A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation

Abstract

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

Nanosystems, Edge Computing, and the Next Generation Computing Systems

“…Similarly, traffic lights augmented with hyperspectral imaging and chem-bio sensors can be made locally smart when combined with weather sensors and the unique local population and infrastructure signatures. More concrete EC applications include scalable framework for early fire detection [99], disaster management services [100], accelerometers for structural health monitoring [101], micro-seismic monitoring platform for hydraulic fracture [102], a framework for searchable personal health records [75,76,103], smart health monitoring [76,104] and healthcare framework [105], improved multimedia traffic [106], a field-programmable gate array (FPGA)-based system for cyber-physical systems [107] and for space applications [108], biomedical wearables for IoMT [73,76,109], air pollution monitoring systems [110], precision agriculture [111,112], diabetes [74] and ECG [109] devices, and marine sensor networks [113].…”

“…In the general case of a composite nanostructured material domain, such as a quantum well [138] of a given morphology or a gap-plasmonic structure [139,140], the ensuing quantum confinement furnishes a variety of enabling mechanisms [141,142,143] via tunneling, modification of local density of states, frustrated total internal reflection, mode coupling, etc. It is envisioned that the opportunities offered by fields, such as advanced nanophotonics [40,42,144,145], nanomaterials [47], and smart sensors, will be capitalized by EC to advance IoT and other network-based applications [113]. Nanosystems, such as nanophotonic crystal cavities, quantum dots, carbon nanotubes (CNT), and nanomaterials, and their composites allow information processing.…”

The Sea Route Planning for Survey Vessel Intelligently Navigating to the Survey Lines

“…In the age of digital measurement, 3S (GNSS, GIS [3,4], RS [5,6]) technology is representative. The new technology not only provides high-precision positioning and depth information [7][8][9], but also expands the technical means of obtaining information on oceanographic surveys. For example, in order to improve the accuracy of ocean measurement and reduce the input of artificial stations, researchers around the world are committed to the use of high-precision GNSS [10] for shipborne navigation [11,12] measurement in recent years.…”