{"_buckets": {"deposit": "c7b551af-527c-4c59-bb8a-2ae6c7987787"}, "_deposit": {"created_by": 45, "id": "6387", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "6387"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/6387", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Resource-based Data Placement Strategy for Hadoop Distributed File System", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Big-Data is a term for data sets that are so large or\ncomplex that traditional data processing tools are\ninadequate to process or manage them. Apache Hadoop\nis an open-source software framework for distributed\nstorage and distributed processing of very large data\nsets on computer clusters built from commodity\nhardware. The default Hadoop data placement strategy\nworks well in homogeneous cluster. But it performs\npoorly in heterogeneous clusters because of the\nheterogeneity (in terms of processing, memory,\nthroughput, I/O, etc.) of the nodes capabilities. It may\ncause load imbalance and reduce Hadoop performance.\nTherefore, Hadoop Distributed File System (HDFS) has\nto rely on load balancing utility to balance data\ndistribution. The utility consumes the cost of extra\nsystem resources and running time. As a result, data can\nbe placed evenly across the Hadoop cluster. But it may\ncause the overhead of transferring unprocessed data\nfrom slow nodes to fast nodes because each node has\ndifferent computing capacity in heterogeneous Hadoop\ncluster. In order to solve these problems, a data/replica\nplacement algorithm based on storage utilization and\ncomputing capacity of each data node in heterogeneous\nHadoop Cluster is proposed. The proposed policy can\nbalance the workload as well as reduce overhead of\ndata transmission between different computing nodes."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "HDFS"}, {"interim": "Data Placement Policy"}, {"interim": "Load Balancing"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-11-20"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Resource-based Data Placement Strategy for Hadoop Distributed File System.pdf", "filesize": [{"value": "342 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_0", "mimetype": "application/pdf", "size": 342000.0, "url": {"url": "https://meral.edu.mm/record/6387/files/Resource-based Data Placement Strategy for Hadoop Distributed File System.pdf"}, "version_id": "9375e58b-a21c-4b91-a738-1cd3fb29678e"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICAIT-2017", "subitem_c_date": "1-2 November, 2017", "subitem_conference_title": "1st International Conference on Advanced Information Technologies", "subitem_place": "Yangon, Myanmar", "subitem_session": "Workshop Session", "subitem_website": "https://www.uit.edu.mm/icait-2017/"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Nang Kham Soe"}, {"subitem_authors_fullname": "Tin Tin Yee"}, {"subitem_authors_fullname": "Ei Chaw Htoon"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2017-11-02"}, "item_title": "Resource-based Data Placement Strategy for Hadoop Distributed File System", "item_type_id": "21", "owner": "45", "path": ["1605779935331"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000006387", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-11-20"}, "publish_date": "2020-11-20", "publish_status": "0", "recid": "6387", "relation": {}, "relation_version_is_last": true, "title": ["Resource-based Data Placement Strategy for Hadoop Distributed File System"], "weko_shared_id": -1}