A hyper elliptic curve crypto architecture for execution of authentication protocols under hard real time constraints is proposed in this contribution. Tailoring the architecture of the computation platform to the cha...
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A hyper elliptic curve crypto architecture for execution of authentication protocols under hard real time constraints is proposed in this contribution. Tailoring the architecture of the computation platform to the characteristics of the underlying cryptographic protocol enables for short authentication times, minimal hardware usage, while providing a higher level of security compared to today's standard cryptosystems. Due to the low hardware footprint it is ideally suited for integration into embedded systems with limited resources such as electronic control units in automobiles. All cryptographic functionality is strictly bound to an internal processing module thus hiding the complexity of the HECC operations. Automotive access control systems is am example of an application area that can be matched perfectly by the proposed architecture. Experiments show that a massive speed up can be achieved which can be exploited to save power or introduce additional security measures on algorithmic level.
Nowadays, energy saving has become one of the most critical issues in IT. In this paper, we propose an energy-efficient method, message classifying and voltage control (MCVC), for scheduling inter-processor communicat...
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Nowadays, energy saving has become one of the most critical issues in IT. In this paper, we propose an energy-efficient method, message classifying and voltage control (MCVC), for scheduling inter-processor communications on multi-core processors. The proposed technique has two new elements in scheduling and energy saving technologies. Firstly, the MCVC suggests a contention-free scheduling method that considers network transmission latency to avoid synchronization delay. For energy saving, according to message sizes, the MCVC suggests different voltage level for dynamically adjusting CPU speed to reduce energy consumption of idle processors. The simulation results show that MCVC has noticeable improvements on communication cost and energy usage.
The well-known drawbacks of lock-based programming have forced researchers to explore new alternatives for parallel programming of which Transactional memory (TM) is a promising one. TM has been shown to scale well in...
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The well-known drawbacks of lock-based programming have forced researchers to explore new alternatives for parallel programming of which Transactional memory (TM) is a promising one. TM has been shown to scale well in multi-core processors when applications have data access patterns with a few conflicts. In contrast, if conflicts happen frequently in programs TM results in poor performance. In this paper, we introduce speculative contention avoidance (SCA) to prevent conflicts in TMs. SCA dynamically controls number of concurrently executing transactions and serializes those transactions that are likely to conflict. This technique is built on the concept of contention locality, which describes the likelihood that a previously aborted transaction fails again in the future. We find that contentions are highly predictable in TMs and exploit simple predictors which rely on history of transactions to speculate contentions. We have incorporated SCA into TL2 and compared the performance of the new implementation with the original STM using Stamp v0.9.7 benchmark suite. Our results show that SCA is highly effective at preventing contentions and significantly improves performance.
Demands for interoperability are getting increased since there are a lot of products available to provide the same functionality which have raised some heterogeneous issues. Various middleware technologies are often u...
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Demands for interoperability are getting increased since there are a lot of products available to provide the same functionality which have raised some heterogeneous issues. Various middleware technologies are often used as the communication infrastructure for distributed system to ensure the interoperability. However, different types of middleware have cause interoperability issues as well. One of the middleware architectures used for heterogeneous systems is MOM. Message Oriented Middleware (MOM) is known as common glue technology for heterogeneous, distributed and loosely coupled software system. In this paper we explore and analyze studies related to distributed communication using MOM architecture. We found that there are some weaknesses for MOM such as limited ability to link complex application, losing the trace of execution and low level of autonomous. To overcome these weaknesses, some researches have been done to extend MOM architecture. Most of these efforts are addressing one or two of the MOM limitations and not the general requirement of cross-platform communication such 24 by 7 environment, autonomous level, failure recovery and guaranteed transmission. In the end, we have proposed conceptual framework which is agent-based MOM for interoperability cross-platform communication of SOA system.
High Performance Computing (HPC) system utilization can be maximized and sustained if one understands the failure behavior. In general, Time to Failure (TTF) of HPC systems has been long studied and showed that the We...
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High Performance Computing (HPC) system utilization can be maximized and sustained if one understands the failure behavior. In general, Time to Failure (TTF) of HPC systems has been long studied and showed that the Wei bull distribution gives the best fit. In addition, in many cases, TTF of such systems exhibit correlations. In our previous study, we developed a reliability model of an HPC system where failures among nodes are independent. However, some studies have clearly shown that in some cases nodes do not fail independently of one another. Therefore, it is of importance to develop a reliability model for an HPC system based on the occurrence of simultaneous failures. In this paper, we develop such a model and derive expressions for the probability density function of time to failure, system reliability, system failure rate, and mean time to failure (MTTF). Results show that if the failure of the components (nodes) in the system possesses a degree of dependency, the system reliability decreases.
The use of nuclear energy to generate electric power is crucial in meeting the high energy demand of modern economy. The dependability analysis of nuclear power plants has been a critical issue and the reactor contain...
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The use of nuclear energy to generate electric power is crucial in meeting the high energy demand of modern economy. The dependability analysis of nuclear power plants has been a critical issue and the reactor containment is the most important safety structure acting as a barrier against the release of radioactive material to the environment. In this paper, we analyze the dependability of the reactor containment. We also propose a tool for design, implementation, and V&V to enhance the dependability of reactor containment through an integrated leakage rate test. Our practical experiences in the on-site tests are also discussed.
Most statistical software packages implement a broad range of techniques but do so in an ad hoc fashion, leaving users who do not have a broad knowledge of statistics at a disadvantage since they may not understand al...
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Most statistical software packages implement a broad range of techniques but do so in an ad hoc fashion, leaving users who do not have a broad knowledge of statistics at a disadvantage since they may not understand all the implications of a given analysis or how to test the validity of results. These packages are also largely serial in nature, or target multicore architectures instead of distributed-memory systems, or provide only a small number of statistics in parallel. This paper surveys a collection of parallel implementations of statistics algorithm developed as part of a common framework over the last 3 years. The framework strategically groups modeling techniques with associated verification and validation techniques to make the underlying assumptions of the statistics more clear. Furthermore it employs a design pattern specifically targeted for distributed-memory parallelism, where architectural advances in large-scale high-performance computing have been focused. Moment-based statistics (which include descriptive, correlative, and multicorrelative statistics, principal component analysis (PCA), and k-means statistics) scale nearly linearly with the data set size and number of processes. Entropy-based statistics (which include order and contingency statistics) do not scale well when the data in question is continuous or quasi-diffuse but do scale well when the data is discrete and compact. We confirm and extend our earlier results by now establishing near-optimal scalability with up to 10,000 processes.
Formal methods are mathematically-based techniques for specifying, developing and verifying a component or system, in order to increase the confidence regarding to the reliability and robustness of the target. Formal ...
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Formal methods are mathematically-based techniques for specifying, developing and verifying a component or system, in order to increase the confidence regarding to the reliability and robustness of the target. Formal methods can be used at different levels with different techniques, and one approach is to use model-oriented formal languages such as VDM languages in writing specifications. During model development, we can test executable specifications in VDM-SL and VDM++. In a lightweight formal approach, we test formal specifications to increase our confidence as we do in implementing software codes with conventional programming languages. While the specific level of rigor depends on the aim of the project, millions of tests may be conducted in developing highly reliable mission-critical software in a light-weight formal approach. In this paper, we introduce our approach to supporting large volume of testing for executable formal specifications using Hadoop, an implementation of MapReduce programming model. We are able to automatically distribute interpretation of specifications in VDM languages by using Hadoop. We also apply a property-based data-driven testing tool, Quick Check, over MapReduce so that specification can be checked with thousands of tests by using formally described pre/post conditions and invariant functions. As an advanced property-based data-driven testing approach, we also discuss model-based testing. We observed scalable performance in testing large amount of data for executable specifications in our approaches.
Through the introduction of SOA(Service Oriented Architecture), enterprises have recently had the benefit of legacy software reuse, heterogeneous environment integration, and ROI(Return On Investment) maximization. SO...
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Through the introduction of SOA(Service Oriented Architecture), enterprises have recently had the benefit of legacy software reuse, heterogeneous environment integration, and ROI(Return On Investment) maximization. SOA consists of a service client, service provider, and service registry. Within this environment, we proposed a service with variability on the basis of a product line concept. Services with variability are generalized services that have similar domain functions, however, they differ in their applications. They require a variability management mechanism with registry and discovery capability for proper registry and use in an SOA interaction model. In this paper, we propose and design an approach for registering and discovering a service with variability based on a 2-level UDDI for reusing a service with variability as a service. First-level registry and discovery consist of registering a service with variability, searching for a service with variability, and deciding the variability of the service with variability. Second-level registry and discovery consist of the registry and discovery of this customized service. Using this approach, a mechanism of reusability management is established through which a service with variability can be realized within the SOA concept.
Planning of distributed energy systems is a challenging task, involving a lot of technical, economic, environmental and political factors. In this study, an optimization model based decision support system and relevan...
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Planning of distributed energy systems is a challenging task, involving a lot of technical, economic, environmental and political factors. In this study, an optimization model based decision support system and relevant software package have been developed to provide comprehensive analysis of economic, eneigetic and environmental issues within a distributed energy system framework. The optimization problem is formulated as a mixed integer linear programming (MILP) model with an objective to minimize overall cost of the distributed energy system including both investment and running ones. The branch and bound (B&B) algorithm in combination with the simplex one has been employed to solve the model. By enduing a user-friendly interface, the system can be easily used without the necessity to understand special expertise and knowledge on energy system planning and decision analysis. In addition, besides the distributed energy system planning, it can be also employed for examining and visualizing effects of local energy and environmental policies, regional development policies, as well as climate change policies within a local framework.
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