scholarly journals UAV-Assisted Low-Consumption Time Synchronization Utilizing Cross-Technology Communication

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5134
Author(s):  
Ziyi Tan ◽  
Xu Yang ◽  
Mingzhi Pang ◽  
Shouwan Gao ◽  
Ming Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Large Scale ◽  
Time Synchronization ◽  
Resource Constraints ◽  
Vital Role ◽  
Sensor Nodes ◽  
Zero Energy ◽  
Synchronization Errors ◽  
Low Consumption

Wireless sensor networks (WSNs) have been used in many fields due to its wide applicability. In this kind of network, each node is independent of each other and has its own local clock and communicates wirelessly. Time synchronization plays a vital role in WSNs and it can ensure accuracy requirements for coordination and data reliability. However, two key challenges exist in large-scale WSNs that are severe resource constraints overhead and multihop time synchronization errors. To address these issues, this paper proposes a novel unmanned aerial vehicle (UAV)-assisted low-consumption time synchronization algorithm based on cross-technology communication (CTC) for a large-scale WSN. This algorithm uses a UAV to send time synchronization data packets for calibration. Moreover, to ensure coverage and a high success rate for UAV data transmission, we use CTC for time synchronization. Without any relays, a high-power time synchronization packet can be sent by a UAV to achieve the time synchronization of low-power sensors. This algorithm can achieve accurate time synchronization with almost zero energy consumption for the sensor nodes. Finally, we implemented our algorithm with 30 low-power RF-CC2430 ZigBee nodes and a Da Jiang Innovations (DJI) M100 UAV on a 1 km highway and an indoor site. The results show that time synchronization can be achieved accurately with almost zero energy consumption for the sensor nodes, and the time synchronization error is less than 30 μs in 99% of cases.

scholarly journals A Study on the Impact of Nodes Density on the Energy Consumption of LoRa

2021 ◽  
Vol 15 (14) ◽  
pp. 157
Author(s):  
Aizat Faiz Ramli ◽  
Muhammad Ikram Shabry ◽  
Mohd Azlan Abu ◽  
Hafiz Basarudin
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Low Power ◽  
Large Scale ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Area Network ◽  
Wide Area Network ◽  
Consumption Ratio ◽  
The Impact

LoRaWAN is one of the leading Low power wide area network (LPWAN) LPWAN technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio ECR to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the nodes density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11.

scholarly journals A Survey on Comparisons of Cryptographic Algorithms Using Certain Parameters in WSN

2017 ◽  
Vol 7 (4) ◽  
pp. 2232 ◽  
Author(s):  
Pooja Singh ◽  
R.K. Chauhan
Keyword(s):  
Energy Consumption ◽  
Processing Speed ◽  
Energy Efficient ◽  
Resource Constraints ◽  
Vital Role ◽  
Sensor Nodes ◽  
Diffie Hellman ◽  
Dna Cryptography ◽  
Cryptographic Algorithms ◽  
Encryption Algorithms

The Wireless Sensor Networks (WSNs) have spread its roots in almost every application. Owing to their scattered nature of sensor nodes, they are more prone to attacks. There are certain applications e.g. military, where sensor data’s confidentiality requirement during transmission is essential. Cryptography has a vital role for achieving security in WSNs.WSN has resource constraints like memory size, processing speed and energy consumption which bounds the applicability of existing cryptographic algorithms for WSN. Any good security algorithms has higher energy consumption by the nodes, so it’s a need to choose most energy-efficient cryptographic encryption algorithms for WSNs. This paper surveys different asymmetric algorithms such as RSA, Diffie-Hellman, DSA, ECC, hybrid and DNA cryptography. These algorithms are compared based on their key size, strength, weakness, attacks and possible countermeasures in the form of table.

scholarly journals Energy management in sensor networks

2012 ◽  
Vol 370 (1958) ◽  
pp. 52-67 ◽  
Author(s):  
John A. Stankovic ◽  
Tian He
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Management ◽  
Large Scale ◽  
Energy Savings ◽  
Time Synchronization ◽  
Media Access Control ◽  
Media Access ◽  
Energy Aware ◽  
Holistic View

This paper presents a holistic view of energy management in sensor networks. We first discuss hardware designs that support the life cycle of energy, namely: (i) energy harvesting, (ii) energy storage and (iii) energy consumption and control. Then, we discuss individual software designs that manage energy consumption in sensor networks. These energy-aware designs include media access control, routing, localization and time-synchronization. At the end of this paper, we present a case study of the VigilNet system to explain how to integrate various types of energy management techniques to achieve collaborative energy savings in a large-scale deployed military surveillance system.

A Trust-Aware and Location-Based Secure Routing Protocol for WSN

2013 ◽  
Vol 373-375 ◽  
pp. 1931-1934 ◽  
Author(s):  
Yi Min Zhou ◽  
La Yuan Li
Keyword(s):  
Routing Protocol ◽  
Trust Management ◽  
Large Scale ◽  
Resource Constraints ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Malicious Nodes ◽  
Distributed Sensor ◽  
Trust Management System ◽  
Secure Routing Protocol

The Wireless Sensor Network applications has widely been used over the last few years. WSN is a novel self-organization wireless network which is made up of randomly distributed sensor Nodes. Due to some resource constraints, the design of security in WSN encounters a great many of new challenges. It is vulnerable to attack, which is harmful for availability of WSN. In this paper we propose a trust-aware and location-based secure routing protocol which protects WSN against routing attacks, and also supports large-scale WSN deployments. The proposed protocol is extended from GPSR protocol, which imports security mechanism that depends on a distributed trust management system. The solution has been shown to efficiently detect and avoid malicious nodes.

A Time Synchronization Algorithm Based on Cluster-Tree

2014 ◽  
Vol 1046 ◽  
pp. 348-351
Author(s):  
Hao Gang ◽  
Yi Zhuang
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Time Synchronization ◽  
High Energy ◽  
Cluster Tree ◽  
Network Synchronization ◽  
Hop Count ◽  
Synchronization Algorithm ◽  
Reduce Energy Consumption ◽  
High Energy Consumption

Concerning the problem that classical time synchronization algorithms applied to large-scale Wireless Sensor Network have low precision and high energy consumption, this paper proposes a time synchronization algorithm based on cluster-tree. The algorithm can decrease the synchronization hop count by constructing a spanning tree, and uses two-way SRS in inter-cluster and one-way ROS in intra-cluster to reduce the number of messages required for the network synchronization. The experimental results show that the algorithm can keep the network synchronization precision at a higher level and effectively reduce energy consumption of nodes compared with the RBS and TPSN.

scholarly journals Efficient Data Collection using Mobile Sink Scheme in IoT

2019 ◽  
Vol 9 (1) ◽  
pp. 1360-1371
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Data Collection ◽  
Large Scale ◽  
Performance Metrics ◽  
Route Planning ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Energy Hole

Wireless sensor networks (WSNs) have become increasingly important in the informative development of communication technology. The growth of Internet of Things (IoT) has increased the use of WSNs in association with large scale industrial applications. The integration of WSNs with IoT is the pillar for the creation of an inescapable smart environment. A huge volume of data is being generated every day by the deployment of WSNs in smart infrastructure. The collaboration is applicable to environmental surveillance, health surveillance, transportation surveillance and many more other fields. A huge quantity of data which is obtained in various formats from varied applications is called big data. The Energy efficient big data collection requires new techniques to gather sensor-based data which is widely and densely distributed in WSNs and spread over wider geographical areas. In view of the limited range of communication and low powered sensor nodes, data gathering in WSN is a tedious task. The energy hole is another considerable issue that requires attention for efficient handling in WSN. The concept of mobile sink has been widely accepted and exploited, since it is able to effectively alleviate the energy hole problem. Scheduling a mobile sink with energy efficiency is still a challenge in WSNs time constraint implementation due to the slow speed of the mobile sink. The paper addresses the above issues and the proposal contains four-phase data collection model; the first phase is the identification of network subgroups, which are formed due to a restricted range of communication in sensor nodes in a wide network, second is clustering which is addressed on each identified subgroup for reducing energy consumption, third is efficient route planning and fourth is based on data collection. The two time-sensitive route planning schemes are presented to build a set of trajectories which satisfy the deadline constraint and minimize the overall delay. We have evaluated the performance of our schemes through simulation and compared them with the generic enhanced expectation-maximization (EEM) mobility based scenario of data collection. Simulation results reveal that our proposed schemes give much better results as compared to the generic EEM mobility approach in terms of selected performance metrics such as energy consumption, delay, network lifetime and packet delivery ratio.

scholarly journals Building Representative-Based Data Aggregation Tree in Wireless Sensor Networks

2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
Yanfei Zheng ◽  
Kefei Chen ◽  
Weidong Qiu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Large Scale ◽  
Resource Constraints ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Detection Mechanism ◽  
Aggregation Tree

Data aggregation is an essential operation to reduce energy consumption in large-scale wireless sensor networks (WSNs). A compromised node may forge an aggregation result and mislead base station into trusting a false reading. Efficient and secure aggregation scheme is critical in WSN applications due to the stringent resource constraints. In this paper, we propose a method to build up the representative-based aggregation tree in the WSNs such that the sensing data are aggregated along the route from the leaf cell to the root of the tree. In the cinema of large-scale and high-density sensor nodes, representative-based aggregation tree can reduce the data transmission overhead greatly by directed aggregation and cell-by-cell communications. It also provides security services including the integrity, freshness, and authentication, via detection mechanism in the cells.

scholarly journals A System-Level Methodology for the Design of Reliable Low-Power Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1800 ◽  
Author(s):  
Oussama Brini ◽  
Dominic Deslandes ◽  
Frederic Nabki
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Low Power ◽  
Forward Error Correction ◽  
Data Communication ◽  
Sensor Nodes ◽  
System Level ◽  
Wireless Sensor ◽  
Ultra Low Power

Innovative Internet of Things (IoT) applications with strict performance and energy consumption requirements and where the agile collection of data is paramount are arising. Wireless sensor networks (WSNs) represent a promising solution as they can be easily deployed to sense, process, and forward data. The large number of Sensor Nodes (SNs) composing a WSN are expected to be autonomous, with a node’s lifetime dictated by the battery’s size. As the form factor of the SN is critical in various use cases, minimizing energy consumption while ensuring availability becomes a priority. Moreover, energy harvesting techniques are increasingly considered as a viable solution for building an entirely green SN and prolonging its lifetime. In the process of building a SN and in the absence of a clear and well-rounded methodology, the designer can easily make unfounded and suboptimal decisions about the right hardware components, their configuration, and reliable data communication techniques, such as automatic repeat request (ARQ) and forward error correction (FEC). In this paper, a methodology to design, configure, and deploy a reliable ultra-low power WSNs is proposed. A comprehensive energy model and a realistic path-loss (PL) model of the sensor node are also established. Through estimations and field measurements it is proven that, following the proposed methodology, the designer can thoroughly explore the design space and the make most favorable decisions when choosing commercial off-the-shelf (COTS) components, configuring the node, and deploying a reliable and energy-efficient WSN.

A Hybrid Energy-Efficient Itinerary Planning for Mobile Agents in Wireless Sensor Networks

2013 ◽  
Author(s):  
Yu-Cheng Chou
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Large Scale ◽  
Evolutionary Process ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Computing Power ◽  
Itinerary Planning ◽  
Hybrid Energy

Wireless sensor networks (WSNs) are limited to resources including computing power, storage capacity, and especially energy supply. Thus, energy consumption of sensor nodes has become a dominant performance index for a WSN. In addition, data transmission between sensor nodes is a main energy consumer of WSNs. This paper presents a method called immune genetic algorithm based multiple-mobile-agent itinerary planning (IGA-M2IP) that addresses issues of energy consumption in large-scale WSNs. The IGA-M2IP preserves a GA’s advantages, and further improves a GA’s efficiency by restraining possible degenerative phenomena during the evolutionary process.

scholarly journals Compression-Aware Aggregation and Energy-Aware Routing in IoT–Fog-Enabled Forest Environment

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4591
Author(s):  
Srividhya Swaminathan ◽  
Suresh Sankaranarayanan ◽  
Sergei Kozlov ◽  
Joel J. P. C. Rodrigues
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Forest Fire ◽  
Routing Protocol ◽  
Fire Management ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Lossy Networks ◽  
Packet Delivery ◽  
Forest Fire Management

Forest fire monitoring is very much needed for protecting the forest from any kind of disaster or anomaly leading to the destruction of the forest. Now, with the advent of Internet of Things (IoT), a good amount of research has been done on energy consumption, coverage, and other issues. These works did not focus on forest fire management. The IoT-enabled environment is made up of low power lossy networks (LLNs). For improving the performance of routing protocol in forest fire management, energy-efficient routing protocol for low power lossy networks (E-RPL) was developed where residual power was used as an objective function towards calculating the rank of the parent node to form the destination-oriented directed acyclic graph (DODAG). The challenge in E-RPL is the scalability of the network resulting in a long end-to-end delay and less packet delivery. Additionally, the energy of sensor nodes increased with different transmission range. So, for obviating the above-mentioned drawbacks in E-RPL, compressed data aggregation and energy-based RPL routing (CAA-ERPL) is proposed. The CAA-ERPL is compared with E-RPL, and the performance is analyzed resulting in reduced packet transfer delay, less energy consumption, and increased packet delivery ratio for 10, 20, 30, 40, and 50 nodes. This has been evaluated using a Contiki Cooja simulator.

Sign in / Sign up

Export Citation Format

Share Document