دانلود مقاله ISI انگلیسی شماره 85809
ترجمه فارسی عنوان مقاله

بودجه آگاهانه کیفیت سنجی، سنسور تشخیص آلودگی را در سیستم توزیع آب محدود می کند

عنوان انگلیسی
Quality-of-sensing aware budget constrained contaminant detection sensor deployment in water distribution system
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
85809 2018 23 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Network and Computer Applications, Volume 103, 1 February 2018, Pages 274-279

ترجمه کلمات کلیدی
سیستم توزیع آب، تشخیص آلودگی، شبکه های حسگر بی سیم، قرار دادن سنسور،
کلمات کلیدی انگلیسی
Water distribution system; Contamination detection; Wireless sensor networks; Sensor placement;
پیش نمایش مقاله
پیش نمایش مقاله  بودجه آگاهانه کیفیت سنجی، سنسور تشخیص آلودگی را در سیستم توزیع آب محدود می کند

چکیده انگلیسی

Water contamination or pollution has raised serious disasters and social impact. It is significant to alleviate its impact or reduce the risks. Deploying water quality monitoring sensors in the water distribution systems naturally becomes a promising solution. In the consideration of sensor deployment, the deployment cost and the achieved quality-of-sensing, usually in terms of coverage, are always two contradictive issues. Although massively deploying sensors implies higher quality-of-sensing, it may also incur extremely high deployment cost. Actually, it is usually infeasible with the consideration of limited sensor deployment budget. In this paper, we are motivated to investigate a budget constrained sensor deployment in water distribution system, with the goal of maximizing the quality-of-sensing. Two kinds of sensors with different prices and hence different communication capabilities are considered. The cheaper one equips with only sensor-to-sensor communication capability. While, the expensive one is further capable of cellular communication. We first formally describe our problem using a mixed integer non-linear programming (MINLP) problem. To address the complexity on solving MINLP, we further propose a heuristic algorithm based on genetic algorithm, whose high efficiency is extensively validated by simulation based studies.