Imagine that in a few years from now a full-scale, practical quantum computer hits the headlines. In this apocalyptic scenario, the world of cryptography would be in a state of shock, since almost everything that forms the foundations of current security would collapse. Indeed, the presence of a quantum computer would render state-of-the-art, public-key cryptography useless. All the underlying assumptions about the intractability of mathematical problems that offer confident levels of security today would no longer apply in the presence of a quantum computer. But are we really doomed? Is cryptography dead? Well, luckily no. This paper examines the technologies that will enable crypto to survive the post-apocalyptic world of quantum computing. There are many things yet to be done to offer an environment as safe as current crypto does, but the tools are there. It is now a game of engineering, pro-active standardization and ingenious mathematics, while following a careful development approach to pave a safe way through the qubits inferno .

In this paper we summarize recent research regarding a novel characterization of large-scale real-life informational networks which can be leveraged to speed computations for network analytics purposes by orders of magnitude. First, using publicly available data, we show that informational networks not only satisfy well-known principles such as the small-world property and variants of the power law degree distribution, but that they also exhibit the geometric property of large-scale negative curvature, also referred to as hyperbolicity. We then provide examples of large-scale physical networks that universally lack this property, thus showing that hyperbolicity is not an ever-present feature of real-life networks in general. We document how hyperbolicity leads to unusually high centrality in informational networks. We then describe an approximation of hyperbolic networks that leverages the observed property of high centrality. We provide evidence that the fidelity of the proposed approximation is not only high for applications such as distance approximation, but that it can speed computation by a factor of 1000X or more. Finally, we discuss two applications of our proposed linear-time distance approximation for informational networks: one for personalized ranking and the other for clustering. These and many more algorithms yet to be developed take full advantage of our proposed tree-approximation of hyperbolic networks and further demonstrate its power and utility.

In recent years, enterprise social networking (ESN) has gained a foothold in many companies. While there are numerous similarities between enterprise and public online social networks such as Facebook or Twitter, there are also important differences, many of which are driven by the inherent organizational structure of an enterprise, that make ESNs an important area to study in their own right. This paper describes the ESN applications that have been used within Alcatel-Lucent over the past several years, focusing on the most recent. We discuss the tools and methodologies utilized to gain access to Alcatel-Lucent's ESN usage data and to perform various types of analyses and visualizations of that data. We provide some statistics about ESN usage within the company and give insights into some of the questions that ESN tools can help to answer, such as the degree to which ESN applications break down geographic and/or organizational boundaries. Our analyses show that employees in the middle levels of the company hierarchy tend to use ESN the most, and that there is a considerable amount of inter-country communication occurring. ® 2014 Alcatel-Lucent.

Telecommunication networks deliver a massive volume of data to individuals and institutions day after day. Network operations also generate valuable data about the network's own health and status. Similarly, records of the activities they support convey much about the subscribers and devices they serve. In each context, there are opportunities to drive information up the value chain, transforming raw data into knowledge. Innovative use of data analytic methodologies can therefore be central to enhancements of telecom networks' capabilities and value.

The “privacy versus personalization” dilemma refers to the situation in which it is necessary for users to disclose their sensitive personal data in order to benefit from collaborative personalized services. Solving this dilemma is a challenge because generating collaborative filtering recommendations requires access to the set of all user profiles in order to identify similar ones, and to compute the top-rated items. The privacy-preserving personalization (P3) paradigm builds on the idea of using locality-sensitive hashing (LSH) to find groups of similar users, while keeping their profiles local. In this work, we analyze the behavior of the adapted LSH algorithm from the perspective of the quality of final recommendations and the distribution of cluster sizes. We investigate the impact of different LSH parameter configurations on the basis of the MovieLens dataset, and empirically show a small, non-prohibitive cost of privacy protection on the recommendations' quality..

Mobile communications have evolved through countless innovations that have resulted in massively improved performance and significantly lower cost with each technology generation. Beginning with the firm theoretical foundations for communications laid by Claude Shannon in 1948, successive improvements in cellular technology have been achieved through a combination of advances in communication theory, computing power, and analog radio frequency (RF) circuit electronics. In this paper, we chart the course of successive generations of mobile technology highlighting some of the key innovations resulting in the major performance improvements that have been achieved over the years. We begin with a high-level discussion of the key technology generations starting with the analog cellular systems deployed in the 1980s through to the 4G Long Term Evolution (LTE) system being deployed today. We highlight the 11 major technical advances that have led to the most significant improvements in cellular technology and then present a view of the future wireless evolution to the beginning of the 5G era.

In this paper we provide analytical insights for dimensioning a multi-layer network and in particular the virtual optical transport network topology exported to the packet client layer according to cost and power consumption. A new approach is described, approximating optimum routing, that can be effectively used to provide an estimation of network cost and reference architectures in network implementations. Results using this estimation approach are compared with those obtained using other estimation approaches regarding bandwidth allocation and network costs. We found that the approximated routing calculations, applied on a virtual network topology, do not significantly penalize the accuracy of the results. This approach can be extended to analyze the impact of new a optical networking technique, flexible-grid wavelength division multiplexing (WDM), providing some insights regarding scenarios in which migration from fixed-grid WDM systems to flexible-grid WDM systems would be advantageous in terms of capital cost and power consumption.

After extensive comparison of candidate technologies, the Full Service Access Network (FSAN) Group in early 2012 made the decision to define Time/ Wavelength Division Multiplexing (TWDM) as the primary solution for the next-generation passive optical network (NG-PON2). A minimum of four wavelengths are foreseen as providing a total capacity per feeder line of 40 Gbit/s downstream and 10 Gbit/s or more upstream. Conventional wavelength division multiplexing (WDM) lasers from core or metro networks are too expensive for fiber to the home (FTTH) systems, because every optical network unit (ONU) will need a tunable laser for upstream transmission. In this paper we will compare different technical solutions and present wavelength-set division multiplexing (WSDM), a scheme developed by Bell Labs as the preferred solution for cost reasons. WSDM uses a laser that can be tuned by an on-chip heater stripe. To exploit this partial wavelength tunability, we do not use contiguous wavelength bands, but wavelength-sets consisting of cyclic interleaved wavelength slots on a fine grid. This wavelength plan can be implemented, e.g., by a cyclic arrayed waveguide grating (AWG) with a small free spectral range. We will describe the concept in detail and report on its experimental validation.