scholarly journals An Energy Efficient Data Transfer Mechanism for Wireless Sensor Network

2013 ◽  
Vol 6 (3) ◽  
pp. 359-369
Author(s):  
Partha Pratim Bhattacharya ◽  
Jyoti Saraswat
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Data Transfer ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Level Energy ◽  
Data Packets ◽  
Traffic Pattern ◽  
Efficient Data ◽  
Correlated Information

Wireless Sensor Networks (WSNs) are generally energy and resource constrained. In most WSN applications the traffic pattern is from sensor-to-sink and for effective utilization of available resources in network data aggregation is employed. If a data packet is lost due to node failure or collision the correlated information content by data packets is lost. Existing protocols that provide reliable data transfer for sensor-to-sink traffic are either not energy efficient or they provide reliability at the event level. Energy efficiency can be improved by employing proper duty cycle values. By extending the concept of monitors the proposed protocol provides packet level reliability and improves the energy efficiency by employing duty cycles. To further decrease the energy consumption only a subset of nodes is chosen as active nodes to transfer the data. The performance of the proposed protocol is evaluated using Matlab. Results show that protocol has significant improvement in terms of energy saving, throughput and packet delivery ratio.

scholarly journals A Reliable Energy Efficient Data Aggregation Algorithm for Wireless Sensor Network

2020 ◽  
Vol 9 (9) ◽  
pp. 686-691
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Cluster Head ◽  
Life Time ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Data Packets ◽  
Efficient Data

One of the popular and emerging networks is wireless sensor networks (WSN), where it comprises of an unlimited number of sensors deployed dynamically and irregularly in a geolocation, for a specific purpose. Each sensor node in the network sense, collect and transmit the environmental data from one location to other location. All the nodes have the capabilities of transmitting and receiving the documents. The major problem in WSN is energy efficiency and network lifetime. By reducing the energy consumption, the network life time can be increased. Clustering, scheduling and other related methods are used to reduce the energy consumption, during the data transmission and receiving. This paper proposed a Reliable Energy Efficient Data Aggregation (REEDA) method for improving the energy efficiency. All the common nodes or the cluster head nodes gather, aggregate, and transmit the data where it reduces the energy consumption. The aggregation method is applied according to correlation of data packets generated by entire node. Simulations results prove that the proposed algorithm provides a good solution for minimizing communication and computation cost.

scholarly journals Energy-Efficient Asynchronous QoS MAC Protocol for Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Sohail Sarang ◽  
Goran M. Stojanović ◽  
Stevan Stankovski ◽  
Željen Trpovski ◽  
Micheal Drieberg
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Mac Protocol ◽  
Mac Protocols ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Data Packets ◽  
Packet Delivery ◽  
Different Types ◽  
Network Operation

In recent years, wireless sensor networks (WSNs) have gained significant attention in both industry and academia. In WSNs, each sensor node is normally equipped with a small-size battery with finite capacity. Hence, energy-efficient communication is considered a key factor for the extension of network lifetime. Formerly, a large number of medium access control (MAC) protocols have been proposed to improve energy efficiency to prolong the network lifetime. There are applications that generate different types of data packets and require quality of service (QoS) without any disruption in network operation. Therefore, these applications need an energy-efficient QoS MAC protocol that can support QoS by considering energy efficiency as the primary goal to avoid any failure in the network. This article proposes an energy-efficient asynchronous QoS (AQSen) MAC protocol, called AQSen-MAC. The AQSen-MAC considers different types of data packets and uses two novel techniques: self-adaptation and scheduling to enhance energy efficiency, packet delivery ratio, and network throughput. Furthermore, in the protocol, the receiver adjusts its duty cycle according to the remaining energy to prolong the network operation. Finally, the performance of the AQSen-MAC protocol has been evaluated through detailed simulation using Castalia and compared with MPQ-MAC, PMME-MAC, and QAEE-MAC protocols. The simulation results indicate that the AQSen-MAC protocol significantly reduces the energy consumption at the receiver of up to 13.4%, consumption per bit of up to 3% and improves the packet delivery ratio and network throughput of up to 12% in the network.

Reliable and Energy-Efficient Routing Scheme for Underwater Wireless Sensor Networks (UWSNs)

2021 ◽  
Vol 11 (4) ◽  
pp. 42-58
Author(s):  
Semab Iqbal ◽  
Israr Hussain ◽  
Zubair Sharif ◽  
Kamran Hassan Qureshi ◽  
Javeria Jabeen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Transmission Error ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Underwater Communication ◽  
Radio Waves ◽  
Energy Efficient Routing ◽  
Resource Exploration

Despite the fact that the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Underwater wireless sensor network (UWSN) is one of the options helping us to discover some domains such as natural assets and underwater resource exploration. However, the acoustic signal is the only suitable option in underwater communication in the absence of radio waves, which face a number of challenges under this environment. To overcome these issues, many routing schemes are introduced by researchers though energy consumption is still a challenge in underwater communication. To overcome the issue of rapid energy consumption, a reliable and energy-efficient routing method is introduced that avoids the redundant forwarding of data; hence, it achieves energy efficiency and eventually prolongs the network lifetime. Simulation results support the claim that the proposed scheme achieves energy efficiency along higher delivery ratio by reducing the data transmission error rate during the routing decisions.

An Energy Efficiency Task Allocation Method Based on Reasoning Model in Wireless Sensor Network

2011 ◽  
Vol 268-270 ◽  
pp. 440-445
Author(s):  
Wang Lan Tian ◽  
Hong Yan Lei
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Task Allocation ◽  
Energy Efficient ◽  
Negotiation Process ◽  
Energy Threshold ◽  
Wireless Sensor ◽  
Level Energy ◽  
Allocation Model

In this paper, a reasoning model is proposed for energy efficiency task allocation in wireless sensor network. The presented energy efficient contract net protocol is used to implement the negotiation process. Multi-issue scoring function can evaluate the offer with multi-issues in a quantifiable way. An energy threshold is brought to decrease communications which will turn out to decrease nodes’ energy consumption. And the usage of energy threshold also promote the nodes with high level energy have more chance to implement tasks. The simulation results show that the allocation model has outstanding performance maintaining a fair energy balance and is energy efficient in negotiation process.

scholarly journals Energy-Efficient Depth-Based Opportunistic Routing with Q-Learning for Underwater Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1025 ◽  
Author(s):  
Yongjie Lu ◽  
Rongxi He ◽  
Xiaojing Chen ◽  
Bin Lin ◽  
Cunqian Yu
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Opportunistic Routing ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Q Value ◽  
Underwater Wireless Sensor Networks ◽  
Q Learning ◽  
Packet Delivery ◽  
Network Overhead

Underwater Wireless Sensor Networks (UWSNs) have aroused increasing interest of many researchers in industry, military, commerce and academe recently. Due to the harsh underwater environment, energy efficiency is a significant theme should be considered for routing in UWSNs. Underwater positioning is also a particularly tricky task since the high attenuation of radio-frequency signals in UWSNs. In this paper, we propose an energy-efficient depth-based opportunistic routing algorithm with Q-learning (EDORQ) for UWSNs to guarantee the energy-saving and reliable data transmission. It combines the respective advantages of Q-learning technique and opportunistic routing (OR) algorithm without the full-dimensional location information to improve the network performance in terms of energy consumption, average network overhead and packet delivery ratio. In EDORQ, the void detection factor, residual energy and depth information of candidate nodes are jointly considered when defining the Q-value function, which contributes to proactively detecting void nodes in advance, meanwhile, reducing energy consumption. In addition, a simple and scalable void node recovery mode is proposed for the selection of candidate set so as to rescue packets that are stuck in void nodes unfortunately. Furthermore, we design a novel method to set the holding time for the schedule of packet forwarding base on Q-value so as to alleviate the packet collision and redundant transmission. We conduct extensive simulations to evaluate the performance of our proposed algorithm and compare it with other three routing algorithms on Aqua-sim platform (NS2). The results show that the proposed algorithm significantly improve the performance in terms of energy efficiency, packet delivery ratio and average network overhead without sacrificing too much average packet delay.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

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