc., and this phenomenon translates to proving that such models have a small diameter. In the first part of this thesis, we rigorously analyze the diameters of several random graph classes that are introduced specifically to model complex networks, verifying whether this phenomenon occurs in them. In Chapter 3 we develop a versatile technique for proving upper bounds for diameters of evolving random graph models, which is based on defining a coupling between these models and variants of random recursive trees. Using this technique we prove, for the first time, logarithmic upper bounds for the diameters of seven well known models. This technique gives unified simple proofs for known results, provides lots of new ones, and will help in proving many of the forthcoming network models are small-world. Perhaps, for any given model, one can come up with an ad hoc argument that the diameter is O(log n), but it is interesting that a unified technique works for such a wide variety of models, and our first major contribution is introducing such a technique. In Chapter 4 we estimate the diameter of random Apollonian networks, a class of random planar graphs. We also give lower and upper bounds for the length of their longest paths. In Chapter 5 we study the diameter of another random graph model, called the random surfer Web-graph model. We find logarithmic upper bounds for the diameter, which are almost tight in the special case when the growing graph is a tree. Although the two models are quite different, surprisingly the same engine is used for proving these results, namely the powerful technique of Broutin and Devroye (Large deviations for the weighted height of an extended class of trees, Algorithmica 2006) for analyzing weighted heights of random trees, which we have adapted and applied to the two random graph models. Our second major contribution is demonstrating the flexibility of this technique via providing two significant applications. In the second part of the thesis, we study rumour spreading in networks. Suppose that initially a node has a piece of information and wants to spread it to all nodes in a network quickly. The problem of designing an efficient protocol performing this task is a fundamental one in distributed computing and has applications in maintenance of replicated databases, broadcasting algorithms, analyzing news propagation is social networks and the spread of viruses on the Internet. Given a rumour spreading protocol, its spread time is the time it takes for the rumour to spread in the whole graph. In Chapter 6 we prove several tight lower and upper bounds for the spread times of two well known randomized rumour spreading protocols, namely the synchronous push&pull protocol and the asynchronous push&pull protocol. In particular, we show the average spread time in both protocols is always at most linear. In Chapter 7 we study the performance of the synchronous push&pull protocol on random k-trees. We show that a.a.s. after a polylogarithmic amount of time, 99 percent of the nodes are informed, but to inform all vertices, a polynomial amount of time is required. Our third majoc contribution is giving analytical proofs for two experimentally verified statements: firstly, the asynchronous push&pull protocol is typically faster than its synchronous variant, and secondly, it takes considerably more time to inform the last 1 percent of the vertices in a social network than the first 99 percent. We hope that our work on the asynchronous push&pull protocol attracts attention to this fascinating model

Epidemic spreading and information dissemination in technological and social systems

In dieser Arbeit betrachten wir Probleme aus dem Bereich der Nachrichten- und Krankheitsverbreitung in dynamischen als auch statischen Strukturen aus dem Gebiet der technologischen und der sozialen Netzwerke. Als erste Fragestellung untersuchen wir, ob ein verteiltes Protokoll zur Nachrichtenverbreitung in Netzwerken mit Power Law Knotengradverteilung existiert, so dass sich die Knotengradverteilung nicht negativ bemerkbar macht. Wir präsentieren ein Protokoll, welches mit hoher Wahrscheinlichkeit nur O(log n) viele Runden mit O(n loglog n) vielen Nachrichten benötigt um alle n Knoten zu informieren. Als nächstes untersuchen wir wie Strategien zur Eindämmung einer solchen Ausbreitung aussehen könnten. Sei V der für die Ausbreitung der schädlichen Nachricht verantwortliche Prozess. Wir lassen V sich von jedem infizierten Knoten über eine konstante Anzahl von Verbindungen verbreiten. Unsere Strategie zur Bekämpfung von V wird an jedem infizierten Knoten nach einer konstanten Anzahl von Schritten aktiviert. Ist der minimale Knotengrad loglog n, so zeigen wir, dass die Immunisierung der direkten Nachbarschaft ausreicht um die Infektion mit hoher Wahrscheinlichkeit zu eliminieren. Ist der minimale Knotengrad eine Konstante und immunisiert jeder infizierte Knoten v alle Knoten in seiner O(log(d(v)))-Nachbarschaft, wobei d(v) den Knotengrad von Knoten v bezeichnet, lassen sich ähnliche Abschätzungen zeigen. Zudem betrachten wir eine Epidemie in einer städtischen Umgebung mit mobilen Einwohnern. Werden keinerlei Gegenmaßnahmen getroffen, so bleibt dennoch mit hoher Wahrscheinlichkeit ein polynomieller Anteil der Population von der Epidemie unberührt. Werden jedoch Gegenmaßnahmen genutzt, so werden mit Wahrscheinlichkeit 1-o(1) nur polylogarithmisch viele Individuen infiziert.In this thesis we consider the problems of information dissemination and epidemic spreading in dynamic as well as static technological and social networks. We start by wondering if there might be a fast decentralized dissemination protocol, such that a power law degree distribution does not slow down the dissemination process in the network. We present a protocol that informs all n nodes within O(log n) many rounds using O(n loglog n) many transmissions with high probability. But how do we design a counteracting dissemination process to combat the malicious one denoted by V? Suppose V uses a constant number of randomly chosen connections of each infected node to infect others for one time only and suppose that the counteracting dissemination process is activated on each infected node after a constant delay. We show that it suffices to immunize the neighborhood of each infected node, provided the minimum degree of the network is loglog n. Otherwise, if the minimum degree of the network is constant, we propose to immunize every node within O(log(d(v))) many hops of each infected node v, where d(v) denotes the degree of node v. Executing these strategies we prove that V does not infect more than o(n) many nodes until it is eliminated with high probability. Finally, we take mobility into account and examine an epidemic outbreak in an urban environment inhabited by mobile individuals on a small and on a large scale. Amongst others, we show that at least a polynomial fraction of the individuals remains uninfected even if they do not respond to the epidemic outbreak in any way. However, if the epidemic outbreak does influence the individual's behavioral pattern and certain countermeasures are applied, then only a polylogarithmic amount of individuals is infected until the epidemic is embanked with probability 1-o(1).Tag der Verteidigung: 24.10.2014Paderborn, Univ., Diss., 201