scholarly journals RODENT: a flexible TOPSIS based routing protocol for multi-technology devices in wireless sensor networks

2021 ◽  
Vol 2 (1) ◽  
pp. 89-100
Author(s):  
Nathalie Mitton ◽  
Brandon Foubert
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Savings ◽  
Wireless Sensor ◽  
Radio Access ◽  
Multiple Data ◽  
Functional Prototype ◽  
Network Technologies ◽  
Data Requirements ◽  
Selection Of

Wireless Sensor Networks (WSN) are efficient tools for many use cases, such as environmental monitoring. However WSN deployment is sometimes limited by the characteristics of the Radio Access Technologies (RATs) they use. To overcome some of these limitations, we propose to leverage the use of a Multiple Technologies Network (MTN). What we refer to as MTN is a network composed of nodes which are able to use several RAT and communicating wirelessly through multi-hop paths. The management of the RAT and routes must be handled by the nodes themselves, in a local and distributed way, with a suitable communication protocol stack. Nodes may reach multiple neighbors over multiple RAT. Therefore, each stack's layer has to take the technologies' heterogeneity of the devices into account. In this article, we introduce our custom Routing Over Different Existing Network Technologies protocol (RODENT), designed for MTN. It enables dynamic (re)selection of the best route and RAT based on the data type and requirements that may evolve over time, potentially mixing each technology over a single path. RODENT relies on a multi-criteria route selection performed with a custom lightweight TOPSIS method. To assess RODENT's performances, we implemented a functional prototype on real WSN hardware, Pycom FiPy devices. Unlike related prototypes, ours has the advantage not to rely on specific infrastructure on the operator's side. Results show that RODENT enables energy savings, an increased coverage as well as multiple data requirements support.

scholarly journals Efficient Node and Sensed Module Management for Multisensory Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2328 ◽  
Author(s):  
Juan Feng ◽  
Xiaozhu Shi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Management Strategies ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Tracking Accuracy ◽  
Node Selection ◽  
Information Utility ◽  
Save Energy ◽  
Selection Of

In target tracking wireless sensor networks, choosing a part of sensor nodes to execute tracking tasks and letting the other nodes sleep to save energy are efficient node management strategies. However, at present more and more sensor nodes carry many different types of sensed modules, and the existing researches on node selection are mainly focused on sensor nodes with a single sensed module. Few works involved the management and selection of the sensed modules for sensor nodes which have several multi-mode sensed modules. This work proposes an efficient node and sensed module management strategy, called ENSMM, for multisensory WSNs (wireless sensor networks). ENSMM considers not only node selection, but also the selection of the sensed modules for each node, and then the power management of sensor nodes is performed according to the selection results. Moreover, a joint weighted information utility measurement is proposed to estimate the information utility of the multiple sensed modules in the different nodes. Through extensive and realistic experiments, the results show that, ENSMM outperforms the state-of-the-art approaches by decreasing the energy consumption and prolonging the network lifetime. Meanwhile, it reduces the computational complexity with guaranteeing the tracking accuracy.

Event Based Data Gathering in Wireless Sensor Networks

2012 ◽  
pp. 445-462 ◽  
Author(s):  
Asfandyar Khan ◽  
Azween Abdullah ◽  
Nurul Hasan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Savings ◽  
Detection System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Detection Model ◽  
Physical Environments ◽  
Event Based

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.

scholarly journals Energy-Effective Data Gathering for UAV-Aided Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2506 ◽  
Author(s):  
Bin Liu ◽  
Hongbo Zhu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Trajectory Optimization ◽  
Energy Savings ◽  
Random Search ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Sensory Data ◽  
Transmission Modes ◽  
Transmission Energy Consumption

Unmanned aerial vehicles (UAVs) are capable of serving as a data collector for wireless sensor networks (WSNs). In this paper, we investigate an energy-effective data gathering approach in UAV-aided WSNs, where each sensor node (SN) dynamically chooses the transmission modes, i.e., (1) waiting, (2) conventional sink node transmission, (3) uploading to UAV, to transmit sensory data within a given time. By jointly considering the SN’s transmission policy and UAV trajectory optimization, we aim to minimize the transmission energy consumption of the SNs and ensure all sensory data completed collected within the given time. We take a two-step iterative approach and decouple the SN’s transmission design and UAV trajectory optimization process. First, we design the optimal SNs transmission mode policy with preplanned UAV trajectory. A dynamic programming (DP) algorithm is proposed to obtain the optimal transmission policy. Then, with the fixed transmission policy, we optimize the UAV’s trajectory from the preplanned trace with recursive random search (RRS) algorithm. Numerical results show that the proposed scheme achieves significant energy savings gain over the benchmark schemes.

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