DocumentCode
3588949
Title
Resource Management in Media Cloud of Things
Author
Aazam, Mohammad ; Eui-Nam Huh
Author_Institution
Dept. of Comput. Eng., Kyung Hee Univ., Suwon, South Korea
fYear
2014
Firstpage
361
Lastpage
367
Abstract
With the rapid increase in multimedia content on the Internet, media cloud is gaining importance. Media cloud provides ubiquitous access to the digital media content. It helps manage resources and advertise services more effectively. Since cloud computing provides ubiquitous access, it can receive data from any devices that has the capability to connect to it. Specially, with increasing Internet of Things (IoT) services, any object/thing can generate data. In case of Visual Sensor Network and Closed Circuit Television (CCTV) connected to cloud, a lot of multimedia data is sent to the cloud. The amalgamation of IoT with cloud computing creates Cloud of Things. With increasing heterogeneous and multimedia based IoT applications, a lot of data is being generated. This consumes a lot of network bandwidth as well as resources of the cloud, which have to be managed effectively for load balancing, fair share, and efficient utilization. In this study, we present a resource management model of Cloud of Things keeping in view resource prediction, allocation, advanced reservation, pricing, and refunding. We implemented and evaluated our model using CloudSim toolkit. The results and discussion justify and validate our model´s performance.
Keywords
Internet of Things; cloud computing; multimedia computing; resource allocation; CCTV; CloudSim toolkit; Internet of Things; IoT services; closed circuit television; cloud computing; digital media content; load balancing; media cloud of things; multimedia based IoT applications; multimedia content; multimedia data; network bandwidth; resource allocation; resource management; resource prediction; ubiquitous access; visual sensor network; Cloud computing; Media; Multimedia communication; Peer-to-peer computing; Pricing; Resource management; Cloud of Things; Internet of Things; media cloud;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Processing Workshops (ICCPW), 2014 43rd International Conference on
ISSN
1530-2016
Type
conf
DOI
10.1109/ICPPW.2014.54
Filename
7103472
Link To Document