Community related applications such as dating platforms, instant messengers, or file-sharing tools enjoy a great popularity in the Internet. Motivated by this success, community-awareness also has become a hot topic i...
The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocati...
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We consider in this paper fault-tolerant mixed-criticality scheduling, where heterogeneous safety guarantees must be provided to functionalities (tasks) of varying criticalities (im-portances). We model explicitly the...
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ISBN:
(纸本)9781479930173
We consider in this paper fault-tolerant mixed-criticality scheduling, where heterogeneous safety guarantees must be provided to functionalities (tasks) of varying criticalities (im-portances). We model explicitly the safety requirements for tasks of different criticalities according to safety standards, assuming hardware transient faults. We further provide analysis techniques to bound the effects of task killing and service degradation on the system safety and schedulability. Based on our model and analysis, we show that our problem can be converted to a conventional mixed-criticality schedul-ing problem. Thus, we broaden the scope of applicability of the conventional mixed-criticality scheduling techniques. Our proposed techniques are validated with a realistic flight management system application and extensive simulations. Copyright 2014 ACM.
Current peer-to-peer (P2P) systems often suffer from a large fraction of freeriders not contributing any resources to the network. Various mechanisms have been designed to overcome this problem. However, the selfish b...
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ISBN:
(纸本)1595933840
Current peer-to-peer (P2P) systems often suffer from a large fraction of freeriders not contributing any resources to the network. Various mechanisms have been designed to overcome this problem. However, the selfish behavior of peers has aspects which go beyond resource sharing. This paper studies the effects on the topology of a P2P network if peers selfishly select the peers to connect to. In our model, a peer exploits locality properties in order to minimixe the latency (or response times) of its lookup operations. At the same time, the peer aims at not having to maintain links to too many other peers in the system. By giving tight hounds on the price of anarchy, we show that the resulting topologies can be much worse than if peers collaborated. Moreover, the network may never stabilize, even in the absence of churn. Finally, we establish the complexity of Nash equilibria in our game theoretic model of P2P networks. Specifically, we prove thai it is NP-hard to decide whether our game has a Nash equilibrium and can stabilize. Copyright 2006 ACM.
Running each application of a many-core system on an isolated (virtual) guest machine is a widely considered solution for performance and reliability issues. When a new application is started, the guest machine is ass...
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End-to-end transport protocols perform poorly in mobile environments, primarily due to the frequent route breaks induced by node mobility. We present a framework for hop-by-hop transport protocols and propose a new re...
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Mathematical modeling for gene regulative networks (GRNs) provides an effective tool for hypothesis testing in biology. A necessary step in setting up such models is the estimation of model parameters, i.e., an optimi...
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ISBN:
(纸本)9781605583259
Mathematical modeling for gene regulative networks (GRNs) provides an effective tool for hypothesis testing in biology. A necessary step in setting up such models is the estimation of model parameters, i.e., an optimization process during which the difference between model output and given experimental data is minimized. This parameter estimation step is often difficult, especially for larger systems due to often incomplete quantitative data, the large size of the parameter space, and non-linearities in system behavior. Addressing the task of parameter estimation, we investigate the influence multiobjectivization can have on the optimization process. On the example of an established model for the segment polarity GRN in Drosophila, we test different multiobjectivization scenarios compared to a singleobjective function proposed earlier for the parameter optimization of the segment polarity network model. Since, instead of a single optimal parameter setting, a set of optimal parameter settings exists for this GRN, the comparison of the different optimization scenarios focuses on the capabilities of the different scenarios to identify optimal parameter settings showing good diversity in the parameter space. By embedding the objective functions in an evolutionary algorithm (EA), we show the superiority of the multiobjective approaches in exploring the model's parameter space. Copyright 2009 ACM.
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distribution of optimal solutions. However, struc...
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ISBN:
(纸本)9781450300728
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distribution of optimal solutions. However, structural characteristics in the decision space can also provide valuable insights. In certain applications, it may even be more important to find a structurally diverse set of close-to-optimal solutions than to identify a set of optimal but structurally similar solutions. Accordingly, multiobjective optimizers are required that are capable of considering both the objective space quality of a Pareto-set approximation and its diversity in the decision space. Although NSGA, one of the first multiobjective evolutionary algorithms, explicitly considered decision space diversity, only a few other studies address that issue. It therefore is an open research question how modern multiobjective evolutionary algorithms can be adapted to search for structurally diverse high-quality Pareto-set approximations. To this end we propose an approach to integrate decision space diversity into hypervolume-based multiobjective search. We present a modified hypervolume indicator and integrate it into an evolutionary algorithm. The proof-of-principle results show the potential of the approach and indicate further research directions for structure-oriented multiobjective search. Copyright 2010 ACM.
Nowadays, the reliability and performance of modern embedded multi-processor systems is threaten by the everincreasing power densities in integrated circuits, and a new additional goal of software synthesis is to redu...
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The tapered asymmetric directional coupler has the potential to realize high fabrication tolerance and high transmission efficiency on-chip mode multiplexer. However, the geometry parameter selection of tapered struct...
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The tapered asymmetric directional coupler has the potential to realize high fabrication tolerance and high transmission efficiency on-chip mode multiplexer. However, the geometry parameter selection of tapered structure remains empirical. In this paper, we propose a design method for the tapered structure based on genetic algorithm. Combined with the adjusted coupling equations and interpolation method, lowtime-cost optimization can be realized. Three mode multiplexers(TE0&TE1, TE0&TE2 and TE0&TE5)are designed by our method. According to simulation results, the insertion loss of the designed devices is lower than 1.8 dB and the crosstalk is lower than-15 dB when the fabrication error is within required range(±10 nm for TE0&TE2 and TE0&TE5, and ±20 nm for TE0&TE1) in the bandwidth of 1.5–1.6 μm. In addition, the entire optimization process takes only 2 h for each device, which is around the time cost of a single 3 D simulation.
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