Energy Efficient Broadcasting Based on Ant Colony System Optimization Algorithm in Wireless Sensor Networks

Abstract

Broadcasting operation is used to distribute the information from one WSNs node to all nodes. In this paper, we develop a protocol for energy efficient Broadcasting based on Ant colony system Optimization Algorithm that is called BAOA. We present the procedure of BAOA including six steps when searching the optimized broadcasting path in WSNs and design BAOA with UML. We also simulate BAOA with C++ language and the results show the lifetime of BAOA is longer and the total energy consumption is less than BIP.

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

“…The main reasons for using bio-inspired methods to solve wake-up scheduling problems have been their optimization capability [143,80,[87][88][89][90]94,20,14,17,105,95,129,104,98,102,100,84,79,58,74,57] that facilitates the discovery of efficient wake-up schedules; distributed nature [113,18,92,80,[87][88][89]94,14,[103][104][105]136,138,17,66,69,74,78,93,57] that well matches the topology of WSNs and allows optimization based on readily available local information; and various self-n properties, that endow the networks with greater autonomy; they include ○ self-organization [ ○ self-assembly (of services and schedules) [138,14], ○ self-healing …”

“…An overview of applications of ant-inspired methods for solving different tasks in the area of WSN was prepared by Hong et al [17]. Nature-inspired methods have also been used to address routing [24][25][26] and broadcasting problems [20,27].…”

“…Nature-inspired methods have been extensively used to provide required functionality in the areas of networking in general [14], and WSN in particular [13,[15][16][17][18][19][20]. For example, Charalambous and Cui [16] used a clustering algorithm inspired by biological intercell signalling schemes and a cluster head selection scheme based on biological lateral inhibition model for energyaware WSN topology management.…”

A Survey on the Application of Evolutionary Algorithms for Mobile Multihop Ad Hoc Network Optimization Problems

“…This is the case of BAOA [67], which uses ant colony optimization algorithms for minimizing the total energy consumption. Although it runs online, it requires global knowledge (location of all nodes).…”

An Ant Colony Optimization Approach for Maximizing the Lifetime of Heterogeneous Wireless Sensor Networks

“…ACO algorithms have been successfully applied to a number of industrial and scientific problems [41]- [47]. In the fields of WSNs, ACO-based routing algorithms have been used for improving the power efficiency in unicasting [8]- [11], broadcasting [12], [13], and data gathering [14]. Different from the above ACO algorithms that focus on the routing issue in homogeneous WSNs, this paper proposes an ACO-based approach for maximizing the lifetime of heterogeneous WSNs by finding the maximum number of connected covers.…”