Developing an On-Demand Cloud-Based Sensing-as-a-Service System for Internet of Things

The increasing number of Internet of Things (IoT) devices with various sensors has resulted in a focus on Cloud-based sensing-as-a-service (CSaaS) as a new value-added service, for example, providing temperature-sensing data via a cloud computing system. However, the industry encounters various chal...

Full description

Saved in:
Bibliographic Details
Main Authors: Mihui Kim, Mihir Asthana, Siddhartha Bhargava, Kartik Krishnan Iyyer, Rohan Tangadpalliwar, Jerry Gao
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:Journal of Computer Networks and Communications
Online Access:http://dx.doi.org/10.1155/2016/3292783
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The increasing number of Internet of Things (IoT) devices with various sensors has resulted in a focus on Cloud-based sensing-as-a-service (CSaaS) as a new value-added service, for example, providing temperature-sensing data via a cloud computing system. However, the industry encounters various challenges in the dynamic provisioning of on-demand CSaaS on diverse sensor networks. We require a system that will provide users with standardized access to various sensor networks and a level of abstraction that hides the underlying complexity. In this study, we aim to develop a cloud-based solution to address the challenges mentioned earlier. Our solution, SenseCloud, includes a sensor virtualization mechanism that interfaces with diverse sensor networks, a multitenancy mechanism that grants multiple users access to virtualized sensor networks while sharing the same underlying infrastructure, and a dynamic provisioning mechanism to allow the users to leverage the vast pool of resources on demand and on a pay-per-use basis. We implement a prototype of SenseCloud by using real sensors and verify the feasibility of our system and its performance. SenseCloud bridges the gap between sensor providers and sensor data consumers who wish to utilize sensor data.
ISSN:2090-7141
2090-715X