مشخصات مقاله | |
ترجمه عنوان مقاله | برنامه ریزی درختان جمع آوری داده با استفاده از اکتشاف محلی برای افزایش طول عمر شبکه در شبکه های حسگر |
عنوان انگلیسی مقاله | Scheduling of data aggregation trees using Local Heuristics to enhance network lifetime in sensor networks |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 14 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
4.205 در سال 2018 |
شاخص H_index | 119 در سال 2019 |
شاخص SJR | 0.592 در سال 2018 |
شناسه ISSN | 1389-1286 |
شاخص Quartile (چارک) | Q1 در سال 2018 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر، مهندسی فناوری اطلاعات |
گرایش های مرتبط | مهندسی الگوریتم و محاسبات، شبکه های کامپیوتری |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | شبکه های کامپیوتری – Computer Networks |
دانشگاه | Department of Computer Science and Engineering, Defence Institute of Advanced Technology, Defence Research and Development Organization, Pune 411021, India |
کلمات کلیدی | اکتشاف محلی، طول عمر شبکه، درختان جمع آوری داده |
کلمات کلیدی انگلیسی | Local Heuristics، Network lifetime، Data aggregation trees |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.comnet.2019.05.017 |
کد محصول | E13671 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract 1. Introduction 2. Proposed work 3. Algorithm SDLHO: Scheduling DATs using Local Heuristics with Ordering 4. Algorithm SDLHT: Scheduling DATs using Local Heuristics with Tree factor 5. Performance evaluation 6. Conclusion Declaration of competing interest References |
بخشی از متن مقاله: |
Abstract
Data gathering is a basic requirement in many applications of Wireless Sensor Networks (WSNs). In tree based data gathering, Data Aggregation Tree (DAT) is constructed by the sink or by the nodes in a distributed manner. In this paper, we study the problem of enhancing Network Lifetime (NL) using hybrid DAT construction methods. In hybrid methods of DAT construction, the sink and the nodes collaboratively construct the DAT. We propose three algorithms for Scheduling DATs using Local Heuristics with Ordering (SDLHO), with Randomization (SDLHR) and with Tree factor (SDLHT) techniques.These techniques avoid disparity in energy levels of the nodes and increase the survivability of the network. In addition, to address imperfect link quality, we propose an algorithm for Scheduling DATs using Local Heuristics with Ordering based on Link Quality (SDLHO-LQ). Rigorous simulation results demonstrate the efficacy of the proposed algorithms; and their ability to scaleup to suit deployment of applications in harsh regions. Further, their performances evaluated to quantify the amount of enhancements of NL with the existing state of art is propitious to suit the distributed environments. Introduction In WSNs, the sensors gather and send data to the sink. In applications like environmental monitoring, battlefield surveillance, structural health monitoring, pipeline monitoring and precision agriculture, the sensor nodes are typically randomly deployed and left unattended. Transmission of packets between sensors consumes energy. In terms of power consumption, transmitting a single bit of data is equivalent to 800 instructions [1]. In such situations, employing data gathering mechanisms that judiciously utilize battery power of sensor nodes is essential. By combining data packets from different sensor nodes, the number of packet transmissions is reduced. This technique of combining data so that crucial data is made available at the sink is termed as in-network data aggregation DA. In-network DA using tree based routing structure saves the cost of maintaining a routing table at each node and is suitable in energy constrained WSNs. Tree based DA reduces the number of packet transmissions, decreases energy consumption and improves NL. However, reducing packet transmissions is a challenging problem as it depends on the amount of data generated at each node and the structure of the DAT.In tree based DA, the DAT can be constructed in two ways. (1) In centralized DAT construction, the sink gathers information of the entire network and then constructs a DAT using a suitable tree construction algorithm [2–7]. (2) In distributed method of DAT construction, the nodes communicate with their neighboring nodes and select appropriate parent and child nodes to construct a DAT [1,5,8–10]. In this case, the sink does not require information about the entire network however this method adds communication overhead. |