Low energy aware communication process in IoT using the green computing approach

IET Networks ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 258-264 ◽  
Author(s):  
Suresh Kallam ◽  
Rajasekhara Babu Madda ◽  
Chi‐Yuan Chen ◽  
Rizwan Patan ◽  
Dhanaraj Cheelu
Keyword(s):  
Green Computing ◽  
Low Energy ◽  
Communication Process ◽  
Energy Aware ◽  
Computing Approach

scholarly journals An Energy Aware Multipath Routing Algorithm for Wireless Sensor Networks

2017 ◽  
Vol 13 (04) ◽  
pp. 45 ◽  
Author(s):  
Liping LV
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Path Selection ◽  
Low Energy ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Transmission Path

<p class="0abstract"><span lang="EN-US">Wireless sensor network is a new field of computer science and technology research. It has a very broad application prospects. In order to improve the network survival time, it is very important to design efficient energy-constrained routing protocols. In this paper, we studied the characteristics of wireless sensor networks, and analyzed the design criteria of sensor network routing algorithms. In view of the shortcomings of traditional algorithms, we proposed an energy-aware multi-path algorithm. When selecting a data transmission path, the energy-aware multi-path algorithm can avoid nodes with low energy levels. At the same time, it takes the remaining energy of the node and the number of hops as one of the measures of the path selection. The multi-path routing algorithm realized the low energy consumption of the data transmission path, thus effectively prolonging the network lifetime. Compared with the traditional algorithm, the results show that our method has high reliability and energy efficiency.</span></p>

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

Energy-Aware Schedules Under Chip Reliability Constraint for Multi-Processor Systems-on-a-Chip

2019 ◽  
Vol 29 (09) ◽  
pp. 2050135
Author(s):  
Hassan Salamy
Keyword(s):  
Low Energy ◽  
Objective Functions ◽  
Energy Aware ◽  
Embedded Computing ◽  
System Architectures ◽  
Energy Consumptions ◽  
Reliability Constraint ◽  
Power And Energy ◽  
Embedded Applications ◽  
Improve Reliability

Even though multi-core systems are effective architectures to overcome the limitation of single-core systems, techniques to improve reliability, throughput and power consumption are highly needed. With the increasing complexity of multi-processor systems-on-a-chip (MPSoCs) to handle the ever increasing complexity of embedded computing applications, the reliability of such systems is now a big concern in the industry. Complex MPSoCs typically have multiple execution modes with different throughput and reliability performances. These complex embedded systems are also expected to perform under minimum power and energy consumptions. In this paper, we present efficient techniques for low-energy and thermal-aware schedules that meet the deadlines under chip reliability constraints. The presented techniques under different objective functions are implemented and executed on multiple embedded applications under multiple underlying system architectures to show the performance and efficiency of the techniques.

scholarly journals Applications of Energy Aware Routing Protocols in WSN

2016 ◽  
Vol 9 (1) ◽  
pp. 24-29
Author(s):  
G Sumalatha ◽  
P Anil
Keyword(s):  
Routing Protocols ◽  
Low Energy ◽  
Sensor Systems ◽  
Coverage Problem ◽  
Energy Aware ◽  
Scarce Resources ◽  
Sensor Field ◽  
Energy Aware Routing

In this paper we have reviewed application of energy aware routing protocols like LEACH, LEACH-C, PEGASIS, BCDCP, ENPC-NPSO, ANPC etc In WSN sensors are randomly deployed in the sensor field which brings the coverage problem. Hence energy and coverage problem are very scarce resources for such sensor systems and has to be managed wisely in order to extend the life of the sensors and maximizing coverage for the duration of a particular mission. In past a lot of cluster based algorithm and techniques were used. In this paper we also find out all type of PSO based algorithm, their application and limitation over present techniques to overcome the problems of low energy and coverage of sensor range.

Intelligent Systems for Energy Management in Wireless Sensor-Based Smart Environments

2013 ◽  
pp. 156-180
Author(s):  
Blerim Qela ◽  
Hussein T. Mouftah
Keyword(s):  
Energy Conservation ◽  
Energy Management ◽  
Intelligent Systems ◽  
Optimal Solution ◽  
Green Computing ◽  
Wireless Sensor ◽  
Management Systems ◽  
Smart Environments ◽  
Energy Aware ◽  
Energy Management Systems

The purpose of this chapter is to explore and address the issues that are applicable to Smart Environments by encouraging and providing new insights towards the “Sustainable Green Computing” initiatives for “energy aware” applicable solutions. The topics covered in this chapter provide an introduction to future wireless sensor-based smart environments for energy management systems. Introduction to the topic, motivation, and objective are covered in Section 1. A review of the state-of-the-art technological achievements, theory, and applications, related to the energy management systems (wireless sensors and intelligent systems) are covered in Section 2. Whilst, Section 3 covers in detail the authors’ proposed methodological approach and main ideas leading towards the “Intelligent Systems for Energy Management in Wireless Sensor-Based Smart Environments.” Case studies of real-world applications, following the principles of “Green Computing” in intelligent systems are introduced. The authors present the simulation results of an “energy conservation perspective” in smart homes, demonstrating the potential improvements with respect to energy conservation. Moreover, they present examples of large Wireless Sensor Networks (WSN) simulations (impact of topology control in network survivability) and hybrid intelligent techniques for energy efficient solutions, i.e. finding optimal solution in a predefined interval. The conclusions and future research directions are provided in Sections 4 and 5, respectively.

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