An Edge-Centric Ensemble Scheme for Queries Assignment

Kolomvatsos, K. and Anagnostopoulos, C. (2018) An Edge-Centric Ensemble Scheme for Queries Assignment. In: 8th International Workshop on Combinations of Intelligent Methods and Applications in conjunction with the 30th International Conference on Tools with Artificial Intelligence (ICTAI 2018), Volos, Greece, 5-7 Nov 2018,

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Publisher's URL: http://ceur-ws.org/Vol-2252/paper1.pdf

Abstract

The new era of the Internet of Things (IoT) reveals new potentials for the management of numerous devices. Such devices produce data streams that are guided to the Cloud for further processing. However, any processing in the Cloud, even if it is supported by increased computational resources, suffers from increased latency. For minimizing the latency we can perform data processing at the edge of the network, i.e., at the edge nodes. The aim is to provide analytics and build knowledge on top of the collected data in the minimum time. In this paper, we deal with the problem of allocating queries, defined for producing knowledge, to a number of edge nodes. The aim is to further reduce the latency by allocating queries to nodes that exhibit low load (the current and the estimated), thus, they can provide the final response in the minimum time. However, before the allocation, we should decide the computational burden that a query will add. The allocation is concluded by the assistance of an ensemble similarity scheme responsible to deliver the complexity class for each query. The complexity class, thus, can be matched against the current load of every edge node. We discuss our scheme and through a large set of simulations and the adoption of benchmarking queries, we reveal the potentials of the proposed model supported by numerical results.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos and Kolomvatsos, Dr Kostas
Authors: Kolomvatsos, K., and Anagnostopoulos, C.
College/School:College of Science and Engineering > School of Computing Science
ISSN:1613-0073
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