A Study to Optimize Heterogeneous Resources for Open IoT

TL;DR

This paper proposes three-layer optimization techniques for Tacit Computing in Open IoT to reduce operational costs and enhance performance by dynamically allocating functions across device, network, and cloud layers.

Contribution

It introduces a novel three-layer optimization framework for Tacit Computing, enabling efficient resource management in heterogeneous Open IoT environments.

Findings

Optimized function offloading reduces operation costs.

Performance improvements achieved through layered resource allocation.

Enhanced continuity of IoT services with dynamic device discovery.

Abstract

Recently, IoT technologies have been progressed, and many sensors and actuators are connected to networks. Previously, IoT services were developed by vertical integration style. But now Open IoT concept has attracted attentions which achieves various IoT services by integrating horizontal separated devices and services. For Open IoT era, we have proposed the Tacit Computing technology to discover the devices with necessary data for users on demand and use them dynamically. We also implemented elemental technologies of Tacit Computing. In this paper, we propose three layers optimizations to reduce operation cost and improve performance of Tacit computing service, in order to make as a continuous service of discovered devices by Tacit Computing. In optimization process, appropriate function allocation or offloading specific functions are calculated on device, network and cloud layer before full-scale operation. Y. Yamato, N. Hoshikawa, H. Noguchi, T. Demizu and M. Kataoka, "A Study to Optimize Heterogeneous Resources for Open IoT," The Fifth International Symposium on Computing and Networking (CANDAR 2017), pp.609-611, DOI: 10.1109/CANDAR.2017.16, Nov. 2017. "(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."