Improved bat algorithm with optimal forage strategy and random disturbance strategy

Self Cite

Summary Wireless sensor networks (WSN) have high value in the field of wireless communications. As the earliest WSN clustering protocol, Low Energy Adaptive Clustering Hierarchy (LEACH) can effectively reduce the energy consumption of data transmission in sensor networks. However, LEACH has some problems such as cluster head nodes are unevenly distributed. In this paper, a unified heuristic bat algorithm (UHBA) is proposed to optimize elections in cluster heads. This algorithm guarantees that the election of cluster heads can freely transform both global search and local search. Meanwhile, comparing with several other variants of the bat algorithm in CEC2013 test suite, it can be seen from results that UHBA has better performance. Moreover, the application of the algorithm on LEACH is better than other algorithms, which further proves that the algorithm has better results.

Section: Figurementioning

confidence: 99%

A unified heuristic bat algorithm to optimize the LEACH protocol

Cai

Geng

et al. 2019

Self Cite

“…Recently, swarm intelligence has paid more attention in academia. 10 The typical swarm intelligent algorithms include artificial colony ant, 11 cuckoo search algorithm, 12 artificial bee colony, 13,14 bat algorithm, [15][16][17] and so on, which have widely used to all kinds of fields such as continuous optimization, [18][19][20] engineering optimization, [21][22][23][24] project management, 25 system optimization, 26 software design, 27,28 and so on. In addition, swarm intelligences have also applied to multi-objective problems.…”

Section: Andmentioning

confidence: 99%

Construction of extended ant colony labor division model for traffic signal timing and its application in mixed traffic flow model of single intersection

Jiang

Chen

et al. 2019

Summary The ant colony labor division model can be used to solve the dynamic and variable traffic signal timing problem because of its adaptive and self‐adjusting characteristics. Based on the basic model, this paper proposes a new extended ant colony labor division model for traffic signal timing. This model is combined with the vehicle characteristics to modify the calculation method of environmental stimulus values. Using the vehicle delay in the unit period, the original fixed response threshold is modified to the dynamic response threshold, and the state transition equation is reconstructed. Based on the mixed traffic flow model of two‐phase single‐point intersection cellular automata, through comparative experiments and discussion and analysis, it is found that the extended ant colony labor division model can effectively improve road traffic capacity according to road conditions and reasonable traffic signal timing.

“…The head node selection has become a popular optimization problem, which influence not only the location but also the limitation of energy, which should be considered in node selection. A biological heuristic algorithm is an effective method for solving this optimization problem such as CS, (BA), GSO, BFO, PSO ABC, etc.…”

Section: Related Workmentioning

confidence: 99%

An improved energy‐low clustering hierarchy protocol based on ensemble algorithm

Xie

Liu

Zhao

2019

Summary LEACH (low‐energy adaptive clustering hierarchy) protocol is an important part of wireless sensor network (WSN) and consisting of a good deal of energy‐constrained nodes. LEACH is widely used but also faces various challenges and constraints. The biggest constraint is that the energy is limited and the network life is finite. In the article, an improved ensemble algorithm based on energy‐efficient LEACH is proposed. The ensemble algorithm benefits from the cuckoo search algorithm (CS), glowworm swarm optimization (GSO), and bacterial foraging optimization (BFO). The paper enhances local and global search capabilities by modify the CS GSO and BFO algorithm. To verify results, this paper performs statistical comparatives with oriented cuckoo search (OCS), bat algorithm with characteristics of Levy flights, particle swarm optimization, and adaptive differential evolution algorithm. Comparison results shows that the new method is effective. Moreover, the research also showed the universal applicability of the ensemble strategy in solving diverse problems by using above different optimization algorithms. To further exploit our mind, this paper applies the improved coupling algorithm to LEACH for selecting the cluster‐head node. Computational experiments illustrate that the method proposed in this paper can provide very competitive results compared to these bio‐inspired LEACH, both in terms of reducing the network energy consumption and improving the lifecycle of nodes.