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Hitch Hiker 2.0: a binding model with flexible data aggregation for the Internet-of-Things

Authors :
Ramachandran, Gowri Sankar
Proença, José
Daniels, Wilfried
Pickavet, Mario
Staessens, Dimitri
Huygens, Christophe
Joosen, Wouter
Hughes, Danny
Ramachandran, Gowri Sankar
Proença, José
Daniels, Wilfried
Pickavet, Mario
Staessens, Dimitri
Huygens, Christophe
Joosen, Wouter
Hughes, Danny
Source :
Journal of Internet Services and Applications
Publication Year :
2016

Abstract

Wireless communication plays a critical role in determining the lifetime of Internet-of-Things (IoT) systems. Data aggregation approaches have been widely used to enhance the performance of IoT applications. Such approaches reduce the number of packets that are transmitted by combining multiple packets into one transmission unit, thereby minimising energy consumption, collisions and congestion. However, current data aggregation schemes restrict developers to a specific network structure or cannot handle multi-hop data aggregation. In this paper, we propose Hitch Hiker 2.0, a component binding model that provides support for multi-hop data aggregation. Hitch Hiker uses component meta-data to discover remote component bindings and to construct a multi-hop overlay network within the free payload space of existing traffic flows. Hitch Hiker 2.0 provides end-to-end routing of low-priority traffic while using only a small fraction of the energy of standard communication. This paper extends upon our previous work by incorporating new mechanisms for decentralised route discovery and providing additional application case studies and evaluation. We have developed a prototype implementation of Hitch Hiker for the LooCI component model. Our evaluation shows that Hitch Hiker consumes minimal resources and that using Hitch Hiker to deliver low-priority traffic reduces energy consumption by up to 32 %.

Details

Database :
OAIster
Journal :
Journal of Internet Services and Applications
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.on1255563904
Document Type :
Electronic Resource