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Journal Articles Sensors Year : 2021

Location-Aware Resource Discovery and QoR-Driven Resource Selection for Hybrid Web Environments

, (1) ,
1
Lara Kallab
  • Function : Author
Michael Mrissa

Abstract

In the Web of Things (WoT) context, an increasing number of stationary and mobile objects provide functions as RESTful services, also called resources, that can be combined with other existing Web resources, to create value-added processes. However, nowadays resource discovery and selection are challenging, due to (1) the growing number of resources providing similar functions, making Quality of Resource (QoR) essential to select appropriate resources, (2) the transient nature of resource availability due to sporadic connectivity, and (3) the location changes of mobile objects in time. In this paper, we first present a location-aware resource discovery that relies on a 3-dimensional indexing schema, which considers object location for resource identification. Then, we present a QoR-driven resource selection approach that uses a Selection Strategy Adaptor (SSA) to form i-compositions (with i ∈N*) offering different implementation alternatives. The defined SSA allows forming resource compositions while considering QoR constraints and Inputs/Outputs matching of related resources, as well as resource availability and users different needs (e.g., optimal and optimistic compositions obtained using a scoring system). Analyses are made to evaluate our service quality model against existing ones, and experiments are conducted in different environments setups to study the performance of our solution.

Dates and versions

hal-03434528 , version 1 (18-11-2021)

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Cite

Lara Kallab, Richard Chbeir, Michael Mrissa. Location-Aware Resource Discovery and QoR-Driven Resource Selection for Hybrid Web Environments. Sensors, 2021, 21 (20), pp.6835. ⟨10.3390/s21206835⟩. ⟨hal-03434528⟩

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