2,459 research outputs found
Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks
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.Comment: To appear in Journal of Computer and System Science
A Review of Interference Reduction in Wireless Networks Using Graph Coloring Methods
The interference imposes a significant negative impact on the performance of
wireless networks. With the continuous deployment of larger and more
sophisticated wireless networks, reducing interference in such networks is
quickly being focused upon as a problem in today's world. In this paper we
analyze the interference reduction problem from a graph theoretical viewpoint.
A graph coloring methods are exploited to model the interference reduction
problem. However, additional constraints to graph coloring scenarios that
account for various networking conditions result in additional complexity to
standard graph coloring. This paper reviews a variety of algorithmic solutions
for specific network topologies.Comment: 10 pages, 5 figure
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