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首页> 外文会议>Proceedings of the 2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORC Workshops 2010) >Locality-Aware Extension of pi-Calculus to Model Self-Organizing Behavior in Massively Distributed Embedded Systems
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Locality-Aware Extension of pi-Calculus to Model Self-Organizing Behavior in Massively Distributed Embedded Systems

机译：pi演算的局部性感知扩展，以对大规模分布式嵌入式系统中的自组织行为建模

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Massively Distributed Embedded Systems (MDES) such as Wireless Sensor Networks (WSN) are gaining increasing attention, since they enable a broad range of novel applications starting from monitoring oceans to exploring distant planets. WSNs consist of hundreds of nodes that have typically very limited recourses (computational, memory, energy, etc.) and are deployed in a dynamic environment, where they have to continuously adapt to new conditions. Due to the small-size requirement of the nodes, they are highly resource-constrained. Because of that, the amount of functionality that may be present in each node is limited. Therefore, cooperation between nodes is needed in order to accomplish complex tasks. These facts turn the design of applications for WSNs into a challenge. A promising approach how to deal with it is to use the emergent self-organization metaphor. In this paper a new process algebra (PA) called "Locality-aware extension of π-Calculus" is presented. The algebra is one of several techniques included in a new design methodology for the design of self-organizing behavior in MDES. The method is based on π-Calculus and allows a highlevel description of interactions among processes. As the most important characteristic of self-organization is the restriction of interactions to neighboring elements (localized interactions), we extend the π-Calculus with locality awareness, a necessary abstraction to allow the modeling of self-organization in MDES. To get full locality awareness in π-Calculus, we extended it with concepts for modeling spatiality, probability and time. Moreover, new types of channels are included to cover various types of communication such as distribution, broadcast and aggregation. In order to validate this new PA, we successfully model a self-organizing clustering algorithm for WSNs.
机译：诸如无线传感器网络（WSN）之类的大规模分布式嵌入式系统（MDES）受到越来越多的关注，因为它们可以实现从监视海洋到探索遥远星球的各种新颖应用。 WSN由数百个节点组成，这些节点通常具有非常有限的资源（计算，内存，能源等），并部署在动态环境中，在这些环境中它们必须不断适应新条件。由于节点的尺寸要求小，因此它们受到资源的高度限制。因此，每个节点中可能存在的功能数量受到限制。因此，需要节点之间的合作才能完成复杂的任务。这些事实使WSN的应用程序设计成为一个挑战。一个有前途的方法是使用新兴的自组织隐喻。在本文中，提出了一个新的过程代数（PA），称为“π演算的局部性扩展”。代数是MDES中用于自组织行为设计的新设计方法中包含的几种技术之一。该方法基于π演算，可以对进程之间的交互进行高级描述。由于自组织的最重要特征是与相邻元素的交互作用（局部相互作用）的限制，因此我们扩展了具有局部性意识的π演算，这是在MDES中进行自组织建模的必要抽象。为了在π演算中获得完整的位置意识，我们通过对空间，概率和时间进行建模的概念对其进行了扩展。而且，包括了新类型的信道以覆盖各种类型的通信，例如分发，广播和聚合。为了验证此新的PA，我们成功地为WSN建立了自组织聚类算法的模型。

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