Performance Comparison among (Star, Tree and Mesh) Topologies for Large Scale WSN based IEEE 802.15.4 Standard

ZigBee is widely used in wireless network in Internet of Things (IoT) applications to remotely sensing and automation due to its unique characteristics compared to other wireless networks. According to ZigBee classification of IEEE 802.15.4 standard, the network consists of four layers. The ZigBee topology is represented in second layer. Furthermore, the ZigBee topology consists of three topologies, star, tree and mesh. Also there are many transmission bands allowed in physical layer, such as 2.4 GHz, 915 MHz, 868 MHz. The aim of this paper is to evaluate the effect of ZigBee topologies on End to End delay and throughput for different transmission bands. Riverbed Modeler is used to simulate multiple ZigBee proposed scenarios and collect the results. The results of the study recommend which topology should be used at each transmission band to provide lowest End to End delay or obtain maximum throughput, which is case sensitive in some IoT applications that required for example minimum delay time or sending high amount of data.

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An Efficient Superframe Structure with Optimal Bandwidth Utilization and Reduced Delay for Internet of Things Based Wireless Sensor Networks

Sensors ◽

10.3390/s20071971 ◽

2020 ◽

Vol 20 (7) ◽

pp. 1971 ◽

Cited By ~ 3

Author(s):

Sangrez Khan ◽

Ahmad Naseem Alvi ◽

Muhammad Awais Javed ◽

Byeong-hee Roh ◽

Jehad Ali

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Internet Of Things ◽

Large Scale ◽

Ieee 802.15.4 ◽

Fine Tuning ◽

Wireless Sensor ◽

Bandwidth Utilization ◽

Iot Applications ◽

Ieee 802.15.4 Standard

Internet of Things (IoT) is a promising technology that uses wireless sensor networks to enable data collection, monitoring, and transmission from the physical devices to the Internet. Due to its potential large scale usage, efficient routing and Medium Access Control (MAC) techniques are vital to meet various application requirements. Most of the IoT applications need low data rate and low powered wireless transmissions and IEEE 802.15.4 standard is mostly used in this regard which offers superframe structure at the MAC layer. However, for IoT applications where nodes have adaptive data traffic, the standard has some limitations such as bandwidth wastage and latency. In this paper, a new superframe structure is proposed that is backward compatible with the existing parameters of the standard. The proposed superframe overcomes limitations of the standard by fine-tuning its superframe structure and squeezing the size of its contention-free slots. Thus, the proposed superframe adjusts its duty cycle according to the traffic requirements and accommodates more nodes in a superframe structure. The analytical results show that our proposed superframe structure has almost 50% less delay, accommodate more nodes and has better link utilization in a superframe as compared to the IEEE 802.15.4 standard.

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Performance Analysis of IEEE 802.15.4 based Sensor Networks for Large Scale Tree Topology

Circulation in Computer Science ◽

10.22632/ccs-2017-252-41 ◽

2017 ◽

Vol 2 (7) ◽

pp. 9-13

Author(s):

Ziyad Khalaf Farej ◽

Ali Maher Abdul-hameed

Keyword(s):

Wireless Sensor Network ◽

Performance Analysis ◽

Large Scale ◽

Network Performance ◽

Ieee 802.15.4 ◽

Tree Topology ◽

Wireless Sensor ◽

Performance Parameters ◽

Packet Size ◽

Ieee 802.15.4 Standard

This paper evaluates the performance of IEEE 802.15.4 standard Wireless Sensor Network (WSN) in tree topology for large scale applications. The performance of the network is analyzed in terms of number of nodes, packet size and packet interval time (PIT) by using the discreet event OPNET (version 14.5) simulator. Performance investigation started with a packet size of 1408 bit and PIT of 1 sec in order to determine the best network performance, then based on the comparison which has been made among the network performance parameters, it is found that the network performance for tree topology is optimized at 90 nodes number with packet size of 4096 bits when PIT equals 1 sec.

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Autoconfiguration with Global Addresses Using IEEE 802.15.4 Standard in Multi-hop Networks

Enfoque UTE ◽

10.29019/enfoqueute.708 ◽

2021 ◽

Vol 12 (1) ◽

pp. 44-58

Author(s):

Carlos Egas Acosta ◽

David Cali ◽

Cristian Espinosa

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Large Scale ◽

Ieee 802.15.4 ◽

Sensor Nodes ◽

Wireless Sensor ◽

Correct Operation ◽

Allocation Process ◽

Ieee 802.15.4 Standard ◽

The Internet Of Things

Wireless sensor networks continue to attract a lot of attention from academia and industry promoting large-scale deployments in applications related to the Internet of Things (IoT). Unfortunately, a network containing a large number of sensor nodes also leads to difficulty in the configuring process and assignment of identifiers to nodes. Various approaches have been proposed to solve problems of auto-configuration in Wireless sensor networks, however, still, there are some issues remaining related to automatic assign identifiers A cluster-based hierarchical global address allocation scheme is proposed for a wireless sensor network. The proposal uses the IEEE 802.15.4 protocol and aims to reduce the latency of the identifier assignments and reduce the network level processes to be performed at the node. The address allocation process assigns each node a unique global address, which allows the node to have end-to-end connectivity without network-level involvement. The scenario of adding new nodes to the network or nodes that leave it is contemplated. Finally, the proposed scheme is evaluated experimentally, verifying the correct operation of the algorithm proposed in the implemented prototype.

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A Survey on Contrastive Self-Supervised Learning

Technologies ◽

10.3390/technologies9010002 ◽

2020 ◽

Vol 9 (1) ◽

pp. 2

Author(s):

Ashish Jaiswal ◽

Ashwin Ramesh Babu ◽

Mohammad Zaki Zadeh ◽

Debapriya Banerjee ◽

Fillia Makedon

Keyword(s):

Computer Vision ◽

Supervised Learning ◽

Language Processing ◽

Large Scale ◽

Performance Comparison ◽

Extensive Review ◽

Future Directions ◽

Dominant Component ◽

Supervised Methods ◽

The Cost

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.

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A Simulation Model of IEEE 802.15.4 GTS Mechanism and GTS Attacks in OMNeT++ / MiXiM + NETA

Computer and Information Science ◽

10.5539/cis.v11n1p78 ◽

2018 ◽

Vol 11 (1) ◽

pp. 78 ◽

Cited By ~ 1

Author(s):

Yasmin M. Amin ◽

Amr T. Abdel-Hamid

Keyword(s):

Simulation Model ◽

Data Transmission ◽

Ieee 802.15.4 ◽

Personal Area Networks ◽

Wireless Personal Area Networks ◽

Mac Layer ◽

Management Scheme ◽

Free Data ◽

Ieee 802.15.4 Standard ◽

Time Critical

The IEEE 802.15.4 standard defines the PHY and MAC layer specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs). With the proliferation of many time-critical applications with real-time delivery, low latency, and/or specific bandwidth requirements, Guaranteed Time Slots (GTS) are increasingly being used for reliable contention-free data transmission by nodes within beacon-enabled WPANs. To evaluate the performance of the 802.15.4 GTS management scheme, this paper introduces a new GTS simulation model for OMNeT++ / MiXiM. Our GTS model considers star-topology WPANs within the 2.4 GHz frequency band, and is in full conformance with the IEEE 802.15.4 – 2006 standard. To enable thorough investigation of the behaviors and impacts of different attacks against the 802.15.4 GTS mechanism, a new GTS attacks simulation model for OMNeT++ is also introduced in this paper. Our GTS attacks model is developed for OMNeT++ / NETA, and is integrated with our GTS model to provide a single inclusive OMNeT++ simulation model for both the GTS mechanism and all known-to-date attacks against it.

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Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model

Journal of Applied Mathematics ◽

10.1155/2014/934610 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15 ◽

Cited By ~ 6

Author(s):

Kwang-il Hwang ◽

Sung-wook Nam

Keyword(s):

Internet Of Things ◽

Large Scale ◽

Ieee 802.15.4 ◽

Design Model ◽

Abstract Model ◽

Modes Of Operation ◽

Network Construction ◽

Scheduling Model ◽

And Performance ◽

Ieee 802.15.4E

In order to construct a successful Internet of things (IoT), reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME) mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.

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Researching, building the routing algorithm in Zigbee networks

Journal of Military Science and Technology ◽

10.54939/1859-1043.j.mst.csce5.2021.32-41 ◽

2021 ◽

pp. 32-41

Author(s):

Dao Xuan Uoc

Keyword(s):

Ieee 802.15.4 ◽

Mesh Networks ◽

Routing Algorithm ◽

Optimal Routing ◽

Star Network ◽

Transmission Distance ◽

Zigbee Networks ◽

Iot Devices ◽

Ieee 802.15.4 Standard ◽

Better Than

Zigbee wireless network built on IEEE 802.15.4 standard is becoming one of the most popular wireless networks in modern IoT devices. One of the disadvantages of Zigbee networks is the short transmission distance between devices. This paper focuses on researching and comparing routing algorithms in Zigbee networks, thereby building the optimal routing algorithm in the existing system. The paper’s objective is to form the basis for making Zigbee tree and mesh networks, which improves the transmission distance for Zigbee networks better than the star network.

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