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Software systems for data‐centric smart city applications
Author(s) -
Chen Dan,
Wang Lizhe,
Zhou Suiping
Publication year - 2017
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2508
Subject(s) - smart city , computer science , cloud computing , big data , scalability , information and communications technology , software , telecommunications , data science , computer security , world wide web , internet of things , database , programming language , operating system
The smart city is the key technology for efficient management, sustainable development, and efficient governance in the current worldwide urbanization process. It incorporates the latest information technologies particularly data-driven trends to improve support for the everyday life of people, especially in security, transportation, and social services. The smart city paradigm can be specified as a large-scale distributed system in which the massive data generated by smart electronic devices, smart environments, and Internet of Things (IoT) can be organized, managed, and analyzed. The design of scalable software applications, frameworks, and packages is important in forming approaches which integrate smart city infrastructures (environment, physical ICT infrastructure), public processes, and services. Recently, software system development for data-centric smart city applications has become a very active area of research in academia and has attracted significant interest from industry. Since computing issues for smart cities are highly interdisciplinary and cover various topics, a special issue of Software: Practice and Experience provides the ideal forum for presenting and discussing the latest research. The goal of this special issue is to present outstanding research results in regard to software systems for data-centric smart city applications. We received 23 manuscript submissions in total; of these, 7 papers were accepted after several rounds of very constructive and deep reviews. Large-scale wireless communication is the fundamental infrastructure needed to ensure the operation of smart city, cloud computing, the IoT, etc. A relay network can provide an efficient solution to reliable transmission of large amounts of data. However, when base stations are densely populated, energy consumption becomes a critical problem. To solve this problem, Lam et al propose a software system for robust power management taking uncertain channel gains into consideration. The system relies on a distributed power allocation algorithm to reduce the overhead of extra information exchange while guaranteeing performance with respect to energy savings and robustness in a dynamic communications environment. Smart city uses many data sources. To manage the massive volume of data, data compression is essential, especially for surveillance videos. Since lossy compression methods cause information loss, a high compression ratio negatively affects data analysis. Xiao et al tackled this problem by proposing a sensitive-object–oriented compression method for surveillance videos. Regions with sensitive objects critical to the analysis of surveillance videos are detected prior to compression. Higher bit rates are assigned to these regions to enable a high compression ratio for the whole video stream without sacrificing the performance of data analysis centered on the sensitive objects. Data analysis is at the very core of smart city applications. Four interesting topics are included in this special issue, covering cloud-based mining for traffic data, low-cost computing for face tracking, fast processing of forensic data, and accurate analysis of human emotions: