يلعب تخفيض استهلاك الطاقة للعقد المختلفة في شبكات الحساسات اللاسلكية دوراً هاماً وأساسياً في إطالة عمر هذه الشبكات. وكي لا يكون استهلاك الطاقة في بعض العقد كبيراً، وفي بعض العقد أقل، أو حتى صغيراً، فإن اختيار خوارزميات توزيع أدوار العقد، بين عقد طرفية، وعقد توجيه، وتبديل هذه الأدوار، يلعب دوراً هاماً في إطالة عمر شبكات الحساسات اللاسلكية.
يقدم هذا البحث خوارزمية لتوزيع الأدوار بما يسمح بتشكيل نماذج شجرية متعددة لشبكة واحدة. وهذا يقدم الإمكانية لمنسق الشبكة بتبديل أدوار العقد مركزياً بتبديل النموذج الشجري كلما دعت الحاجة حسب مؤشرات استهلاك الطاقة في العقد. وتظهر النتائج أن استخدام الخوارزمية يؤدي إلى تحسن كبير في زمن حياة الشبكة يتراوح بين 2 و 4 مرات، وذلك حسب السماح بنوم واستيقاظ العقد أو عدم السماح بذلك. وذلك من أجل معدلات إرسال مختلفة.
وقد تم اختبار سيناريوهات عمل شبكات الحساسات اللاسلكية بالاعتماد على استخدام تقنية ZigBee، وباستخدام المحاكاة، اعتماداً على المحاكي الشبكي NS-2.
The reducing of energy consumption for various nodes in wireless sensor networks
plays an important and essential role in the prolonging of the life of these networks. In
order not to be the energy consumption in some node is very high and in others is less or
very low, the choice of distribution algorithms of the nodes role, as a router node or
terminal nodes, and switching between them, plays an important role in prolonging the
lifetime of wireless sensor networks.
This paper presents an algorithm for the distribution of WSN nodes roles, including
allowing the applying of many tree patterns to a single network. This offers the potential to
alter the network nodes roles centrally by coordinator and switching between these tree
patterns whenever the need arises according to the indicators of energy consumption in the
nodes. The results show that the use of the algorithm leads to a significant improvement in
the network life ranges between 2 and 4 times, according to the allowing the nodes to sleep
and wakeup, or not, for different transmission rates where the scenarios have been tested
for ZigBee based wireless sensors networks using NS-2 simulator.
References used
Jennifer Yick, Biswanath Mukherjee, DipakGhosal, “Wireless sensor network survey,” Computer Networks, Elsevier Publications, vol. 52, pp. 2229–2330, 2008
Z. Xu, Yue Yin, Jin Wang and Jeong-UkKim“An Energy-Efficient Clustering Algorithm in WSN with Multiple Sinks”, International Journal of Distributed Sensor Network, 2012
K. Padmanabhan, Dr. P. Kamalakkannan “Energy Efficient Adaptive Protocol for Clustered Wireless Sensor Networks” IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 1, September 2013
Tony Ducrocq, Michaël Hauspie, and Nathalie Mitton; Balancing Energy Consumption in Clustered; Wireless Sensor Networks; ISRN Sensor Networks; September 2013
Gun M., Kosar R., Ersoy C. Lifetime optimization using variable battery capacities and nonuniform density deployment in wireless sensor networks // Computer and information sciences, 2007. iscis 2007. 22nd international symposium on. 2007. P. 1–6
Many wireless sensor network applications like forest fire detection and environment
monitoring recommend making benefit from moving humans, vehicles, or animals to
enhance network performance. In this research, we had improved our previous protoco
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The development of these net
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r
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