An Energy-Efficient Model for Opportunistic Data Collection in IoV-Enabled SC Waste Management

2021 ◽  
pp. 1-19
Author(s):  
Gerald K. Ijemaru ◽  
Ericmoore T. Ngharamike ◽  
Emmanuel U. Oleka ◽  
Augustine O. Nwajana
Keyword(s):  
Data Collection ◽  
Waste Management ◽  
Energy Efficient ◽  
Vehicular Networks ◽  
Access Point ◽  
High Energy ◽  
Sensor Nodes ◽  
Management Scenarios ◽  
Mobile Data Collectors ◽  
High Energy Consumption

Recent advancements in technological research have seen the use of mobile data collectors (MDCs) or data MULEs for wireless sensor network (WSN) applications. In the context of smart city (SC) waste management scenarios, vehicular networks or the internet of Vehicles (IoV) can be exploited as MDCs or data MULEs for data collection and transmission purposes from the sparsely distributed smart sensors that are attached to the smart bins to an access point or sink node and further deployed for waste management operations. A major challenge with the traditional methods of data collection using static sink nodes is the high energy consumption of the sensor-nodes. The use of MDCs has been well studied and shown to be energy efficient. To the best of the authors' knowledge, this scheme has not been exploited for waste management operations in a SC. Compared to the centralized schemes, the data MULE scheme presents several advantages for data collection in WSN applications. This chapter proposes an energy-efficient model for opportunistic data collection in IoV-enabled SC waste management operations.

scholarly journals The importance of energy efficient in wireless sensor networks

2019 ◽  
Vol 6 (6) ◽  
pp. 207-219
Author(s):  
Ellon Mask ◽  
Surgey Brown ◽  
Wood Lucky ◽  
Lorry Peter
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
High Energy ◽  
Mobile Node ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Level Energy ◽  
Mobile Nodes ◽  
Mobile Data ◽  
Mobile Data Collectors

Mobile Node-based routing is an efficient routing technique compared to traditional approaches. Due to this FERP majorly data isolation is provided for sensor nodes, and the network is more energy efficient. The Mobile data collector collects data from only Family heads and forwards to the cluster head. The Node level energy saving scheme is proposed in this work. The performance of this routing protocol is assessed based on Energy consumption, Throughput, Lifetime, Packet Delivery Ratio, Energy efficiency. Most of the Energy is saved due to the introducing of mobile nodes for data collection. Apart from this, we are reducing the load for mobile data collectors also. In general, mobile data collectors have high energy resources. But it is not possible in all terrains. This FERP gives better results in military and plateaus, and irregular terrains where multihop communication is complex. This work is further enhanced by Trust node based routing to improve the lifetime of the network.

Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 168-172
Author(s):  
Ravi Kumar Poluru ◽  
M. Praveen Kumar Reddy ◽  
Syed Muzamil Basha ◽  
Rizwan Patan ◽  
Suresh Kallam
Keyword(s):  
Network Lifetime ◽  
Routing Protocols ◽  
Energy Efficient ◽  
High Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Stability Period ◽  
Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

scholarly journals Office Interior: The Influence of Office Environmental Factors towards Task Performance

2018 ◽  
Vol 7 (3.32) ◽  
pp. 116
Author(s):  
Arita Hanim Awang ◽  
Zuraini Denan ◽  
Noor Hanita Abdul Majid
Keyword(s):  
Task Performance ◽  
Energy Efficient ◽  
High Energy ◽  
Office Workers ◽  
Related Field ◽  
Second Home ◽  
Environmental Setting ◽  
Environmental Air ◽  
Energy Efficient Building ◽  
High Energy Consumption

Office environment has become crucial in providing comfort for the workers and in maintaining the sustainability of an office.  Office environmental comfort is significant to office workers life as the office has become their second home. Almost half of the five working days were spend in the office.  Air conditioning and lighting are among the most significant contributors to high energy consumption in office building in Malaysia. In promoting an energy efficient building, consumption of electrical lighting and air condition in office from morning till evening requires an investigation. The aim of the research is to explore the environmental condition of office which occupied by design related field employees. The environmental air condition and lighting preference are among the significant variables tested.  A controlled experiment of a mock-up office with combination of those variables was conducted. The findings indicate that the office workers can still perform their task in extreme conditions which are low level of lighting below 200 lux with highest or lowest temperature between 16 to 32 Degree Celsius, however, the percentage of completion (POC) of the AutoCAD drafting task relatively decreasing. This scenarios show that the designers’ office environmental conditions have significant impact towards task performance. The optimum office environmental setting is needed in order to increase employee’s task performance.  

Secure Energy Efficient Data Collection Scheme Over Wireless Multimedia Sensor Networks

2016 ◽  
Vol 13 (10) ◽  
pp. 7375-7384
Author(s):  
Hyunsung Kim ◽  
Sung Woon Lee
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Data Collection ◽  
Energy Efficient ◽  
Wireless Multimedia Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Multimedia ◽  
Multimedia Sensor Networks ◽  
Efficient Data ◽  
Efficient Data Collection

A secure data collection in wireless multimedia sensor networks (WMSNs) has given attention to one of security issues. WMSNs pose unique security challenges due to their inherent limitations in communication and computing, which makes vulnerable to various attacks. For the energy efficiency, WMSNs adopt mobile sinks to collect data from sensor nodes. Thus, how to gather data securely and efficiently is an important issue WMSNs. In this paper, we propose a secure energy efficient data collection scheme over WMSNs, which are based on Bilinear pairing and symmetric key cryptosystem. First of all, we devise a security model based on a hierarchical key structure for the security mechanisms, authentication, key agreement, confidentiality, and integrity. Based on the model, we propose a secure energy efficient data collection scheme, which could establish secure session in one round. The proposed scheme could efficiently remedy security and efficiency problems in the previous data collection schemes over WMSNs. It has only about 18% of overhead for the security but also has energy efficiency compared with the other related schemes.

scholarly journals Ping-Pong Free Advanced and Energy Efficient Sensor Relocation for IoT-Sensory Network

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5654
Author(s):  
Moonseong Kim ◽  
Sooyeon Park ◽  
Woochan Lee
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Energy Efficient ◽  
Essential Role ◽  
Sensor Nodes ◽  
Ping Pong ◽  
Iot Devices ◽  
Artificial Network ◽  
Specific Cluster ◽  
Big Data Technology

With the growing interest in big data technology, mobile IoT devices play an essential role in data collection. Generally, IoT sensor nodes are randomly distributed to areas where data cannot be easily collected. Subsequently, when data collection is impossible (i.e., sensing holes occurrence situation) due to improper placement of sensors or energy exhaustion of sensors, the sensors should be relocated. The cluster header in the sensing hole sends requests to neighboring cluster headers for the sensors to be relocated. However, it can be possible that sensors in the specific cluster zones near the sensing hole are continuously requested to move. With this knowledge, there can be a ping-pong problem, where the cluster headers in the neighboring sensing holes repeatedly request the movement of the sensors in the counterpart sensing hole. In this paper, we first proposed the near-uniform selection and movement scheme of the sensors to be relocated. By this scheme, the energy consumption of the sensors can be equalized, and the sensing capability can be extended. Thus the network lifetime can be extended. Next, the proposed relocation protocol resolves a ping-pong problem using queues with request scheduling. Another crucial contribution of this paper is that performance was analyzed using the fully-customed OMNeT++ simulator to reflect actual environmental conditions, not under over-simplified artificial network conditions. The proposed relocation protocol demonstrates a uniform and energy-efficient movement with ping-pong free capability.

OPTIMAL WINDOW GEOMETRY FACTORS FOR ELEMENTARY SCHOOL BUILDINGS IN PORTUGAL

2018 ◽  
Vol 13 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Jorge S. Carlos
Keyword(s):  
Energy Efficient ◽  
Energy Savings ◽  
High Energy ◽  
Building Envelope ◽  
Major Influence ◽  
Thermal Discomfort ◽  
Building Component ◽  
U Value ◽  
High Energy Consumption ◽  
Optimal Window

INTRODUCTION With respect to thermal performance, windows are the weakest component of the building envelope, essentially because the U-value is usually higher than the opaque envelope. This would allow the highest heat conductance of the building envelope. However, it also helps buildings to gain useful solar heat during winter. Therefore, it has been generally accepted that passive buildings would have small windows towards the poles and large windows facing the equator (Persson, Roos, and Wall 2006). In spite of this guideline, large or fully glazed facades have been used in modern architecture. The intensive use of air conditioning is the result of overheating and high thermal loss problems, which otherwise would lead to thermal discomfort. This extensive use of large windows associated with high energy consumption has motivated researchers to study this building component. Window areas were investigated by Persson et al. (Persson, Roos, and Wall 2006) on 20 terraced houses with larger windows facing the equator and built in Gothenburg. The building envelope was well insulated and fitted with energy efficient windows. It was found that energy efficient windows do not have a major influence on the heating demand in the winter, but it is relevant for the cooling need in summer. Therefore, reduced indoor illuminance due to small windows can be solved by enlarging them in order to obtain relevant daylighting conditions. When efficient windows are designed for a warm climate, as in Mexico, reducing heat flux and solar transmittance indoors was the best option for energy savings (Aguilar et al. 2017). However, reducing solar transmittance influences the indoor illuminance, which was not analyzed.

The Energy Conservation Analysis and Transformation Technology for Flat Roofs of Existing Buildings in Zhengzhou

2011 ◽  
Vol 71-78 ◽  
pp. 1824-1830
Author(s):  
Yi Zhong Zhang ◽  
Chao Yan
Keyword(s):  
Energy Conservation ◽  
Energy Efficient ◽  
High Energy ◽  
Building Construction ◽  
Existing Buildings ◽  
Insulating Materials ◽  
Conservation Analysis ◽  
Energy Conservation Measures ◽  
Flat Roofs ◽  
High Energy Consumption

For the construction of a building was insulated and energy efficient effect, zhengzhou have evaluated the building, construction and the flat roofs structure raging indicators and energy conservation of heat transfer is far below the effect of the relevant provisions. In the heat of the environment, the building runs high energy consumption, raise the roof insulating structure of the insulator, "flat" to "slope" and adopt a ceiling on the roof insulating materials of energy conservation measures for reforming and feasibility of energy conservation raging technical analysis.

scholarly journals An Improved GPSR Algorithm Based on Energy Gradient and APIT Grid

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Zhuang Liu ◽  
Xin Feng ◽  
Jingjing Zhang ◽  
Teng Li ◽  
Yanlong Wang
Keyword(s):  
Energy Consumption ◽  
Greedy Algorithm ◽  
Routing Algorithm ◽  
High Energy ◽  
Sensor Nodes ◽  
Target Area ◽  
Localization Algorithm ◽  
Right Hand ◽  
Energy Gradient ◽  
High Energy Consumption

We investigate GPSR algorithms of WSN and propose an improved routing algorithm based on energy gradient and APIT grid to solve the problem of high and unbalanced energy consumption of GPSR. In GPSR, network uses greedy algorithm and right-hand rule to establish routing paths, and the path keeps running till some nodes within the path are invalid because energy is exhausted, which would lead to the high energy consumption of some nodes in the path and the low energy consumption of others nearby the nodes not in the path as well as bringing high and unbalanced energy consumption of the network. Regarding these problems, we use APIT localization algorithm and APIT grid to query and establish routing paths and establish the corresponding energy gradient when messages are transmitted along the routing paths. When some nodes are approaching the threshold status, we use right-hand rule and recursion greedy algorithm in advance to plan a new routing path towards the target area. When query messages arrive at the event area, the network uses a different method to transmit data according to the density of sensor nodes. Simulation experiments show that the improved routing algorithm is capable of reducing the energy consumption of network and extending the lifecycle of network.

scholarly journals A Hybrid Prediction Model for Energy-Efficient Data Collection in Wireless Sensor Networks

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2024
Author(s):  
Seyed Ahmad Soleymani ◽  
Shidrokh Goudarzi ◽  
Nazri Kama ◽  
Saiful Adli Ismail ◽  
Mazlan Ali ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Data Collection ◽  
Data Transmission ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Sampling ◽  
Efficient Data ◽  
Efficient Data Collection

Energy consumption because of unnecessary data transmission is a significant problem over wireless sensor networks (WSNs). Dealing with this problem leads to increasing the lifetime of any network and improved network feasibility for real time applications. Building on this, energy-efficient data collection is becoming a necessary requirement for WSN applications comprising of low powered sensing devices. In these applications, data clustering and prediction methods that utilize symmetry correlations in the sensor data can be used for reducing the energy consumption of sensor nodes for persistent data collection. In this work, a hybrid model based on decision tree (DT), autoregressive integrated moving average (ARIMA), and Kalman filtering (KF) methods is proposed to predict the data sampling requirement of sensor nodes to reduce unnecessary data transmission. To perform data sampling predictions in the WSNs efficiently, clustering and data aggregation to each cluster head are utilized, mainly to reduce the processing overheads generating the prediction model. Simulation experiments, comparisons, and performance evaluations conducted in various cases show that the forecasting accuracy of our approach can outperform existing Gaussian and probabilistic based models to provide better energy efficiency due to reducing the number of packet transmissions.

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