An IoT Unified Access Platform for Heterogeneity Sensing Devices Based on Edge Computing

Abstract

With the rapid development of the Internet of Things (IoT), a large number of heterogeneous sensing devices are accessed in their proprietary ways to IoT applications, formed ''silos'' application mode. The growth of IoT applications has been hampered by this mode due to the barriers of resource sharing of heterogeneous sensing devices. This paper proposes an IoT access platform deployed at the network edge near the sensing devices. This architecture can enable more responsive IoT applications and provide efficient privacy protection for sensitive data. We propose a general ontology-based resource description model of IoT devices to provide a consistent view of heterogeneous sensing devices for IoT applications in the cloud. Based on this model, we propose an adaptive access method to provide unified access, control, and management of IoT devices with various intelligence levels. The access platform turns the ''silos'' application mode of IoT into a horizontal application mode, supports applications to share and reuse the resources of IoT devices. We demonstrate the efficacy of our architecture with an application case study that highlights our proposed resource description model and adaptive access method and evaluate performance improvement with experiments. INDEX TERMS Sensing devices access platform, Internet of Things, edge computing, resource description model, adaptive access method.

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

“…The exact point located concerning the affected spot on the sekai-ichi apple image region is estimated by make work for a particular IoT based Intelligent Agriculture. The experimental moments carry that the suggested model distinguishes a sensing functioning with an optimized-separation ratio is higher timevariant of the separation process [43,44].…”

Optimization of Resource Management for NFV-Enabled IoT Systems in Edge Cloud Computing

“…Several recent studies have been dedicated to resource management problems in edge cloud computing for IoT by investigating various critical problems. For instance, Lan et al propose an IoT access framework focused on edge computing that allows the exposure of massive devices and resource capacity as a single unified interface [2]. Xu et al propose a computation offloading method for dynamic task scheduling in an IoT system based on cloud edge computing to improve the completion time and save the energy consumption for mobile devices [5].…”

“…We aim at optimizing the cost of gateway deployment while satisfying a requirement of routing performance represented by a maximum number of relays from an end node to its gateway. Conditions (2) and (3) assure that link (i, j) belongs to path from s to d (i.e., y sd ij = 1) only if data generated by end node s is routed through IoT gateway d (i.e., z sd = 1) and link (i, j) exists (i.e., e ij = 1). Conditions (4) and (5) guarantee that data is routed from v to g only if v is an end node (i.e., x v = 0) and g is an IoT gateway (i.e., x g = 1).…”

“…Edge cloud computing and network function virtualization (NFV) technologies are potential approaches to improve resource use efficiency and highly flexible services in an IoT system by moving computing resources to the edge of networks close to IoT nodes [2]- [4]. Further, the adoption of NFV can provide a high degree of dynamic elasticity of IoT services due to the high versatility in the location and position of a particular service function composing an IoT service.…”

“…A detailed discussion of the literature on the use of NFV for IoT in edge cloud computing has been provided in Section II. As discussed in Section II, much of the existing work has investigated the integration of IoT and edge cloud computing [2], [4]- [10]. Some works have considered the performance of an IoT system based on NFV and edge cloud computing [3], [11].…”