The Internet of Things (IoT) has brought to a significant growing of data produced, and therefore, new models and approaches are needed to investigate these "big data" in terms of volume, velocity and variability. IoT services can be considered a dynamic content, including data sources and middleware infrastructures. An effective solution to manage dynamic contents are Content Delivery Networks (CDNs), but, in dynamic and large systems as IoT environment, their limits emerge, therefore, decentralized approaches and algorithms have to be designed and employed. This paper proposes SmartFinder, a swarm based algorithm to build a CDN based discovery service in pervasive and dynamic environment as IoT. The CDN servers are represented with metadata obtained through a locality preserving hash function. A swarm of mobile agents move the metadata and, by applying of tailored probability functions, achieve a logical organization of the servers. The outcome is a sorted overlay network that allows content and services discovery operations faster. Experimental results show the effectiveness of the approach.
A Smart Discovery Service in Internet of Things Using Swarm Intelligence
Agostino Forestiero
2017
Abstract
The Internet of Things (IoT) has brought to a significant growing of data produced, and therefore, new models and approaches are needed to investigate these "big data" in terms of volume, velocity and variability. IoT services can be considered a dynamic content, including data sources and middleware infrastructures. An effective solution to manage dynamic contents are Content Delivery Networks (CDNs), but, in dynamic and large systems as IoT environment, their limits emerge, therefore, decentralized approaches and algorithms have to be designed and employed. This paper proposes SmartFinder, a swarm based algorithm to build a CDN based discovery service in pervasive and dynamic environment as IoT. The CDN servers are represented with metadata obtained through a locality preserving hash function. A swarm of mobile agents move the metadata and, by applying of tailored probability functions, achieve a logical organization of the servers. The outcome is a sorted overlay network that allows content and services discovery operations faster. Experimental results show the effectiveness of the approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.