No abstract

Cache-oblivious algorithms have been advanced as a way of circumventing some of the difficulties of optimizing applications to take advantage of the memory hierarchy of modern microprocessors. These algorithms are based on the divide-and-conquer paradigm -each division step creates sub-problems of smaller size, and when the working set of a sub-problem fits in some level of the memory hierarchy, the computations in that sub-problem can be executed without suffering capacity misses at that level. In this way, divideand-conquer algorithms adapt automatically to all levels of the memory hierarchy; in fact, for problems like matrix multiplication, matrix transpose, and FFT, these recursive algorithms are optimal to within constant factors for some theoretical models of the memory hierarchy.An important question is the following: how well do carefully tuned cache-oblivious programs perform compared to carefully tuned cache-conscious programs for the same problem? Is there a price for obliviousness, and if so, how much performance do we lose? Somewhat surprisingly, there are few studies in the literature that have addressed this question.This paper reports the results of such a study in the domain of dense linear algebra. Our main finding is that in this domain, even highly optimized cache-oblivious programs perform significantly worse than corresponding cacheconscious programs. We provide insights into why this is so, and suggest research directions for making cache-oblivious algorithms more competitive.

In this paper, we describe the design and implementation of a distributed operating system for ad hoc networks. Our system simplifies the programming of ad hoc networks and extends total system lifetime by making the entire network appear as a single virtual machine. It automatically and transparently partitions applications into components and dynamically finds them a placement on nodes within the network to reduce energy consumption and to increase system longevity. This paper describes our programming model, outlines the design and implementation of our system and examines the energy efficiency of our approach through extensive simulations as well as validation of a deployment on a physical testbed. We evaluate practical, power-aware, general-purpose algorithms for component placement and migration, and demonstrate that they can significantly increase system longevity by effectively distributing energy consumption and avoiding hotspots.

Proactive obfuscation is a new method for creating server replicas that are likely to have fewer shared vulnerabilities. It uses semantics-preserving code transformations to generate diverse executables, periodically restarting servers with these fresh versions. The periodic restarts help bound the number of compromised replicas that a service ever concurrently runs, and therefore proactive obfuscation makes an adversary's job harder. Proactive obfuscation was used in implementing two prototypes: a distributed firewall based on state-machine replication and a distributed storage service based on quorum systems. Costs intrinsic to supporting proactive obfuscation in replicated systems were evaluated by measuring the performance of these prototypes. The results show that employing proactive obfuscation adds little to the cost of replica-management protocols.

Abstract. Multi-verifier signatures generalize public-key signatures to a secret-key setting. Just like public-key signatures, these signatures are both transferable and secure under arbitrary (unbounded) adaptive chosen-message attacks. In contrast to public-key signature schemes, however, we exhibit practical constructions of multi-verifier signature schemes that are provably secure and are based only on pseudorandom functions in the plain model without any random oracles.