A new framework for conflict-free coloring of hypergraphs is presented, leading to a novel graph problem which generalizes the partition and the list coloring problems, well-known for their multiple applications. Two integer linear programming formulations are proposed for this problem: a compact formulation inspired by the pioneering formulation for the vertex coloring problem and a set covering formulation whose variables are associated with stable sets. For the latter formulation, a branch-and-price algorithm is developed. Computational experiments in random instances validate the superiority of this approach over the direct solution of the compact formulation with a commercial solver.

ABSTRACT In the minimum clique routing problem on cycles mcrpc, we are given a cycle together with a set of demands (weighted terminals pairs) and the goal is to route all the pairs minimizing the maximum weight clique of the intersection graph induced by the routing. The nodes of this graph are the demands with their corresponding weights and two demands are adjacent when their routes share at least one arc. In this work, we are not only interested in the mcrpc but also in two natural subproblems. First, we consider the situation where the demands are disjoint, in the sense that every two demands do not share any of their corresponding terminals. Second, we analyze the subproblem where the weights of the routes are all equal. We first show that the problem is NP‐hard even in the subproblem of disjoint demands. For the case of arbitrary weights, we exhibit a simple combinatorial 2‐approximation algorithm and a ‐approximation algorithm based on rounding a solution of a relaxation of an integer linear programming formulation of our problem. Finally, we give a fixed parameter tractable algorithm for the case of uniform weights, whose parameter is the maximum number of demands for which a demand exists whose terminals alternate in the cycle with the terminals of each of them.

The World Wide Web has evolved rapidly, incorporating new content types and becoming more dynamic. The contents from a website can be distributed between several servers, and as a consequence, web traffic has become increasingly complex. From a network traffic perspective, it can be difficult to ascertain which websites are being visited by a user, let alone which part of the user's traffic each website is responsible for. In this paper we present a method for identifying the TCP connections involved in the same full webpage download without the need of deep packet inspection. This identification is needed for example to enable free browsing of specific websites in a pay per use mobile Internet access. It could be not only for third party promoted websites but also portals to gubernamental or medical emergency websites. The proposal is based on a modification of the DBSCAN clustering algorithm to work online and over one-dimensional sorted data. In order to validate our results we use both real traffic and packet captures from a controlled environment. The proposal achieves excellent results in consistency (99%) and completeness (92%), meaning that its error margin identifying the webpage downloads is minimal.

This work is based on an extension of the Petri net framework. Our model relies on the definition of a priority relation between conflicting transitions, which is encoded in a compact manner by orienting the edges of a transition conflict graph. The benefit is that this allows the use of a successor function for the study of dynamic processes from a global point of view, independent from a particular initial state and the (complete) construction of the reachability graph. We address the problem of gaining the information that allows to provide an appropriate priority relation governing the dynamic behavior of the studied system and discuss some further implications and generalizations of the studied approach.

Abstract In social networking sites, it is useful to receive recommendations about whom to contact or follow. These recommendations not only allow to establish connections with people one might already know in real life but also with people or users that have similar interests or are potentially interesting. We propose an approach that tackles contact (followee) recommendation in Twitter by means of fuzzy logic. This fuzzy approach handles recommendation as a link prediction problem and uses three types of similarity between a pair of users: tweet similarity, followee id similarity, and followee tweet similarity. These similarities are calculated by extracting user profiles. These profiles are, in turn, obtained by considering Twitter as a heterogeneous information network. To test our approach, we crawled a repository of 6000 users and two million tweets, and we measured accuracy by comparing our results with the actual followee lists of the users. These results, which are also compared against the results given by state‐of‐the‐art methods, show a high accuracy. Other advantages of the fuzzy system include a self‐explanatory capability and the ability to produce a non‐binary friendship value.

Abstract—Over the last years websites have evolved rapidly incorporating new content types and becoming more and more dynamic. Users today are able to access a wide variety of content and services through their web browsers. As a consequence, web traffic has become increasingly complex and, from a network perspective it can be difficult to ascertain which websites are being visited by a user, let alone which part of the user’s traffic each of them is responsible for. Although there is an extensive literature on the new charac-teristics of web traffic, few works have focused on a connection level perspective even if this kind of data is easily available for network administrators. In this paper we offer a characteriza-tion of webpage download using connection level metrics. This description is a first step in developing techniques able to identify individual webpage downloads in real traffic. We have captured an extensive dataset of more than 20,000 webpage downloads that we study in order to provide different connection level based metrics. We study how these metrics vary between different webpages of different popularity and complexity. In the end, we attempt to provide a general modelling of a normal webpage download. I.

In the field of traffic classification, previous efforts have been centered on identifying applications (HTTP, SMTP, FTP, etc) rather than the actual services that they provide (email, file transfer, video streaming, etc.). Nowadays, however, a single application as HTTP can provide multiple services for the end-user. Some methods have been proposed to distinguish between these services but tuning and testing them remains a challenge as there is no easy way to obtain labelled HTTP traffic traces. In this paper we present a method to discover server IP addresses related to a specific website in a traffic trace. Our method uses NetFlow-type records which makes it scalable an impervious to encryption of packet payloads. By applying the method to a representative set of websites the resulting list of IP addresses can be used to label a sizeable number of connections in the trace.