Spatiotemporal Compressive Network Coding for Energy-Efficient Distributed Data Storage in Wireless Sensor Networks

Remote System for Oil Spill Detection Based on ZigBee and GIS

“…Wang [9] established the pollution level assessment model for oil spill on offshore platforms through the application of analytic hierarchy process into the discrimination on the contamination degree of offshore oil spill. In detail, the corresponding oil spill parameters were selected to construct the risk hierarchical structure of oil spill pollutions which determined the corresponding object layer, criterion layer and program layer, and defined the membership grade of each parameter, finally, set up the total sort table of risk level assessment for the oil spill contamination on oil platform of Bohai.…”

“…It is provided with many advantages like short-distance, low-complexity, lowpower, low-rate and low-cost. This wireless technique is built upon IEEE802.15.4 protocol; the 802.15.4 workgroup is responsible for the establishment of PHY layer and MAC layer protocol, and the application and exploitation above are taken charge of by Zigbee Alliance [9].…”

Distributed Data Storage Strategy in Wireless Sensor Networks

“…Although, these placement algorithms focus on connectivity, coverage, energy consumption, congestion control, storage capacity and other issues in WSNs, there is still one or more shortcomings in these algorithms, such as: poor application background, too strong assumption, poor scalability, higher degree of complexity on computing and communications and so on. In response to this situation, Gong [11] has conducted a wide range of investigation on placement problem in WSNs. Based on the weaknesses of wireless sensor networks, which are of poor transmission reliability, limited energy, limited storage and computing ability, the lack of placement algorithms for mobile sensor networks, he designed a set of placement algorithms for wireless sensor networks.…”

Compressive network coding for wireless sensor networks: Spatio-temporal coding and optimization design

“…A C C E P T E D M A N U S C R I P T 4 Gong et al [15] formulated the fourth category scheme where the spatial and temporal correlations are both considered and investigated as a unity. The NC scheme in [15] is a spatiotemporal compressive scheme for distributed data storage in WSNs.…”

“…The NC scheme in [15] is a spatiotemporal compressive scheme for distributed data storage in WSNs. This scheme can reduce the number of transmissions and receptions, but involves a high computational complexity in the reconstruction process.…”