Network Lifetime Enhancement in Wireless Sensor Networks using Energy Aware Clustering with Fuzzy System

2020 ◽  
Vol 14 (5) ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Fuzzy System ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Lifetime Enhancement

scholarly journals Energy Aware Simple Ant Routing Algorithm for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Sohail Jabbar ◽  
Rabia Iram ◽  
Muhammad Imran ◽  
Awais Ahmad ◽  
Anand Paul ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Large Scale ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Route Discovery ◽  
Route Selection ◽  
Energy Aware ◽  
Forwarding Node

Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

scholarly journals Improved continuous enhancement routing solution for energy-aware data aggregation in wireless sensor networks

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877468 ◽  
Author(s):  
Edson Ticona-Zegarra ◽  
Rafael CS Schouery ◽  
Leandro A Villas ◽  
Flávio K Miyazawa
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Energy State ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Network Nodes ◽  
Battery Energy ◽  
Routing Tree

Wireless sensor networks consist of hundreds or thousands of nodes with limited energy resources, and thus, efficient use of energy is necessary for these networks. Given that transmissions are the most energy-demanding operation, routing algorithms should consider efficient use of transmissions in their designs in order to extend the network lifetime. To tackle these challenges, a centralized algorithm is proposed, called improved continuous enhancement routing (ICER), for computing routing trees of refined quality, based on data aggregation while being aware of the battery energy state. Comparisons between ICER and other known solutions in the literature are performed. Our experiments show that ICER is able to ensure, on average, the survival of 99.6% and the connectivity of 99.3% of the network nodes compared to 90.2% and 72.4% in relation to the best-compared algorithm. The obtained results show that ICER significantly extends the network lifetime while maintaining the quality of the routing tree.

scholarly journals Adaptive Dual-Mode Routing-Based Mobile Data Gathering Algorithm in Rechargeable Wireless Sensor Networks for Internet of Things

2020 ◽  
Vol 10 (5) ◽  
pp. 1821 ◽  
Author(s):  
Liangrui Tang ◽  
Haobo Guo ◽  
Runze Wu ◽  
Bing Fan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Network Lifetime ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Dual Mode ◽  
Energy Aware ◽  
Mobile Data ◽  
Mobile Data Gathering

Great improvement recently appeared in terms of efficient service delivery in wireless sensor networks (WSNs) for Internet of things (IoT). The IoT is mainly dependent on optimal routing of energy-aware WSNs for gathering data. In addition, as the wireless charging technology develops in leaps and bounds, the performance of rechargeable wireless sensor networks (RWSNs) is greatly ameliorated. Many researches integrated wireless energy transfer into data gathering to prolong network lifetime. However, the mobile collector cannot visit all nodes under the constraints of charging efficiency and gathering delay. Thus, energy consumption differences caused by different upload distances to collectors impose a great challenge in balancing energy. In this paper, we propose an adaptive dual-mode routing-based mobile data gathering algorithm (ADRMDGA) in RWSNs for IoT. The energy replenishment capability is reasonably allocated to low-energy nodes according to our objective function. Furthermore, the innovative adaptive dual-mode routing allows nodes to choose direct or multi-hop upload modes according to their relative upload distances. The empirical study confirms that ADRMDGA has excellent energy equilibrium and effectively extends the network lifetime.

scholarly journals proposing a new clustering algorithm to Reduction of Energy Consumption using Fuzzy Logic and Genetic Algorithm for Wireless Sensor Networks.

2016 ◽  
Vol 11 (2) ◽  
pp. 2702-2719
Author(s):  
Sayyed Hedayat Tarighi Nejad ◽  
Reza Alinaghian ◽  
Mehdi Sadeghzadeh
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Fuzzy System ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Reduction Of Energy Consumption

The large-scale deployment of wireless sensor networks  and the need for data aggregation necessitate efficient organization of the network topology for the purpose of balancing the load and prolonging the network lifetime. Clustering is one of the important methods for prolonging the network lifetime in wireless sensor networks. It involves grouping of sensor nodes into clusters and electing cluster heads for all the clusters. Clustering has proven to be an effective approach for organizing the network into a connected hierarchy.In this paper, using fuzzy system design and system optimization by genetic algorithm and colony of ants is presented approach to select the best cluster head in sensor networks. Using design and simulation a sensor network has been addressed to evaluation the presented fuzzy system in this paper, and finally the amount of energy consumption using proposed fuzzy system in comparison with LEACH method is calculated in select the cluster head. The result of evaluations is representative of a reduction of energy consumption in the proposed method in comparison with LEATCH method for select the cluster head. The reduction of energy consumption directly is effective on lifetime of wireless sensor network and can cause increase the lifetime these networks.

Extending Lifetime of Biomedical Wireless Sensor Networks using Energy-Aware Routing and Relay Nodes

2018 ◽  
pp. 714-726
Author(s):  
Carlos Abreu ◽  
Paulo M. Mendes
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Healthcare Services ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Relay Nodes ◽  
Energy Aware Routing

Biomedical wireless sensor networks are a key technology to enable the development of new healthcare services and/or applications, reducing costs and improving the citizen's quality of life. However, since they deal with health data, such networks should implement mechanisms to enforce high levels of quality of service. In most cases, the sensor nodes that form such networks are small and battery powered, and these extra quality of service mechanisms mean significant lifetime reduction due to the extra energy consumption. The network lifetime is thus a relevant feature to ensure the necessary quality of service requirements. In order to maximise the network lifetime, and its ability to offer the required quality of service, new strategies are needed to increase the energy efficiency, and balance in the network. The focus of this work goes to the effective use of the available energy in each node, combined with information about the reliability of the wireless links, as a metric to form reliable and energy-aware routes throughout the network. This paper present and discusses two different deployment strategies using energy-aware routing and relay nodes, assessed for different logical topologies. The authors' conclusion is that the use of energy-aware routing combined with strategic placed relay nodes my increase the network lifetime as high as 45%.

Sign in / Sign up

Export Citation Format

Share Document