scholarly journals Real Time Meteorological Solar Data Based Modified Solar Aware LEACH

2019 ◽  
Vol 8 (12) ◽  
pp. 3860-3868
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Network Performance ◽  
Meteorological Data ◽  
Vital Role ◽  
Wireless Sensor ◽  
Dense Network ◽  
Data Throughput ◽  
Improved Performance ◽  
And Performance

In hostile and non-accessible remote area, energy conservation plays vital role in the performance of Wireless Sensor Network (WSN). Shorter life of battery operated sensors tends to lower lifespan of the WSN which further degrades the dense network performance. In this paper, we propose the modified solar aware LEACH for efficient routing in WSN to maximize the network lifespan. This proposed scheme uses real time solar meteorological data for the implementation of solar aware LEACH (sLEACH), advance solar aware LEACH (AsLEACH), improved solar aware LEACH (IS-LEACH).The proposed algorithm is simulated using MATLAB and performance is evaluated on the basis of data throughput, energy consumption and network lifetime which show improved performance than existing techniques.

Performance Analysis of RNC Clustering Protocol in Wireless Sensor Network

2019 ◽  
Vol 10 ◽  
Author(s):  
Piyush Rawat ◽  
Siddhartha Chauhan
Keyword(s):  
Energy Consumption ◽  
Network Performance ◽  
Energy Levels ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Threshold Function ◽  
Efficient Manner ◽  
Clustering Protocol

Background and Objective: The functionalities of wireless sensor networks (WSN) are growing in various areas, so to handle the energy consumption of network in an efficient manner is a challenging task. The sensor nodes in the WSN are equipped with limited battery power, so there is a need to utilize the sensor power in an efficient way. The clustering of nodes in the network is one of the ways to handle the limited energy of nodes to enhance the lifetime of the network for its longer working without failure. Methods: The proposed approach is based on forming a cluster of various sensor nodes and then selecting a sensor as cluster head (CH). The heterogeneous sensor nodes are used in the proposed approach in which sensors are provided with different energy levels. The selection of an efficient node as CH can help in enhancing the network lifetime. The threshold function and random function are used for selecting the cluster head among various sensors for selecting the efficient node as CH. Various performance parameters such as network lifespan, packets transferred to the base station (BS) and energy consumption are used to perform the comparison between the proposed technique and previous approaches. Results and Discussion: To validate the working of the proposed technique the simulation is performed in MATLAB simulator. The proposed approach has enhanced the lifetime of the network as compared to the existing approaches. The proposed algorithm is compared with various existing techniques to measure its performance and effectiveness. The sensor nodes are randomly deployed in a 100m*100m area. Conclusion: The simulation results showed that the proposed technique has enhanced the lifespan of the network by utilizing the node’s energy in an efficient manner and reduced the consumption of energy for better network performance.

scholarly journals Optimizations for Energy Efficiency in Software-Defined Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4779
Author(s):  
Sorin Buzura ◽  
Bogdan Iancu ◽  
Vasile Dadarlat ◽  
Adrian Peculea ◽  
Emil Cebuc
Keyword(s):  
Energy Efficiency ◽  
Network Performance ◽  
Wireless Sensor ◽  
Management Approach ◽  
Control Plane ◽  
Data Broadcast ◽  
Data Packets ◽  
Similar Work ◽  
And Performance ◽  
The Individual

Software-defined wireless sensor networking (SDWSN) is an emerging networking architecture which is envisioned to become the main enabler for the internet of things (IoT). In this architecture, the sensors plane is managed by a control plane. With this separation, the network management is facilitated, and performance is improved in dynamic environments. One of the main issues a sensor environment is facing is the limited lifetime of network devices influenced by high levels of energy consumption. The current work proposes a system design which aims to improve the energy efficiency in an SDWSN by combining the concepts of content awareness and adaptive data broadcast. The purpose is to increase the sensors’ lifespan by reducing the number of generated data packets in the resource-constrained sensors plane of the network. The system has a distributed management approach, with content awareness being implemented at the individual programmable sensor level and the adaptive data broadcast being performed in the control plane. Several simulations were run on historical weather and the results show a significant decrease in network traffic. Compared to similar work in this area which focuses on improving energy efficiency with complex algorithms for routing, clustering, or caching, the current proposal employs simple computing procedures on each network device with a high impact on the overall network performance.

scholarly journals Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 13 ◽  
Author(s):  
Saeed Alsamhi ◽  
Ou Ma ◽  
M. Ansari ◽  
Sachin Gupta
Keyword(s):  
Wireless Communication ◽  
Real Time ◽  
Performance Optimization ◽  
Public Safety ◽  
Network Performance ◽  
Smart Cities ◽  
Vital Role ◽  
Efficient Manner ◽  
Safety Requirements ◽  
Critical Facilities

This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy.

scholarly journals Energy Consumption Estimation for Machining Processes Based on Real-time Shop Floor Monitoring via Wireless Sensor Networks

Procedia CIRP ◽  
2016 ◽  
Vol 57 ◽  
pp. 637-642 ◽  
Author(s):  
Dimitris Mourtzis ◽  
Ekaterini Vlachou ◽  
Nikolaos Milas ◽  
George Dimitrakopoulos
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensor ◽  
Shop Floor ◽  
Machining Processes

scholarly journals Fast Image-Based Ambient Occlusion IBAO

2011 ◽  
Vol 10 (4) ◽  
pp. 61-65
Author(s):  
Robert Sajko ◽  
Zeljka Mihajlovic
Keyword(s):  
Real Time ◽  
Sampling Method ◽  
Dynamic Scenes ◽  
Heuristic Function ◽  
Ambient Occlusion ◽  
Improved Performance ◽  
Straightforward Solution ◽  
And Performance ◽  
Screen Space

The quality of computer rendering and perception of realism greatly depend on the shading method used to implement the interaction of light with the surfaces of objects in a scene. Ambient occlusion (AO) enhances the realistic impression of rendered objects and scenes. Properties that make Screen Space Ambient Occlusion (SSAO) interesting for real-time graphics are scene complexity independence, and support for fully dynamic scenes. However, there are also important issues with current approaches: poor texture cache use, introduction of noise, and performance swings. In this paper, a straightforward solution is presented. Instead of a traditional, geometry-based sampling method, a novel, image-based sampling method is developed, coupled with a revised heuristic function for computing occlusion. Proposed algorithm harnessing GPU power improves texture cache use and reduces aliasing artifacts. Two implementations are developed, traditional and novel, and their comparison reveals improved performance and quality of the proposed algorithm.

scholarly journals Centralized Energy Prediction in Wireless Sensor Networks Leveraged by Software-Defined Networking

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5379
Author(s):  
Gustavo A. Nunez Segura ◽  
Cintia Borges Margi
Keyword(s):  
Wireless Sensor Networks ◽  
Markov Chain ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Performance ◽  
Resource Constraints ◽  
Software Defined Networking ◽  
Wireless Sensor ◽  
Prediction Algorithm ◽  
Energy Prediction

Resource Constraints in Wireless Sensor Networks are a key factor in protocols and application design. Furthermore, energy consumption plays an important role in protocols decisions, such as routing metrics. In Software-Defined Networking (SDN)-based networks, the controller is in charge of all control and routing decisions. Using energy as a metric requires such information from the nodes, which would increase packets traffic, impacting the network performance. Previous works have used energy prediction techniques to reduce the number of packets exchanged in traditional distributed routing protocols. We applied this technique in Software-Defined Wireless Sensor Networks (SDWSN). For this, we implemented an energy prediction algorithm for SDWSN using Markov chain. We evaluated its performance executing the prediction on every node and on the SDN controller. Then, we compared their results with the case without prediction. Our results showed that by running the Markov chain on the controller we obtain better prediction and network performance than when running the predictions on every node. Furthermore, we reduced the energy consumption for topologies up to 49 nodes for the case without prediction.

scholarly journals Optimizing Energy Consumption in IoT-Based Scalable Wireless Sensor Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 1-16
Author(s):  
Vinay Rishiwal ◽  
Preeti Yadav ◽  
Omkar Singh ◽  
B. G. Prasad
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Network Performance ◽  
Optimal Path ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Selection For

In recent era of IoT, energy ingesting by sensor nodes in Wireless Sensor Networks (WSN) is one of the key challenges. It is decisive to diminish energy ingesting due to restricted battery lifespan of sensor nodes, Objective of this research is to develop efficient routing protocol/algorithm in IoT based scenario to enhance network performance with QoS parameters. Therefore, keeping this objective in mind, a QoS based Optimized Energy Clustering Routing (QOECR) protocol for IoT based WSN is proposed and evaluated. QOECR discovers optimal path for sink node and provides better selection for sub-sink nodes. Simulation has been done in MATLAB to assess the performance of QOECR with pre-existing routing protocols. Simulation outcomes represent that QOECR reduces E2E delay 30%-35%, enhances throughput 25%-30%, minimizes energy consumption 35%-40%, minimizes packet loss 28%-32%, improves PDR and prolongs network lifetime 32%-38% than CBCCP, HCSM and ZEAL routing protocols.

scholarly journals A Novel Adjacent Sensors-Based Mechanism to Increase Performance of Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Mohammed Al-Shalabi ◽  
Jafar Ababneh ◽  
Waled Abdulraheem
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Performance ◽  
Environmental Parameters ◽  
Base Station ◽  
Decision Makers ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Leach Protocol ◽  
And Performance

Wireless Sensor Networks are widely used nowadays to support the decision-makers in different applications by monitoring and collecting the environmental parameters in specific areas. Sensors are deployed in such areas either randomly or formally. In a high-density Wireless Sensor Network, several sensors are randomly deployed in a small area. This will make the adjacent sensors collect same data and send them to the sink, which will increase the power consumption in those sensors. Adjacent sensors are considered critical because of their effect on the network performance. In this paper, the effect of the adjacent sensors is minimized because of the above-mentioned criticality and performance influence of these sensors. The proposed mechanism is evaluated by using MATLAB simulator and is then compared with the low-energy adaptive clustering hierarchy (LEACH) protocol. Results prove that the proposed mechanism outperforms the LEACH protocol by 21% in terms of the network lifetime and by 18% in terms of the number of the transmitted packets to the cluster heads and reduces the number of the transmitted packets to the base station by approximately 3% by avoiding the duplicated packets.

scholarly journals An Internet of Things Wireless Sensor Network Data Exchange Model Based on Hierarchical Address Automatic Configuration and Header Compression Encoding Strategy

2017 ◽  
Vol 13 (07) ◽  
pp. 140 ◽  
Author(s):  
Yuankun Yang ◽  
Yongqing Ji
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Real Time ◽  
Sensor Network ◽  
Data Exchange ◽  
Wireless Sensor ◽  
The Internet ◽  
Network Data ◽  
Sink Node

<p><span style="font-size: medium;"><span style="font-family: 宋体;">To explore the wireless sensor network data exchange model, an addressing strategy is applied to the Internet of Things, and the real-time communication between the underlying wireless sensor network and the Internet based on the IEEE 802.15.4 protocol is realized. In addition, Hierarchical address auto configuration strategy is adopted. First of all, inside the bottom network, it allows nodes to use link local address derived by 16-bit short address for data packet transmission. Secondly, Sink node in each underlying network accesses to the global routing prefix through the upper IP router, and combined with interface identifier, it forms Sink node global address, and realizes wireless sensor network and Internet data exchange. The research results show that the strategy has certain superiority in network cost, throughput, energy consumption and other performances. In summary, the proposed addressing strategy has the characteristics of effectively integrating heterogeneous networks, reducing system energy consumption, increasing network throughput and ensuring real-time system performance for the future Internet of things.</span></span></p>

scholarly journals A Trusted Real-Time Scheduling Model for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Weizhe Zhang ◽  
Boyu Song ◽  
Enci Bai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Real Time ◽  
Task Scheduling ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Bee Colony ◽  
Scheduling Model

Heterogeneous multicore and multiprocessor systems have been widely used for wireless sensor information processing, but system energy consumption has become an increasingly important issue. To ensure the reliable and safe operation of sensor systems, the task scheduling success rate of heterogeneous platforms should be improved, and energy consumption should be reduced. This work establishes a trusted task scheduling model for wireless sensor networks, proposes an energy consumption model, and adopts the ant colony algorithm and bee colony algorithm for the task scheduling of a real-time sensor node. Experimental result shows that the genetic algorithm and ant colony algorithm can efficiently solve the energy consumption problem in the trusted task scheduling of a wireless sensor and that the performance of the bee colony algorithm is slightly inferior to that of the first two methods.

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