Distributed pre-computation for a cryptanalytic time-memory trade-off

adversary. In this paper, we introduce the concept of information-theoretically secure file delivery when the files have a non-uniform popularity distribution. For this scenario, the cache memory of each user is split into two parts: one part is used to store data (some function of the files), whereas

.) that both affect performance of real-time applications. Distributing information over different packets can increase transmission reliability at the price of further delays. Packet interleaving can improve communication performance when some delay is allowed and re-transmission is not. The trade-off between

, we propose new scalable techniques that allow large SMPs to be tied together efficiently, while maintaining the compatibility with, and performance characteristics of, an SMP. The trade-offs of such an architecture differ from those of traditional, scalable, Non-Uniform Memory Architecture (cc

of classical cryptanalytic advances or progress on the development of quantum computers the hardness of these closely related problems might be seriously weakened. A potential alternative approach is the construction of sig-nature schemes based on the hardness of certain lattices problems which are assumed

Message-oriented middleware (MOM) is at the core of a vast number of financial services and telco applications, and is gaining increasing traction in other industries, such as manufacturing, transportation, health-care and supply chain management. Novel messaging applications, however, pose some serious performance and scalability challenges. In this paper, we present a methodology for performance evaluation of MOM platforms using the SPECjms2007 standard benchmark. SPECjms2007 is based on a novel application in the supply chain management domain designed to stress MOM infrastructures in a manner representative of real-world applications. In addition to providing a standard workload and metrics for MOM performance, the benchmark provides a flexible performance analysis framework that allows users to tailor the workload to their requirements. The contributions of this paper are: i) we present a detailed workload characterization of SPECjms2007 with the goal to help users understand the internal components of the workload and the way they are scaled, ii) we show how the workload can be customized to exercise and evaluate selected aspects of MOM performance, iii) we present a case study of a leading JMS platform, the BEA WebLogic server, conducting an in-depth performance analysis of the platform under a number of different workload and configuration scenarios. The methodology we propose is the first one that uses a standard benchmark providing both a representative workload as Message-oriented middleware (MOM) is increasingly adopted as an enabling technology for modern event-driven applications

of the transmitted pulse. The large amounts of sampled data also necessitate vast memory capacity. In addition, real-time processing of the data typically results in high power consumption. Recently, new approaches for radar sensing and estimation were introduced, based on the Finite Rate of Innovation and Xampling

April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by:

. Recently, many authors have suggested applying sparse recovery algorithms in the context of similar estimation or detection problems. These works typically focus on the benefits of sparse recovery, but not generally on the cost brought by compressive sensing. Thus, our goal is to examine the trade-off

I first thank my thesis advisors Thiemo Voigt and Adam Dunkels for being my excellent advisors, and also for being the great colleagues you still are. Thiemo and Adam have complemented each other superbly, giving me feedback, perspectives, insights, and having made every single new venture truly fun. My deepest thanks also go to my professor Per Gunningberg, Uppsala University. Per has in a seemingly easy way spotted erroneous assumptions, has valued my research contributions, and has connected my own work with another broader world of research. I want to thank all colleagues in the Networked Embedded Systems group: