Analysis of Energy Consumption in Edge Router with Sleep Mode for Green OBS Networks

2013 ◽  
pp. 873-879 ◽  
Author(s):  
Wonhyuk Yang ◽  
Mohamed A. Ahmed ◽  
Ki-Beom Lee ◽  
Young-Chon Kim
Keyword(s):  
Energy Consumption ◽  
Sleep Mode ◽  
Edge Router

scholarly journals Delay versus energy consumption of the IEEE 802.16e sleep-mode mechanism

2009 ◽  
Vol 8 (11) ◽  
pp. 5383-5387 ◽  
Author(s):  
S. Vuyst ◽  
K. Turck ◽  
D. Fiems ◽  
S. Wittevrongel ◽  
H. Bruneel
Keyword(s):  
Energy Consumption ◽  
Sleep Mode ◽  
Ieee 802.16E

An Advanced Wireless Sensor Networks Design for Energy-Efficient Applications Using Condition-Based Access Protocol

2021 ◽  
pp. 171-186
Author(s):  
Vijendra Babu D. ◽  
K. Nagi Reddy ◽  
K. Butchi Raju ◽  
A. Ratna Raju
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Network Throughput ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Medium Access ◽  
Access Protocol ◽  
Battery Lifetime

A modern wireless sensor and its development majorly depend on distributed condition maintenance protocol. The medium access and its computing have been handled by multi hope sensor mechanism. In this investigation, WSN networks maintenance is balanced through condition-based access (CBA) protocol. The CBA is most useful for real-time 4G and 5G communication to handle internet assistance devices. The following CBA mechanism is energy efficient to increase the battery lifetime. Due to sleep mode and backup mode mechanism, this protocol maintains its energy efficiency as well as network throughput. Finally, 76% of the energy consumption and 42.8% of the speed of operation have been attained using CBI WSN protocol.

Adaptive Duty Cycle Medium Access Control Protocol for Wireless Sensor Networks

2016 ◽  
Vol 5 (2) ◽  
pp. 79
Author(s):  
Anand Babu
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Duty Cycle ◽  
Consumption Rate ◽  
Medium Access Control Protocol ◽  
Sleep Mode ◽  
Medium Access ◽  
Low Energy Consumption ◽  
Idle Listening ◽  
Energy Consumption Rate

<p>To increase the network lifetime of WSNs is a major concern. Network lifetime can be increased by reducing energy consumptions through MAC protocols periodic and a- periodic sleep mode mechanisms. The short duty cycle makes sensors have low energy consumption rate but increases the transmission delay and long duty cycle makes the sensor to increase the energy consumption and reduce the delay. Duty cycle need to be adaptively varied to reduce the idle listening. In the proposed Adaptive Duty cycle MAC (ADMAC) protocol, duty cycle is varied by taking nodes rate of energy consumption and filled queue length in account. It reduces the delay and energy spent by reducing the idle listening. ADMAC is realized in NS2 and its performance is compared with SMAC.</p>

scholarly journals An Energy-Efficient Distributed Dynamic Bandwidth Allocation Algorithm for Passive Optical Access Networks

2020 ◽  
Vol 12 (6) ◽  
pp. 2264 ◽  
Author(s):  
Hamzeh Khalili ◽  
David Rincón ◽  
Sebastià Sallent ◽  
José Ramón Piney
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Bandwidth Allocation ◽  
Access Networks ◽  
Dynamic Bandwidth Allocation ◽  
Sleep Mode ◽  
Optical Access Networks ◽  
Optical Access ◽  
Wide Range ◽  
Dynamic Bandwidth

The rapid deployment of passive optical access networks (PONs) increases the global energy consumption of networking infrastructure. This paper focuses on the minimization of energy consumption in Ethernet PONs (EPONs). We present an energy-efficient, distributed dynamic bandwidth allocation (DBA) algorithm able to power off the transmitter and receiver of an optical network unit (ONU) when there is no upstream or downstream traffic. Our main contribution is combining the advantages of a distributed DBA (namely, a smaller packet delay compared to centralized DBAs, due to less time being needed to allocate the transmission slot) with energy saving features (that come at a price of longer delays due to the longer queue waiting times when transmitters are switched off). The proposed algorithm analyzes the queue size of the ONUs in order to switch them to doze/sleep mode when there is no upstream/downstream traffic in the network, respectively. Our results show that we minimized the ONU energy consumption across a wide range of network loads while keeping delay bounded.

scholarly journals A new hybrid architecture with an intersection-based coverage algorithm in wireless sensor networks

2014 ◽  
Vol 11 (3) ◽  
pp. 1017-1035 ◽  
Author(s):  
Young-Long Chen ◽  
Mu-Yen Chen ◽  
Fu-Kai Cheung ◽  
Yung-Chi Chang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Hybrid Architecture ◽  
Power Efficient ◽  
Adaptive Clustering ◽  
Average Distribution

Energy is limited in wireless sensor networks (WSNs) so that energy consumption is very important. In this paper, we propose a hybrid architecture based on power-efficient gathering in sensor information system (PEGASIS) and low-energy adaptive clustering hierarchy (LEACH). This architecture can achieve an average distribution of energy loads, and reduced energy consumption in transmission. To further extend the system lifetime, we combine the intersection-based coverage algorithm (IBCA) with LEACH architecture and the hybrid architecture to prolong the system lifetime that introducing sensor nodes to enter sleep mode when inactive. This step can save more energy consumption. Simulation results show that the performance of our proposed LEACH architecture with IBCA and the hybrid architecture with IBCA perform better than LEACH architecture with PBCA in terms of energy efficiency, surviving nodes and sensing areas.

Optimization of Clustering in Wireless Sensor Networks Using Genetic Algorithm

2020 ◽  
pp. 822-836
Author(s):  
Pritee Parwekar ◽  
Sireesha Rodda
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Network ◽  
Sensor Node ◽  
Fitness Function ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Communication Distance ◽  
Selection Of

The energy of a sensor node is a major factor for life of a network in wireless sensor network. The depletion of the sensor energy is dependent on the communication range from the sink. Clustering is mainly used to prolong the life of a network with energy consumption. This paper proposes optimization of clustering using genetic algorithm which will help to minimize the communication distance. The cluster overhead and the active and sleep mode of a sensor is also considered while calculating the fitness function to form the cluster. This approach helps to prolong the network life of sensor network. The proposed work is tested for different number of nodes and is helping to find the correct solution for the selection of cluster heads.

scholarly journals An Energy-Efficient Task Scheduling Mechanism with Switching On/Sleep Mode of Servers in Virtualized Cloud Data Centers

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Chunxia Yin ◽  
Jian Liu ◽  
Shunfu Jin
Keyword(s):  
Energy Consumption ◽  
Task Scheduling ◽  
Data Center ◽  
Energy Efficient ◽  
Data Centers ◽  
Sleep Mode ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Response Performance

In recent years, the energy consumption of cloud data centers has continued to increase. A large number of servers run at a low utilization rate, which results in a great waste of power. To save more energy in a cloud data center, we propose an energy-efficient task-scheduling mechanism with switching on/sleep mode of servers in the virtualized cloud data center. The key idea is that when the number of idle VMs reaches a specified threshold, the server with the most idle VMs will be switched to sleep mode after migrating all the running tasks to other servers. From the perspective of the total number of tasks and the number of servers in sleep mode in the system, we establish a two-dimensional Markov chain to analyse the proposed energy-efficient mechanism. By using the method of the matrix-geometric solution, we mathematically estimate the energy consumption and the response performance. Both numerical and simulated experiments show that our proposed energy-efficient mechanism can effectively reduce the energy consumption and guarantee the response performance. Finally, by constructing a cost function, the number of VMs hosted on each server is optimized.

scholarly journals A Novel Hybrid HNN and Firefly Algorithm to Overcome Denial of Sleep Attack on Wireless Sensor Nodes

2021 ◽  
Vol 2 (4) ◽  
pp. 223-227
Author(s):  
Vivekanadam B
Keyword(s):  
Energy Consumption ◽  
Firefly Algorithm ◽  
Data Transfer ◽  
Hopfield Neural Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Wireless Sensor Nodes ◽  
Sleep Attack ◽  
Energy Consumption Patterns

A typical Wireless Sensor Network (WSN) comprises of multiple nodes that are used to control as well as monitor the environment and perform pre-described actions. Based on the network, the sensor nodes are distributed and their energy consumption proves to be challenging. When the nodes are located near the sink, they serve as the interface for data transfer between the sink and the node. Because of this, there is a decrease in the networks lifetime and further the energy consumption of the nodes increases significantly. Denial-of-sleep attack is a threat that sensor nodes face in WSNs. DoSA is the condition when there is much loss of energy at the nodes by preventing them from entering into sleep mode and power save mode. We propose a hybrid methodology of Hopfield neural network and firefly algorithm using leach to tackle this issue such that there is a significant increase in network lifetime and energy consumption patterns.

Optimization of Clustering in Wireless Sensor Networks Using Genetic Algorithm

2017 ◽  
Vol 8 (4) ◽  
pp. 84-98 ◽  
Author(s):  
Pritee Parwekar ◽  
Sireesha Rodda
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Network ◽  
Sensor Node ◽  
Fitness Function ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Communication Distance ◽  
Selection Of

The energy of a sensor node is a major factor for life of a network in wireless sensor network. The depletion of the sensor energy is dependent on the communication range from the sink. Clustering is mainly used to prolong the life of a network with energy consumption. This paper proposes optimization of clustering using genetic algorithm which will help to minimize the communication distance. The cluster overhead and the active and sleep mode of a sensor is also considered while calculating the fitness function to form the cluster. This approach helps to prolong the network life of sensor network. The proposed work is tested for different number of nodes and is helping to find the correct solution for the selection of cluster heads.

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