TỐI ƯU DỮ LIỆU LỚN HÀNG HẢI GOM CỤM K NHÓM THEO TRUNG BÌNH DỰA VÀO MÔ HÌNH MAPREUCE

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Tác giả: TÂM THÀNH PHẠM, TUẤN ANH PHẠM, XUÂN KIÊN ĐẶNG

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học Công nghệ Hàng hải, 2020

Mô tả vật lý: tr.15-21

Bộ sưu tập: Metadata

ID: 329663

Thêm vào giỏ Liên kết toàn văn

Với sự phát triển của công nghệ thông tin, dữ liệu hàng hải lớn đang là xu hướng ngày càng tăng của các ứng dụng nhằm xử lý mà không đủ bộ nhớ chính của việc phân tích dữ liệu lớn đang là bài toán thách thức hiện nay. Đối với ứng dụng chuyên sâu, dữ liệu hàng hải lớn, thuật ngữ “MapReduce” gần đây đã thu hút sự chú ý đáng kể và bắt đầu được nghiên cứu để phân tích mà có thể xử lý hàng petabyte dữ liệu AIS cho hàng triệu tàu thuyền. MapReduce là một mô hình lập trình cho phép dễ dàng phát triển các ứng dụng song song có thể mở rộng để xử lý dữ liệu lớn trên các cụm máy tính [1]. Trong bài nghiên cứu này, một thuật toán gom cụm được gọi là K-means dựa trên mô hình MapReduce để xử lý dữ liệu hàng hải tàu biển tại khu vực miền Nam, Việt Nam. Với kết quả thu được, chúng tôi đưa ra suy luận hoặc dự đoán về dữ liệu gom cụm mà chúng được thu thập và sau đó là hiển thị dữ liệu của các hàng hải tàu biển, bao gồm quy mô, hướng và phân bố không gian.With the development of information technology, the maritime big data is an increasing trend of applications being expected to deal with big data that usually do not fit in the main memory of an analyzing big data is a challenging problem today. For such data intensive application, the maritime big data, the “MapReduce” framework has recently attracted considerable attention and started to be investigated for analysis which can handle petabyte of AIS data for millions of vessels. MapReduce is a programming model that allows easy development of scalable parallel applications to process big data on large clusters of commodity machines. This study, a standard clustering algorithm called K-means is based on the MapReduce model to be processed the marine traffic data in southern region, Viet Nam. According to the main results obtained, we concerned with making inference or prediction the clustering data which were collected and were shown the dashboard of maritime vessels traffic, including the scale, the trend of change and the spatial distribution situation.

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