2011/12/30 by Chi Lin, Lin, Chi, Guowei Wu +9
Computer Science · Engineering · #68M14 #C.2 #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Networking and Internet Architecture (cs.NI) #Security in Wireless Sensor Networks #acm:68M14 #cs.NI #msc:68M14
paper · pdf · doi:10.48550/arxiv.1201.0119
To appear in Journal of Computer and System Sciences
arxiv created 2011/12/30 · openalex publication_date 2011/12/30 · arxiv updated 2012/01/04 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some 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 we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.