کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
429593 687607 2012 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy efficient ant colony algorithms for data aggregation in wireless sensor networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Energy efficient ant colony algorithms for data aggregation in wireless sensor networks
چکیده انگلیسی

In energy-constrained wireless sensor networks, energy efficiency is critical for prolonging the network lifetime. A family of ant colony algorithms called DAACA for data aggregation are proposed in this paper. DAACA consists of three phases: initialization, packets transmissions and operations on pheromones. In the transmission phase, each node estimates the remaining energy and the amount of pheromones of neighbor nodes to compute the probabilities for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustments are performed, which take the advantages of both global and local merits for evaporating or depositing pheromones. Four different pheromones adjustment strategies which constitute DAACA family are designed to prolong the network lifetime. Experimental results indicate that, compared with other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last, the features of DAACA are analyzed.


► A family of ant colony algorithms for data aggregation are proposed called DAACA.
► DAACA adjusts the network topology by using pheromones.
► DAACA prolongs the network lifetime and enhances the energy efficiency.
► DAACA has low computational complexity and high transmission success ratio.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computer and System Sciences - Volume 78, Issue 6, November 2012, Pages 1686–1702
نویسندگان
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