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电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考|Constraint Based Methods

Kogekar et al. [8] presented an approach for constraint-guided software reconfiguration in sensor networks. They have implemented a system which relies on monitoring the system requirements expressed as formal constraints. Those constraints drive the reconfiguration process that takes place in a base station that can communicate to all the sensor nodes. They subsequently demonstrate their approach using simulation results from a simple one-dimensional tracking problem.

In a related article from Eames [9], a method called DesertFD (Design Space ExploRation Tool using Finite Domain constraints) is demonstrated for design space exploration based on constraint satisfaction problems. The authors specifically mention that the tool was initially produced for design-time configuration, but was later embedded in a runtime reconfiguration framework in order to do on-the-fly optimization. They combine design-time derived metadata from profiles, benchmarks and expert knowledge, with runtime information from monitoring instruments. The process is then periodically called, and evaluates and prunes the set of system configurations with the goal of selecting the proper configuration to deploy.

An example of a reconfiguration model based on constraint satisfaction programming is given by Syrjänen [10] who examined of software configuration management. A declarative rule-based formal language is proposed for representing configuration knowledge. A case study is shown for managing Debian GNU/Linux packages. The author states that finding a stable in any program in normal logic is NP-hard. In order to find a solution for the configuration problem a method is used to find stable models semantics for logic programs developed by Simons [11]. This method called smodels is an algorithm for solving a constrained design problem, and as the authors denote, it does have some overhead and even possibly more than comparable methods. However this overhead provides the designer with a more powerful language. Consequently, problems that can be more compactly represented by logic programs can be more quickly solved with smodels than with a satisfiability checker.

电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考|Logic Based Methods

A logic based reconfiguration method will rely on some type of logical reasoner to find a configuration that matches requirements in runtime. One example a first-order logic interpreter is Prolog [12]. Prolog uses backtracking methods and Selective Linear Definite clause resolution to find solutions $[13,14]$. This way of solving logic statements is proven to be both sound and complete [15]. Backtracking is the process of finding a solution by searching for partial solutions. For each candidate of a partial solution the validity is checked, if at one point no solutions exist for the last partial solution, a different one is searched for the previous one. This is analogous for finding solutions in a search tree, and looking depth-first for a solution that satisfies all sub statements.

Selective Linear Definite clause resolution is a method for checking statements by denoting them as disjunctive literals, and refuting all negated literals via the before mentioned backtracking method. SLD-resolution is very efficient both in terms of time and space. However, similar sub goals may be derived multiple times if the query contains recursive calls. Moreover, SLD-resolution is not guaranteed to always terminate [16].

In the SOSE project [17] a framework is described for reconfiguration at the heart of which lies a Prolog based reasoner. Using a relatively simple set of rules the authors can describe the reconfiguration strategies. The method is demonstrated for a greenhouse use case in which an optimal configuration needs to be employed for estimating the temperature distribution. Whereas in this case the goal of the system was purely state estimation, the framework was set up in a generic manner, so different applications are possible as well.

Isermann [18] already used a fuzzy logic controller for automatic supervision and fault diagnosis. He concluded that fuzzy logic provides a systematic framework to process vague variables and/or vague knowledge. As an example of this type of framework, Aubrun et al. [19] used fuzzy logic for monitoring and reconfiguring a power plant. They concluded that fuzzy logic provides better results for failure detection in terms of the robustness of the models comparing to classical methods. A freely available fuzzy logics reasoner called FuzzyDL [20] uses algorithms that comhine a tableaux algorithm and that of a MII .P-solver. It extends normal description logic with concepts of real values, integers, strings and definitions of fuzzy membership functions. It also allows for concepts in the knowledge base to be constrained using syntax which is comparable to constraint description. In a related article, the same authors propose a method for finding solutions using fuzzy logics from models described in OWL [21].

电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考|EECS262

电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考|Constraint Based Methods

Kogekar 等人。[8] 提出了一种在传感器网络中进行约束引导的软件重新配置的方法。他们实施了一个系统,该系统依赖于监控以形式约束表示的系统要求。这些约束推动了在可以与所有传感器节点通信的基站中进行的重新配置过程。随后,他们使用来自简单一维跟踪问题的模拟结果展示了他们的方法。

在 Eames [9] 的相关文章中,演示了一种名为 DesertFD(使用有限域约束的设计空间探索工具)的方法,用于基于约束满足问题的设计空间探索。作者特别提到该工具最初是为设计时配置而生产的,但后来被嵌入到运行时重新配置框架中以进行动态优化。它们将来自配置文件、基准和专家知识的设计时派生元数据与来自监控仪器的运行时信息相结合。然后定期调用该过程,并评估和修剪系统配置集,以选择要部署的正确配置。

Syrjänen [10] 给出了一个基于约束满足编程的重新配置模型的例子,他研究了软件配置管理。提出了一种基于声明性规则的形式语言来表示配置知识。展示了管理 Debian GNU/Linux 软件包的案例研究。作者指出,在正常逻辑中的任何程序中找到一个稳定是 NP 难的。为了找到配置问题的解决方案,一种方法被用来为 Simons [11] 开发的逻辑程序找到稳定的模型语义。这种称为 smodels 的方法是一种用于解决受限设计问题的算法,正如作者所指出的,它确实有一些开销,甚至可能比同类方法更多。然而,这种开销为设计人员提供了更强大的语言。最后,

电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考|Logic Based Methods

基于逻辑的重新配置方法将依赖某种类型的逻辑推理器在运行时找到匹配需求的配置。一阶逻辑解释器的一个例子是 Prolog [12]。Prolog 使用回溯方法和选择性线性定子句解析来寻找解决方案[13,14]. 这种解决逻辑语句的方法被证明是合理和完整的[15]。回溯是通过搜索部分解决方案来找到解决方案的过程。对于部分解决方案的每个候选者,都会检查有效性,如果在某一时刻对于最后一个部分解决方案不存在解决方案,则为前一个部分解决方案搜索不同的解决方案。这类似于在搜索树中寻找解决方案,并首先寻找满足所有子语句的解决方案。

选择性线性定子句解析是一种通过将语句表示为析取文字并通过前面提到的回溯方法驳斥所有否定文字来检查语句的方法。SLD 分辨率在时间和空间方面都非常有效。但是,如果查询包含递归调用,则可能会多次派生类似的子目标。此外,不能保证 SLD 解析总是终止 [16]。

在 SOSE 项目 [17] 中,描述了一个用于重新配置的框架,其核心是基于 Prolog 的推理器。作者可以使用一组相对简单的规则来描述重新配置策略。该方法针对温室用例进行了演示,其中需要采用最佳配置来估计温度分布。虽然在这种情况下,系统的目标是纯粹的状态估计,但框架是以通用方式设置的,因此不同的应用程序也是可能的。

Isermann [18] 已经使用模糊逻辑控制器进行自动监督和故障诊断。他得出结论,模糊逻辑为处理模糊变量和/或模糊知识提供了一个系统框架。作为这类框架的一个例子,Aubrun 等人。[19] 使用模糊逻辑来监控和重新配置发电厂。他们得出结论,与经典方法相比,模糊逻辑在模型的鲁棒性方面为故障检测提供了更好的结果。一个免费提供的模糊逻辑推理器,称为 FuzzyDL [20],使用结合了表格算法和 MII .P 求解器的算法。它用实数值、整数、字符串的概念和模糊隶属函数的定义扩展了正常的描述逻辑。它还允许使用类似于约束描述的语法来约束知识库中的概念。在一篇相关文章中,同一作者提出了一种使用 OWL [21] 中描述的模型中的模糊逻辑来寻找解决方案的方法。

电子工程代写|嵌入式网络系统代写Embedded Networked Systems代考

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