scholarly journals Modelling and QoS Implementation of Wireless Sensor Networks based on the Ant Colony Optimization Approach

2018 ◽  
Vol 10 (6) ◽  
pp. 23-35
Author(s):  
Ademola P. Abidoye ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Optimization Approach

An Ant Colony Optimization Approach to Power Allocation in Wireless Sensor Networks

2012 ◽  
Vol 263-266 ◽  
pp. 954-958
Author(s):  
Xiang Yang Liu ◽  
Da Wang ◽  
Jin Pan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Power Allocation ◽  
Detection Performance ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ant Colony System ◽  
Optimization Approach

The ant colony optimization algorithm is good at solving multidimensional optimization problem. The allocation of power resource of a node in wireless sensor networks should make the detection performance of the whole network maximum, which is complex due to the detection probability of the whole system cannot be expressed explicitly. Therefore, continuous ant colony system (CACS) is adopted to optimize the allocation of each node’s power between sensing and communications. The results show that it can lead to a good power allocation. At the same time, the scheme that all sensor nodes have identical power assignment can achieve nearly the same detection performance as compared that achieved by the best scheme searched by CACS. As a result, particu-larly for a large number of sensors, an identical power allocation scheme for each node can be employed to achieve nearly the best detection performance.

Ant Colony Algorithms for Steiner Trees

2011 ◽  
pp. 1551-1575 ◽  
Author(s):  
Gurdip Singh ◽  
Sanjoy Das ◽  
Shekhar V. Gosavi ◽  
Sandeep Pujar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Problems ◽  
Steiner Trees ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Graph Theoretic ◽  
Ant Colony Algorithms ◽  
Complex Optimization

This chapter introduces ant colony optimization as a method for computing minimum Steiner trees in graphs. Tree computation is achieved when multiple ants, starting out from different nodes in the graph, move towards one another and ultimately merge into a single entity. A distributed version of the proposed algorithm is also described, which is applied to the specific problem of data-centric routing in wireless sensor networks. This research illustrates how tree based graph theoretic computations can be accomplished by means of purely local ant interaction. The authors hope that this work will demonstrate how innovative ways to carry out ant interactions can be used to design effective ant colony algorithms for complex optimization problems.

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