| dc.identifier.uri | http://hdl.handle.net/11401/77441 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Energy constraint is one of the major constraints in the design and deployment of conventional wireless sensor networks. In such networks, usually powered by batteries with limited capacity, one or few number of static data sinks are deployed to collect sensory data from the network through multi-hop relay in non-uniform pattern. Such a methodology inevitably causes quick depletion of battery energy in the sensors which transmit large amount of data, e.g., the sensors around data sinks. This results in the formation of energy holes that may disconnect sensors from the networks, and even terminates the operation of the networks. Mobile data gathering provides a reasonable approach to alleviate this problem as one or more mobile data collectors roam over the sensing field and work as data sinks to collect data from surrounding sensors By virtually increasing the number of data sinks and careful calculate their locations in the networks, the length of relays are shortened and the amount of data being transmitted are greatly decreased, thus energy can be significantly saved in sensors. In the meanwhile, energy harvesting techniques have been applied in wireless sensor networks to supply the sensors with the energy obtained from ambient environment. Recent breakthrough in wireless power transfer based on inductance resonance emerges as a promising method to relieve energy limitation in wireless sensor networks. As mobile energy transporters are employed for energy injection into the networks, the sensors are provided with sustained energy through wireless recharge charging, and perpetual network operation can be achieved. This dissertation focuses on scheme design and performance optimization of mobile data gathering and energy replenishment, and experimental evaluation in WSNs. We present a joint design of mobile data gathering and energy replenishment to maximize the network utility in wireless sensor networks. We develop an efficient NDN-based protocol to collect real-time battery information from the network so that the trajectories of mobile data collectors or energy transporters as well as routing scheme for the sensory data can be carefully calculated based on the energy distribution. We studies energy neutral problem and designed algorithms for recharge scheduling of the sensors based on their energy situation to achieve perpetual network operation. We propose a mobility assisted data gathering scheme with solar irradiance awareness which utilizes data sinks with limited mobility in solar-powered sensor networks to maximize the amount of sensory data that can be collected from the network. We also design a versatile platform for experimental research on mobile data gathering in wireless sensor networks. Our testbed includes both wireless sensor node and mobile data collector on which algorithms and protocols can run in real world. Compared with mathematical analysis and software simulation, which may neglect the impact of many real factors due to the limitation of the models and present inaccurate results of performance evaluation. Our testbed provides a more convincing method for performance evaluation by, instead of modeling the real world, running the algorithms and protocols in the same environment the application will be deployed. It also offers the assistance of deep insight for system modeling, which could help the development of better solutions. We implement mobile data gathering on our testbed and conduct experiment for wildlife surveillance. It successfully captures the impact of many real factors which are usually omitted in theoretical analysis and software simulation due to the limitation of the models. | |
| dcterms.available | 2017-09-20T16:52:42Z | |
| dcterms.contributor | Donetski, Dmitri | en_US |
| dcterms.contributor | Yang, Yuanyuan | en_US |
| dcterms.contributor | Hong, Sangjin | en_US |
| dcterms.contributor | Das, Samir R | en_US |
| dcterms.contributor | . | en_US |
| dcterms.creator | Li, Ji | |
| dcterms.dateAccepted | 2017-09-20T16:52:42Z | |
| dcterms.dateSubmitted | 2017-09-20T16:52:42Z | |
| dcterms.description | Department of Electrical Engineering | en_US |
| dcterms.extent | 170 pg. | en_US |
| dcterms.format | Application/PDF | en_US |
| dcterms.format | Monograph | |
| dcterms.identifier | http://hdl.handle.net/11401/77441 | |
| dcterms.issued | 2017-05-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:52:42Z (GMT). No. of bitstreams: 1
Li_grad.sunysb_0771E_13274.pdf: 6536757 bytes, checksum: dd854e02521fec165398d6a0d5b70f6c (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Electrical engineering | |
| dcterms.subject | energy harvesting, mobile data gathering, wireless recharge, wireless sensor networks | |
| dcterms.title | Mobile Data Gathering and Energy Replenishment inWireless Sensor Networks: Theoretical and Experimental Approaches | |
| dcterms.type | Dissertation | |
