Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Sequential measurement-based quantum computing with memories

We introduce a general scheme for sequential one-way quantum computation where static systems with long-living quantum coherence (memories) interact with moving systems that may possess very short coherence times. Both the generation of the cluster state needed for the computation and its consumption by measurements are carried out simultaneously. As a consequence, effective clusters of one spatial dimension fewer than in the standard approach are sufficient for computation. In particular, universal computation requires only a one-dimensional array of memories. The scheme applies to discrete-variable systems of any dimension as well as to continuous-variable ones, and both are treated equivalently under the light of local complementation of graphs. In this way our formalism introduces a general framework that encompasses and generalizes in a unified manner some previous system-dependent proposals. The procedure is intrinsically well suited for implementations with atom-photon interfaces.

Trade-offs between personal immunity and reproduction in the burying beetle, Nicrophorus vespilloides

How are resources split between caring for offspring and self-maintenance? Is the timing of immune challenge important? In burying beetles challenging the immune system prior to breeding does not affect the total number and quality of offspring produced during the individual's lifetime. However, the immune system is suppressed during breeding and if an immune challenge is presented during this time the beetle will upregulate its immune system, but at the detriment to the number of offspring produced during that breeding opportunity.We know that parental investment and immune investment are costly processes, but it is unclear which trait will be prioritized when both may be required. Here, we address this question using the burying beetle Nicrophorus vespilloides, carrion breeders that exhibit biparental care of young. Our results show that immunosuppression occurs during provision of parental care. We measured phenoloxidase (PO) on Days 1-8 of the breeding bout and results show a clear decrease in PO immediately from presentation of the breeding resource onward. Having established baseline immune investment during breeding we then manipulated immune investment at different times by applying a wounding challenge. Beetles were wounded prior to and during the parental care period and reproductive investment quantified. Different effects on reproductive output occur depending on the timing of wounding. Challenging the immune system with wounding prior to breeding does not affect reproductive output and subsequent lifetime reproductive success (LRS). LRS is also unaffected by applying an immune elicitor prior to breeding, though different arms of the immune system are up/downregulated, perhaps indicating a trade-off between cellular and humoral immunity. In contrast, wounding during breeding reduces reproductive output and to the greatest extent if the challenge is applied early in the breeding bout. Despite being immunosuppressed, breeding beetles can still respond to wounding by increasing PO, albeit not to prebreeding levels. This upregulation of PO during breeding may affect parental investment, resulting in a reduction in reproductive output. The potential role of juvenile hormone in controlling this trade-off is discussed.

Energy Efficiency through Significance-Based Computing

An extension of approximate computing, significance-based computing exploits applications' inherent error resiliency and offers a new structural paradigm that strategically relaxes full computational precision to provide significant energy savings with minimal performance degradation.