Data management for the Internet of Things: Green directions

Abstract

The technology pertaining to connecting objects together in the Internet of Things is already the focus of intensive research efforts. However, the mechanisms managing and utilizing the resulting significant volume of data from these objects has yet to match the maturity of the technology itself. The traditional approach of migrating raw data to centralized points for data storage and analysis may incur debilitating communication and energy costs, which will negatively affect the environment in the future. In this paper, we will discuss the life cycle of data within the Internet of Things and survey the current research in the data management field for the In 1 ternet of Things. The discussion will focus on the research pertaining to the optimization of communication overhead and storage mechanisms as they have the most significant impact on energy consumption. We prove the need for further analysis and addressing of issues concerning "green" data management systems designs for the Internet of Things.

A Holistic Overview of Anticipatory Learning for the Internet of Moving Things: Research Challenges and Opportunities

“…Tsai, Chun-Wei, et al [99] give a brief review of data mining techniques for IoT systems. Figure 2 illustrates the state of the art research for context prediction using different analytical algorithms and a variety of data sources, while Table 2 below summarizes the approaches used for building a prediction model based on supervised and unsupervised prediction techniques [100][101][102]. Supervised techniques rely on labeled data and training to find a model that can afterwards be applied to a new dataset.…”

Data Mining Framework for IoT Applications

“…Ali et al [6] differentiated types of data from IoT into "data about things" and "data generated by things". Data about things refers to data that describe things themselves (e.g., state, location, identity, and so on) and data generated by things refers to data generated or captured by things.…”

Special requirements on ontology for customer support in Internet of Things

“…Example of event definitionAnalysis in[20] focuses on the problem, how can the large traffic of data between the objects and central repositories reduced to provide an acceptable response time. In the study[21] on Internet of Things architecture a chapter is devoted to the life cycle management problem.…”