ASDP: An Action-Based Service Discovery Protocol Using Ant Colony Algorithm in Wireless Sensor Networks

Author(s):  
Hongwei Huo ◽  
Deyun Gao ◽  
Yanchao Niu ◽  
Shuai Gao
2017 ◽  
Vol 13 (07) ◽  
pp. 69 ◽  
Author(s):  
Lin-lin Wang ◽  
Chengliang Wang

<p><span style="font-size: medium;"><span style="font-family: 宋体;">Aiming at the coverage problem of self-organizing wireless sensor networks, a target coverage method for wireless sensor networks based on Quantum Ant Colony Evolutionary Algorithm (QACEA) is put forward. This method introduces quantum state vector into the coding of ant colony algorithm, and realizes the dynamic adjustment of ant colony through quantum rotation port. The simulation results show that the quantum ant colony evolutionary algorithm proposed in this paper can effectively improve the target coverage of wireless sensor networks, and has obvious advantages compared with the other two methods in detecting the number of targets and the convergence speed. Based on the above findings, it is concluded that the algorithm proposed plays an essential role in the improvement of target coverage and it can be widely used in the similar fields, which has great and significant practical value.</span></span></p>


2016 ◽  
Vol 15 (3) ◽  
pp. 6632-6642
Author(s):  
Khalid Kahloot ◽  
Akram A. ElKhatib

In the literature of wireless sensor networks (WSNs), a well studied problem is that of achieving full sevice discovery within a region according to the topology model of coverage. A large waiting time of wireless sensor applications spent in node discovery, as nodes need to periodically advertise their presence and be awake to discover other nodes for services. Uniformly random distributions are widely accepted models for the location of the nodes in WSNs. Depending on the application, it may also be possible to place sensors in a four models of topologies; random, square, tringle and hexagon. There is a rich literature on throughput capacity for WSNs topologies in general, but we want to specifically study Service Discovery Protocol and how proper node deployment scheme can reduce the complexity of problems. In this paper, the effect of node topology on the performance of Tiny Service Discovery Protocol (TinySDP) in WSNs has been analyzed. In order to measure and evaluate the performance of TinySDP within variant shapes of topologies, We compared in terms of success ratio, number of transmitted messages and average waiting time. Simulation results showed that hexagon topology has a high data success ratio and a very low average waiting time, which are major requirements for disaster management scenarios.  


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.


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