2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2011)
Aug. 30, 2011 to Sept. 2, 2011
M. Baktashmotlagh , Sch. of ITEE, Univ. of Queensland, Brisbane, QLD, Australia
A. Bigdeli , Sch. of ITEE, Univ. of Queensland, Brisbane, QLD, Australia
B. C. Lovell , Sch. of ITEE, Univ. of Queensland, Brisbane, QLD, Australia
Today's work in the sensor networks community focuses on collecting and processing data from specific networks with associated base stations. One of the most important requirements in these networks is minimizing resource usage such as processing power and storage size on sensor nodes. Resource constraints in the sensor nodes can be divided into four categories: energy, communication, storage and computational power. In this paper, we present an efficient deployment of sensors with possibility of accessing most recent data through information obtained from ERP (enterprise resource planning) systems' re-configuration models. In this scheme the probability of losing any precious data or events would be minimized. In other words, our main focus in this paper is using ERP or high level distributed decision making systems' processed data or prediction models to reduce resource usage needed on sensor nodes. In the area of integration of sensors and ERPs or distributed decision making systems, very little work has been reported. However, those reported in the literature, mostly address relaying data from sensors to ERPs and tend to largely ignore issues that come with sensor resource constraints. Also they don't make use of the information processed and generated by ERPs in the cloud environment to optimize power consumption and transmission frequency of sensors, which is our aim.
power consumption, dynamic resource aware sensor networks, sensor cloud, ERP, enterprise resource planning, reconfiguration models, probability, cloud environment
M. Baktashmotlagh, B. C. Lovell and A. Bigdeli, "Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs," 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Klagenfurt, 2011, pp. 455-460.