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

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.
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https://hal-univ-pau.archives-ouvertes.fr/hal-03434528
Contributor : Richard Chbeir Connect in order to contact the contributor
Submitted on : Thursday, November 18, 2021 - 12:28:17 PM
Last modification on : Friday, November 19, 2021 - 3:45:48 AM

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

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