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Improving sensor-cloud : energy efficiency, security, sensory data transmission, and quality of service

University of British Columbia

Recently, induced by incorporating 1) the ubiquitous data gathering capabilities of wireless sensor networks (WSNs) as well as 2) the powerful data storage and data processing abilities of cloud computing (CC), Sensor-Cloud is attracting growing attention from both academia and industry. However, Sensor-Cloud is still in its infancy and a lot of research efforts are expected to emerge in this area. Improving Sensor-Cloud, this thesis first presents the important research issues that are yet to be widely investigated by other researchers regarding the energy efficiency, security, sensory data transmission and quality of service (QoS) of Sensor-Cloud, respectively. Further, our accomplished work regarding solving the identified research issues is described. Particularly, two collaborative location-based sleep scheduling (CLSS) schemes are designed. Based on the locations of mobile users, CLSS dynamically determines the awake or asleep status of each sensor node to reduce energy consumption of the WSN integrated with mobile cloud. An authenticated trust and reputation calculation and management (ATRCM) system is introduced. ATRCM considers i) the authenticity of cloud service provider (CSP) and sensor network provider (SNP); ii) the attribute requirement of cloud service user (CSU) and CSP; iii) the cost, trust, and reputation of the service of CSP and SNP. A mechanism named TPSS is shown. TPSS consists of two main parts: 1) time and priority-based selective data transmission (TPSDT) for WSN gateway to selectively transmit sensory data to the cloud and 2) priority-based sleep scheduling (PSS) algorithm for WSN to save energy consumption. Trust-Assisted Sensor-Cloud (TASC) is exhibited. In TASC, the sensory data is gathered and transmitted to cloud, by the trusted sensors (i.e., sensors which own trust values surpassing a threshold) in WSN. The sensory data is stored, processed and on demand delivered to users, by the trusted data centers (i.e., data centers which own trust values surpassing a threshold) in cloud. The analytical and experimental results conducted in our work show that the proposed approaches can effectively alleviate the corresponding research issues, respectively. We hope our work can attract more research into Sensor-Cloud to make it develop faster and better.

Text

2016-06-29

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/58352

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/