定向社会物联网服务网络中基于邻域重叠的服务提供商优先排序方法

Nishit Narang, Subrat Kar
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引用次数: 1

摘要

社交物联网(Social IoT,或SIoT)是物联网的另一种架构模式,它涉及将社交行为属性赋予物联网设备。SIoT业务网络利用物联网设备(作为服务用户或服务提供商或两者)之间的社交协作,实现低延迟的协同服务和应用。在异构物联网设备的多供应商网络中实现SIoT服务网络的关键挑战是信任问题。问题在于以自主和独立的方式确定值得信赖的服务提供者的优先级和选择。在单一供应商的网络中,问题是通过专有方法来处理的,而这些方法不适用于多供应商的环境。在具有计算和存储资源受限的物联网设备的网络中,问题进一步复杂化。在本文中,我们建议使用邻里重叠来估计联系强度,并根据估计的联系强度确定服务提供商的优先级。我们使用三个公开可用的数据集验证邻域重叠和连接强度之间的关系。以往对邻域重叠及其与联系强度关系的研究主要集中在无向社交网络上,本文将邻域重叠的定义扩展到有向社交网络。我们在两个公开可用的定向社交网络数据集的帮助下进一步证明了这个扩展。本文提出的思想是基本的,可以扩展到为SIoT定义信任框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Neighborhood Overlap Based Approach for Service Provider Prioritization in a Directed Social IoT Service Network
Social IoT (or SIoT) is an alternate architectural pattern for IoT, which involves imparting social behavioral attributes to IoT devices. An SIoT service network uses social collaboration between IoT devices (acting as service users or service providers or both), enabling low-latency collaborative services and applications. A key challenge in implementing an SIoT service network in a multi-vendor network of heterogeneous IoT devices is the issue of Trust. The problem is in prioritization and selection of trustworthy service provider(s) in an autonomous and independent manner. In a single-vendor network, the problem is handled via proprietary methods that do not scale for multi-vendor environments. The problem is further compounded in networks having IoT devices that are constrained in computational and storage resources. In this paper, we propose the use of Neighborhood Overlap for estimating tie-strengths and the consequent prioritization of service providers based on the estimated tie-strength. We verify the relationship between neighborhood overlap and tie-strength using three publicly available datasets. While past research on neighborhood-overlap and its relationship with tie-strength focuses on undirected social networks only, we extend the definition of neighborhood-overlap for directed networks. We further prove this extension with the help of two publicly available directed social network datasets. The idea proposed in this paper is fundamental and can be extended towards defining a trust framework for SIoT.
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