Network capacity analysis for code propagation in Wireless Sensor Networks

For meeting the needs of the survey of agriculture environment communication in Hainan Province, an intelligent monitoring system was developed based on ZigBee which consists of four parts: wireless sensor networks, gateway, transmission network, remote monitoring center. A new type network structure which is composed of wireless sensor networks and the transmission network was proposed. This paper is devoted to explanation and illustration for our design of intelligent agricultural monitoring system. The system feasibility and superiority was verified in a simple star topology setup in a botanical garden in QiongZhou University. The sensor nodes can obtain the temperature, humidity and illumination information in real time, and then transferred to the remote monitoring center by the gateway via the transmission network. The test result shows that this intelligent agriculture monitoring system has the useful characteristics of low power consumption, low cost, large network capacity, flexible disposition, and minor influence on the natural environment. It has better actual application value.

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Genetic Algorithm for Effective Optimization of Delay Performance in Wireless Sensor Networks

Journal of University of Babylon for Pure and Applied Sciences ◽

10.29196/jubpas.v26i10.1886 ◽

2018 ◽

Vol 26 (10) ◽

pp. 281-308

Author(s):

Saif Khalid Musluh ◽

Alaa Abid Muslam ◽

Raid Abd Alreda Shekan

Keyword(s):

Genetic Algorithm ◽

Wireless Sensor Networks ◽

Wireless Networks ◽

Sensor Networks ◽

Network Performance ◽

Data Transfer ◽

Relay Node ◽

Network Capacity ◽

Wireless Sensor ◽

Delay Performance

Wireless sensor networks (WSNs) play an important role in many real-world applications like surveillance. Wireless networks are also used to have data transfer. In such cases, there are problems with resourcece-constraintnednetworks. The problems include a delay in communication and reduction in Quality of Service (QoS). Topology control can solve this problem to some extent. However, the delay performance and QoS need to be improved further to support intended operations in wireless networks. When relay node concept is considered, it is possible to optimize performance in such networks. In this paper, we proposed a Genetic Algorithm (GA) based relay configuration for optimizing delay performance in WSN. Relay nodes compute optimal positions using the proposed algorithm so as to improve QoS and reduce delay as much as possible. We implemented the algorithm using NS2 simulations. The results revealed that the proposed approach is able to improve QoS, reduce delay besides improving network performance in terms of throughput, network capacity, and energy efficiency.

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Capacity Analysis for Flat and Clustered Wireless Sensor Networks

International Conference on Wireless Algorithms, Systems and Applications (WASA 2007) ◽

10.1109/wasa.2007.145 ◽

2007 ◽

Author(s):

Min Song ◽

Bei He

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Wireless Sensor ◽

Capacity Analysis

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Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing

Complexity ◽

10.1155/2021/5556651 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Jie Liu ◽

Li Zhu

Keyword(s):

Resource Allocation ◽

Wireless Sensor Networks ◽

Sensor Networks ◽

Single Channel ◽

Network Capacity ◽

Edge Computing ◽

Wireless Sensor ◽

Allocation Model ◽

Single Interface ◽

Joint Resource Allocation

Resource allocation has always been a key technology in wireless sensor networks (WSN), but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of single interface and single channel networks, it also brings new opportunities to the development of wireless sensor networks, but the multi-interface and multichannel technology not only improves the performance of wireless sensor networks but also brings great challenges to the resource allocation of wireless sensor networks. Edge computing changes the traditional centralized cloud computing processing method into a method that reduces computing storage capacity to the edge of the network and faces users and terminals. Realize the advantages of lower latency, higher bandwidth, and fast response. Therefore, this paper proposes a joint optimization algorithm of resource allocation based on edge computing. We establish a wireless sensor allocation model and then propose our algorithm model combined with the advantages of edge computing. Compared with the traditional allocation algorithm (PCOA, MCMH, and TDMA), it can further improve the resource utilization, reduce the network energy consumption, increase network capacity, and reduce the complexity of the schemes.

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