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Query Support for Data Processing and Analysis on Ethereum Blockchain
Pratama F.A.a, Mutijarsa K.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Blockchain technology has gained immense popularity because many researchers believe that it could solve numerous problems and could be applied in various fields of study. Unfortunately, behind its potentials, blockchain also possessed many challenges and limitations. The highlighted problem is the usability aspect of blockchain technology examined from developer and user perspective. This paper tried to address this problem by proposing query functionalities, with the help of query layer system, to facilitate the developer and the user to access blockchain data easily. There are three main query functionalities that will be discussed in this paper: (1) finding blockchain data based on multiple search parameters (retrieval query), (2) providing simple statistical analysis from a collection of blockchain data (aggregate query) and (3) sorting blockchain data according to its blockchain component (ranking query). For the implementation stage, Ethereum is used as platform to provide blockchain network, MongoDB is used as cloud storage service and REST API is used as web services. For the testing stage, throughput and time response are used to evaluate the performance of the developed query functionalities in the query layer system. The results are: (1) the throughput of query layer system is lower than Ethereum service for blockchain data retrieval and (2) the time response of query layer system is affected by the number of thread and the amount of data stored in cloud storage.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Aggregate queries,Cloud storage services,Cloud storages,Data processing and analysis,Multiple search,Number of threads,query,User perspectives[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]blockchain,cloud storage,Ethereum,query[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ISESD.2018.8605476[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]