A novel multimedia device ability matching technique for ubiquitous computing environments

Abstract

In wireless multimedia sensor networks (WMSNs), wirelessly interconnected devices are able to ubiquitously retrieve multimedia contents such as video and audio streams from the environment. However, since WMSN applications are large-scale, dynamic and highly concurrent, how to achieve both effective multimedia device resource management and collaborative task scheduling simultaneously becomes a serious problem. In this paper, using the hierarchical modeling technique, we first propose a device ability model including spatial information. In order to solve the problem of insufficient capacity of single devices, we then give a composite device ability model and relevant calculation formulae. Next, we introduce a novel device resource matching technique based on the proposed model. Compared with previous works, experimental results show that our technique achieves better recall and precision and meets WMSN application needs more effectively. Furthermore, our proposed approach greatly reduces the design complexity as well as the workload of application designers.

A Survey on New Approaches of Internet of Things Data Mining

“…Support Vector Machines calculation is run learning model with connected learning calculations that dissect data and perceive designs that is in light of measurable learning hypothesis [14]. SVM produces a parallel classifier the alleged ideal analytic hyper planes through associate astonishingly nonlinear mapping of the knowledge vectors into the high-dimensional highlight house.…”

Data Mining for the Internet of Things: Literature Review and Challenges

“…However, no previous effort has been made to review the different views of data mining in a systematic way, especially in nowadays big data [5][6][7]; mobile internet and Internet of Things [8][9][10] grow rapidly and some data mining researchers shift their attention from data mining to big data. There are lots of data that can be mined, for example, database data (relational database, NoSQL database), data warehouse, data stream, spatiotemporal, time series, sequence, text and web, multimedia [11], graphs, the World Wide Web, Internet of Things data [12][13][14], and legacy system log. Motivated by this, in this paper, we attempt to make a comprehensive survey of the important recent developments of data mining research.…”