Link quality evaluation of a wireless sensor network in metal marine environments

2018 ◽  
Vol 25 (3) ◽  
pp. 1253-1271 ◽  
Author(s):  
David Rojas ◽  
John Barrett
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Quality Evaluation ◽  
Link Quality ◽  
Wireless Sensor ◽  
Marine Environments

scholarly journals V2X-Based Mobile Localization in 3D Wireless Sensor Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Iram Javed ◽  
Xianlun Tang ◽  
Kamran Shaukat ◽  
Muhammed Umer Sarwar ◽  
Talha Mahboob Alam ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Three Dimensional ◽  
Link Quality ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Position Information ◽  
Mobile Anchor ◽  
Anchor Nodes

In a wireless sensor network (WSN), node localization is a key requirement for many applications. The concept of mobile anchor-based localization is not a new concept; however, the localization of mobile anchor nodes gains much attention with the advancement in the Internet of Things (IoT) and electronic industry. In this paper, we present a range-free localization algorithm for sensors in a three-dimensional (3D) wireless sensor networks based on flying anchors. The nature of the algorithm is also suitable for vehicle localization as we are using the setup much similar to vehicle-to-infrastructure- (V2I-) based positioning algorithm. A multilayer C-shaped trajectory is chosen for the random walk of mobile anchor nodes equipped with a Global Positioning System (GPS) and broadcasts its location information over the sensing space. The mobile anchor nodes keep transmitting the beacon along with their position information to unknown nodes and select three further anchor nodes to form a triangle. The distance is then computed by the link quality induction against each anchor node that uses the centroid-based formula to compute the localization error. The simulation shows that the average localization error of our proposed system is 1.4 m with a standard deviation of 1.21 m. The geometrical computation of localization eliminated the use of extra hardware that avoids any direct communication between the sensors and is applicable for all types of network topologies.

scholarly journals JSMCRP: Cross-Layer Architecture based Joint-Synchronous MAC and Routing Protocol for Wireless Sensor Network

2021 ◽  
Vol 19 (1) ◽  
pp. 94-113
Author(s):  
Shruti Birur Viswanath ◽  
Thippeswamy Muddenahalli Nagendrappa ◽  
Krishna Rao Venkatesh
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Communication Systems ◽  
Ieee 802.15.4 ◽  
Dynamic Network ◽  
Link Quality ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Monitoring And Control

The exponential rise in wireless technologies and allied applications has revitalized academia-industries to develop more efficient and economic routing solution to meet Quality-of-Service (QoS) provision. Amongst the major wireless communication systems, Wireless Sensor Network (WSN) is the most sought technology for defense surveillance, healthcare monitoring, industrial monitoring and control, civic and strategic infrastructure surveillance etc. Additionally, the up surge in Internet of Things (IoT) and Machine to Machine (M2M) communication systems too have broadened the horizon for WSNs based communication. However, the parallel increase in communication environment, complex network conditions etc confine efficacy of the classical WSN protocols. Dynamic network and node conditions often force classical protocols to undergo pre-mature link outage, delayed transmission, energy exhaustion and eventual QoS violation. To address such issues enhancing Median Access Control (MAC) and allied routing decision can have vital significance. However major existing efforts either focus on MAC enhancement or routing optimization, even under static WSN topology. Considering it as motive in this paper a highly robust “Cross-layer architecture based Joint-Synchronous MAC and Routing Protocol for WSN communication (JSMCRP)” has been developed. Being cross layer model JSMCRP protocol employs Application Layer, Network Layer, MAC Layer and PHY Layer to perform Network Adaptive MAC scheduling and Dynamic Routing Decision. JSMCRP employs Data Traffic Assessment, Prioritization and Scheduling (DTAPS), Proactive Network Monitoring and Knowledge (PNMK), Dynamic Congestion Index Estimation (DCIE), Adaptive Link Quality, Packet Injection Rate and Cumulative Rank Sensitive Routing Decision (CRSRD) to perform routing decision. Additionally, exploiting dynamic network/node conditions it performs Cognitive MAC scheduling to ensure QoS centric communication over IEEE 802.15.4 protocol stack. JSMCRP exhibited higher PDR, lower PLR and low delay under varying network conditions, suitable for real-time communication over constrained mobile WSN conditions.

scholarly journals Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096435 ◽  
Author(s):  
Muhammad Ilyas ◽  
Zahid Ullah ◽  
Fakhri Alam Khan ◽  
Muhammad Hasanain Chaudary ◽  
Muhammad Sheraz Arshed Malik ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Sensor Network ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Network Throughput ◽  
Link Quality ◽  
Wireless Sensor ◽  
Packet Latency

Internet of things grew swiftly and many services, software, sensors-embedded electronic devices and related protocols were developed and still in progress with full swing. Internet of things enabling physically existing things to see, hear, think and perform a notable task by allowing them to talk to each other and share useful information while making decision and caring-on/out their important tasks. Internet of things is greatly promoted by wireless sensor network as it becomes a perpetual layer for it. Wireless sensor network works as a base-stone for most of the Internet of things applications. There are severe general and specific threats and technical challenges to Internet of things–based sensor networks which must overcome to ensure adaptation and diffusion of it. Most of the limitations of wireless sensor networks are due to its resource constraint objects nature. The specified open research challenges in Internet of things–based sensor network are power consumption, network lifespan, network throughput, routing and network security. To overcome aforementioned problems, this work aimed to prolong network lifetime, improve throughput, decrease packet latency/packet loss and further improvise in encountering malicious nodes. To further tune the network lifetime in terms of energy, wireless harvesting energy is suggested in proposed three-layer cluster-based wireless sensor network routing protocol. The proposed mechanism is a three-tier clustering technique with implanted security mechanism to encounter malicious activities of sensor nodes and to slant them into blacklist. It is a centred-based clustering protocol, where selection of cluster head and grid head is carried out by sink node based on the value of its cost function. Moreover, hardware-based link quality estimators are used to check link effectiveness and to further improve routing efficiency. At the end, excessive experiments have been carried out to check efficacy of the proposed protocol. It outperforms most of its counterpart protocols such as fuzzy logic–based unequal clustering and ant colony optimization–based routing hybrid, Artificial Bee Colony-SD, enhanced three-layer hybrid clustering mechanism and energy aware multi-hop routing in terms of network lifetime, network throughput, average energy consumption and packet latency.

scholarly journals Human Detection through RSSI Processing with Packet Dropout in Wireless Sensor Network

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Haijing Wang ◽  
Fangfang Zhang ◽  
Wenli Zhang
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Detection Method ◽  
Human Detection ◽  
Link Quality ◽  
Wireless Sensor ◽  
Packet Dropout ◽  
Data Packets ◽  
Device Free

This paper presents a device-free human detection method for using Received Signal Strength Indicator (RSSI) measurement of Wireless Sensor Network (WSN) with packet dropout based on ZigBee. Packet loss is observed to be a familiar phenomenon with transmissions of WSNs. The packet reception rate (PRR) based on a large number of data packets cannot reflect the real-time link quality accurately. So this paper firstly raises a real-time RSSI link quality evaluation method based on the exponential smoothing method. Then, a device-free human detection method is proposed. Compared to conventional solutions which utilize a complex set of sensors for detection, the proposed approach achieves the same only by RSSI volatility. The intermittent Karman algorithm is used to filter RSSI fluctuation caused by environment and other factors in data packets loss situation, and online learning is adopted to set algorithm parameters considering environmental changes. The experimental measurements are conducted in laboratory. A high-quality network based on ZigBee is obtained, and then, RSSI can be calculated from the receive sensor modules. Experimental results show the uncertainty of RSSI change at the moment of human through the network area and confirm the validity of the detection method.

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