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

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

Existing marine sensor networks acquire data in sea areas divided geographically and store them in their own data centers of the sea area independently. In the case of marine disaster across multiple sea areas, which needs to retrieve data from multiple data centers, the current network structure has a serious impact on real-time decision making. To efficiently carry out data layout and speed up the data retrieval, in this study, the marine sensor network is abstracted as a graph, all the sensors are considered as the vertexes of the graph, and the degree of correlation between the sensors computed with the previous disasters data is taken as the edge. A multi-objective optimization algorithm (NSGA-II) is used to partition the abstract graph into multiple regions and store them in a cloud computing platform. The NSGA-II maximizes the correlation of sensor within the region, minimizes the correlation of inter-region, achieves a balanced size of the regions and minimizes communication time of inter-region. The experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in China Sea area, and effectively shorten the data retrieval time, providing fast and efficient data access service for marine disasters.

Multi-objective balanced partitioning method for marine sensor network

Environmental monitoring plays an important role in human life, so this project aims to provide a spatial-temporal resolution of data collected inland water storages and lakes through the development of a unique floating platform. Several challenges in monitoring environment especially the accessibility to the site and representativesness of data cause the quality of water and air become worse. Hence, an unsupervised floating platform was developed in order to monitor the environment. The system focused on doing a precision measurement of water quality and air quality. With the help of several sensors that act as an input that is Real-Time Clock, Global Positioning System (GPS) sensor, humidity and temperature sensor, pH sensor and carbon monoxide sensor. Through this sensor, the floating platform collects the data and save it for every 10 minutes to perform real-time data collection. The data are saved into SD card, which consists of time, date, longitude, latitude, carbon monoxide, water pH value, temperature, and humidity. The results obtained then used to evaluate the quality of the air and water of the lake.

Unsupervised floating platform for environmental monitoring

In general, having a good lifestyle and clean environment is the main goals in life. Hence, environmental monitoring plays a great role in human life. The problem of environmental pollution has become increasingly serious especially in water quality as well as air quality. Thus, this project aim on to provide a spatial-temporal resolution of data collected through the process of developing of a floating platform. In order to maintain the quality of water and air, this floating platform will be attached with several sensors that will measure several parameters to be verified. Hence, a floating platform was developed in order to observe the surroundings. This floating platform focused on doing a precision measurement of water quality and air quality. Several sensors were attached to the floating platform and act as an input which is; Real-Time Clock, Global Positioning System (GPS) sensor, temperature and humidity sensor, pH sensor, and carbon monoxide sensor. Then, the collected data from each sensor will be saved in to the SD card for every 10 minutes in order to perform real-time data collection. The data saved consists of time, date, longitude, latitude, temperature and humidity value, water pH value, and carbon monoxide value. The results prevail then used to evaluate the quality of water and air of the lake.

Development of a floating platform for measuring air and water quality

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Port Operational Marine Observing System

The Bulgarian National Operational Marine Observing System (NOMOS) is a system of systems designed to allow the real-time assessment of weather and marine conditions in the coastal, shelf and open sea areas of the western part of Black Sea. NOMOS consists of several subsystems: POMOS, Galata, Shkorpilovtci, BulSeaL and BulARGO. POMOS is an observing system located in the ports (14 measuring sites, 45 instruments, 14 weather and seastate parameters), designed to provide weather and sea state operational information for the areas of major Bulgarian ports (Varna, Burgas and Balchik), intended to secure safety shipping in ports, canals and bays. Galata is a platform which provides open sea Real-time meteorological and oceanographic information from 24 sensors, measuring 31 major oceanographic and meteorological parameters. Shkorpilovtci is a coastal oceanographic station compiling: weather station, sea level gauge, UV radiation sensor and Recording Doppler Current Profiler with wave sensor. BulSeaL is a network of sea level stations including four historical sites, measuring sea level from more than 80 years. BulARGO is a set of Argo floats deployed in the frame if the project supported by Bulgarian National Science Fund, Ministry of education, youth and science. The purpose of the BulARGO project is to develop a new national marine research infrastructure for in situ observation in Black Sea based on autonomous profiling floats as a Bulgarian component of the Euro Argo network. These subsystems collect real time data using various instruments and sensors placed at different strategic locations. All instruments are connected to communication system via intranet which provides direct access to the sensors. The measured data are transmitted to the central collecting system, where the information is processed and stored in database. Access to database is through internet/intranet with the help of browsers. Actual data is controlled by Data Management System an can be displayed on the computer screens using report server supporting thereby needs of different group of users. Next future development will be to install new system which includes five open sea moorings equipped with meteorological and oceanographic sensors as well as with seismometers as a main component of a marine hazards early warning system. The main goal of NOMOS is to support sustainable development of the Bulgarian Black Sea coast and EEZ, and the main task is to provide operational information for the needs of: national security, civil protection, Search and Rescue, government and local authorities, port authorities, shipping, marine industry, fishery and aquaculture, tourist industry, environmental protection, coast protection, oil spills combat and other interested. NOMOS real time data is one of the most important sources of multi-parameter operational information in the Black Sea which will serve for monitoring, verification and improvement of model results and forecasts as well as for collecting long time series of data needed for climatic research, marine physics, chemistry and biology. Free real time data access and developed user friendly WEB and WAP interfaces made the system useful not only for science, marine industry and governmental agencies but also for general public, especially for yachtsmen and windsurfers.

Violrta Slabakova

Papers

Bulgarian National Operational Marine Observing System