scholarly journals Design of Trusted Security Routing in Wireless Sensor Networks Based on Quantum Ant Colony Algorithm

2017 ◽  
Vol 13 (07) ◽  
pp. 4
Author(s):  
Xiaobin Shu ◽  
Caihong Liu ◽  
Chunxia Jiao ◽  
Qin Wang ◽  
Hongfeng Yin
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Font Size

<span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">To d</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">esign an effective secure routing of trusted nodes in wireless sensor networks</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">, </span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">quantum ant colony algorithm is applied to the design of large-scale wireless sensor network routing. The trustworthy network is used as the pheromone distribution strategy.</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">Then</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">,</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US"> the pheromone is encoded by the quantum bit</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">. The pheromone is updated by the quantum revolving door, and the energy consumption prediction is carried out to select the path. Finally, the trusted security routing algorithm of the wireless sensor network based on the global energy balance is realized. </span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">The quantum ant colony algorithm is superior to the traditional ant colony algorithm in algorithm convergence speed and global optimization. It can balance the energy consumption of the network node and can effectively resist the attacks such as Wormholes.</span><span style="font-family: 'Times New Roman',serif; font-size: 10.5pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">It is very promising to apply the quantum ant colony algorithm to the routing algorithm of large scale wireless sensor networks.</span>

Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks

2016 ◽  
pp. 267-293
Author(s):  
Sahabul Alam ◽  
Debashis De
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Balanced Energy Consumption

Now a days Wireless Sensor Networks (WSNs) have grown rapidly due to advancement of information technology. Sensor nodes are deployed over the field for collecting useful information. Sensor nodes have limited battery power and bandwidth. As a result it is critical for planning energy efficient protocols in WSNs. It is necessary to transfer and gather information in optimized way to reduce the energy dissipation. Ant Colony Optimization (ACO) is already proved to be better technique to optimize the network routing protocols in WSNs. Ant based routing can have significant role to extend the network life time and balance energy consumption in WSNs. In this chapter wireless sensor network architecture, routing factors of wireless sensor networks, computational intelligence technique, ant colony algorithm and ant colony based balanced energy consumption approaches in wireless sensor network have been discussed.

Wireless Sensor Network Mobile Agent Routing Based on the Improved Ant Colony Algorithm

2014 ◽  
Vol 587-589 ◽  
pp. 2339-2345
Author(s):  
Jia Yan Li ◽  
Jun Ping Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Mobile Agent ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Redundant Data

This paper proposes a new wireless sensor routing algorithm by combining the ant colony algorithm with the mobile agent technology. This algorithm considers the distance and path energy overhead among nodes and residual node energy, equalizes the energy overhead in the network, improves the update rule of the ant colony information elements and speeds up convergence of the ant colony algorithm to get the optimal values. The simulation results indicate that this algorithm can improve the globalization and convergence speed, effectively reduce redundant data transmission and communication overhead, extend the network lifecycle and be very suitable for a large-scale wireless sensor network compared to other mobile agent routing algorithms.

scholarly journals Low-Energy Secure Routing Protocol for WSNs Based on Multiobjective Ant Colony Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm

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.

scholarly journals A Trusted Real-Time Scheduling Model for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Weizhe Zhang ◽  
Boyu Song ◽  
Enci Bai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Real Time ◽  
Task Scheduling ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Bee Colony ◽  
Scheduling Model

Heterogeneous multicore and multiprocessor systems have been widely used for wireless sensor information processing, but system energy consumption has become an increasingly important issue. To ensure the reliable and safe operation of sensor systems, the task scheduling success rate of heterogeneous platforms should be improved, and energy consumption should be reduced. This work establishes a trusted task scheduling model for wireless sensor networks, proposes an energy consumption model, and adopts the ant colony algorithm and bee colony algorithm for the task scheduling of a real-time sensor node. Experimental result shows that the genetic algorithm and ant colony algorithm can efficiently solve the energy consumption problem in the trusted task scheduling of a wireless sensor and that the performance of the bee colony algorithm is slightly inferior to that of the first two methods.

Study of Complex Network Optimization in Wireless Sensor Networks

2011 ◽  
Vol 55-57 ◽  
pp. 1305-1309
Author(s):  
Zheng Yao ◽  
Zhao Hua Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Complex Network ◽  
Ant Colony Algorithm ◽  
Transition Probability ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Local Optimum ◽  
Network Systems

Energy consumption is a critical problem in operation of wireless sensor networks. For the sake of avoiding the data abundance and balancing the energy consumption in wireless sensor networks, this paper makes a research on network nodes Optimization in wireless sensor network based on ant colony algorithm and WIA-PA protocol stack. The novel design improved on hardware and software to control consumption of the energy and used transition probability of ant colony algorithm from one node to the other to calculate and determine the optimal path of network node in traversal of these locations. The results of the examples show that this method has lower energy consumption, computational briefness and higher positioning accuracy; it can not easily run into the local optimum, and also be applied to other tracking of complex network systems.

MCL and ACO Based QoS Routing Algorithm for WSN Used in Power Line Monitoring

2014 ◽  
Vol 672-674 ◽  
pp. 2033-2036
Author(s):  
Li Fen Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Qos Routing ◽  
Ant Colony ◽  
Link Quality ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Qos Routing Algorithm

This paper presents a new cross-layer QoS routing algorithm for wireless sensor networks. Basing on the principle of cross-layer design, the algorithm adopts delay, nodes’ load and link quality as QoS metrics. The QoS routing metrics are regarded as heuristics correction factors in ant colony algorithm (ACA). The ants are divided into a number of different populations. Through the interaction of pheromone between multi populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone in time. To overcome the slow convergence of ant colony algorithm, membership cloud model (MCL) is used to control the randomness of the ants. The simulation results demonstrate that the routing algorithm can guarantee the real time, reliability and robustness of wireless sensor networks. It can also achieve the network load balancing.

scholarly journals A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

Algorithms ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 250
Author(s):  
Xingxing Xiao ◽  
Haining Huang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Sink Node ◽  
Underwater Wireless Sensor Networks ◽  
Head Node

Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selection based on the residual energy of nodes and the distance factor. The selected CHN gathers data sent by the CMNs and transmits them to the sink node by multiple hops. Optimal multi-hop paths from the CHNs to the SN are found by an improved ACO algorithm. This paper presents the ACO algorithm through the improvement of the heuristic information, the evaporation parameter for the pheromone update mechanism, and the ant searching scope. Simulation results indicate the high effectiveness and efficiency of the proposed algorithm in reducing the energy consumption, prolonging the network lifetime, and decreasing the packet loss ratio.

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