Bio-inspired monitoring of pervasive environments

A. Malatras, F. Peng, B. Hirsbrunner
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Abstract

Successful deployment of the pervasive computing paradigm is based on the exploitation of the multitude of participating devices and associated data. It becomes therefore evident that there is a necessity to provide optimal resource discovery mechanisms, the effectiveness of which will constitute the foundation for the efficient operation of pervasive computing environments. To mitigate the drawbacks brought by the inherent nature of pervasive environments, i.e. dynamicity, heterogeneity and scalability of the network infrastructure, we propose to employ P2P overlay networks that lead to more manageable topologies and optimize resource monitoring by scaling down the degree of complexity. In particular, we take advantage of bio-inspired self-organization mechanisms to construct reliable P2P overlays and thus provide more robust and adaptive monitoring solutions. High-level policy-based management operations driven by monitored context information enable a further level of runtime adaptation and optimization, subject to the overall application requirements. We report here on our ongoing work in this research area.
对无处不在的环境进行仿生监测
普及计算范式的成功部署是基于对大量参与设备和相关数据的利用。因此,很明显,有必要提供最优的资源发现机制,其有效性将构成普适计算环境高效运行的基础。为了减轻普适环境固有的缺点,即网络基础设施的动态性、异质性和可扩展性,我们建议采用P2P覆盖网络,从而产生更易于管理的拓扑结构,并通过降低复杂性来优化资源监控。特别是,我们利用生物启发的自组织机制来构建可靠的P2P覆盖,从而提供更健壮和自适应的监测解决方案。受监视的上下文信息驱动的基于策略的高级管理操作支持进一步的运行时适应和优化,以满足总体应用程序需求。我们在这里报告我们在这个研究领域正在进行的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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