A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing...

Area of Science:

• Computer Science
• Electrical Engineering
• Mobile Computing

Background:

• Periodic sensing in Internet of Things (IoT) systems leads to energy waste from redundant data transmission.
• Mobile cloud computing applications require efficient sensing strategies to manage resources.

Purpose of the Study:

• To propose and evaluate a location-based interactive model for IoT and cloud integration.
• To compare the energy efficiency and network lifetime of the proposed model against a periodic sensing model.

Main Methods:

• Developed a location-based interactive IoT-cloud model for mobile cloud computing.
• Utilized cloud as a coordinator for on-demand sensing services based on user interest and location.
• Implemented sensor scheduling controlled by the cloud to activate sensors only when needed.

Main Results:

• The location-based model demonstrates significant energy savings by deactivating sensors when there is no demand.
• Experimental results show a substantial improvement in network lifetime compared to the traditional periodic sensing model.
• On-demand sensing services based on user location and interest optimize resource utilization.

Conclusions:

• The proposed location-based interactive IoT-cloud model offers a more energy-efficient approach for mobile cloud computing.
• This model effectively reduces energy consumption and extends the operational lifespan of IoT networks.
• On-demand, location-aware sensing is a key strategy for sustainable mobile cloud applications.