Nature-Inspired Interference Management in Smart Peer Groups
Nature-Inspired Interference Management in Smart Peer Groups
复制标题
智能对等群体中受自然启发的干扰管理
DOI：
10.1109/ie.2014.27
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
C. Becker
中科院分区：
文献类型：
--
作者：
F. Roth;Christian Krupitzer;Sebastian VanSyckel;C. Becker
智能环境中的应用程序具有上下文感知和上下文更改功能，以支持用户的日常任务。在共享上下文的多用户环境中，可能会发生干扰。干扰是应用程序引起的上下文，它迫使其他应用程序做出反应。在COMITY项目中，我们开发了干扰检测和分辨率算法。但是，特别是基于约束满足的分辨率算法计算量很大。它需要一个成熟的机器来实现适合交互系统的运行时。在自发形成的智能对等群体中，没有这样的基础设施。在本文中，我们提出了一种检测和解决智能对等组干扰的方法。这种方法的灵感来自于自然界的两种协调机制。我们将干扰检测和解决问题映射到群集机制的规则中，展示了如何实现基于群集的干扰管理，并提出了基于局部抑制的智能对等体领导选举，以选举协调实体。最后，我们通过评估我们的原型来证明我们的方法的可行性。
Applications in intelligent environments are context-aware and context-altering in order to support users in their everyday tasks. In multi-user environments with shared context, interferences are likely to occur. An interference is an application-induced context that forces other applications to react. In our COMITY project, we developed interference detection and resolution algorithms. However, especially the constraint satisfaction-based resolution algorithm is computationally expensive. It requires a full-fledged machine in order to achieve runtimes suitable for interactive systems. In spontaneously formed smart peer groups, such infrastructure is not given. In this paper, we present an approach for detecting and resolving interferences in smart peer groups. The approach is inspired by two coordination mechanisms from nature. We map the problems of interference detection and resolution to the rules of the flocking mechanism, show how to implement a flocking-based interference management, and present a local inhibition-based leader election for smart peer groups in order to elect the coordinating entity. Finally, we show the feasibility of our approach by evaluating our prototype.