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 Intelligent Routing Algorithm in Wireless Sensor Networks Based on Reinforcement Learning

2014 ◽  
Vol 678 ◽  
pp. 487-493 ◽  
Author(s):  
Wen Jing Guo ◽  
Cai Rong Yan ◽  
Yang Lan Gan ◽  
Ting Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Hop Count ◽  
Packet Delivery ◽  
Intelligent Routing

Lifetime enhancement has been a hot issue in Wireless Sensor Networks (WSNs). To prolong the network lifetime of WSNs, this paper proposes an intelligent routing algorithm named RLLO. RLLO makes uses of the superiority of reinforcement learning (RL) and considers residual energy and hop count to define the reward function. It is to uniformly distribute the energy consumption and improve the packet delivery without additional cost. This proposed algorithm has been compared with Energy Aware Routing (EAR) and improved EAR (I-EAR). Simulation results show that RLLO gains a significant improvement in terms of network lifetime and packet delivery over these two algorithms.

An Energy Balancing Cross Layer Scheme for Long Lifetime Wireless Sensor Networks

2015 ◽  
Vol 764-765 ◽  
pp. 827-831
Author(s):  
Yung Fa Huang ◽  
Tan Hsu Tan ◽  
Yau Der Wang ◽  
Young Long Chen ◽  
Neng Chung Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Energy Balancing ◽  
Energy Aware

In this paper, we propose an improved routing algorithm to prolong network lifetime of wireless sensor networks (WSNs) by combining the shortest hop routing tree (SHORT) algorithm and the, turn off redundant node (TORN) MAC layer protocol to cross layer SHORTORN scheme. Moreover, to prolong the lifetime of the first node death (FND) in networks, the rate of energy consumption should be balanced for all nodes. Therefore, this paper further proposes a load balancing SHORTORN scheme by combining the weight and energy-aware, called energy-aware weight-based SHORTORN (EWSHORTORN). The proposed EWSHORTORN algorithm lets more nodes share the load of the leader and balances the opportunity of data relaying to all nodes. The proposed load balancing scheme allocates energy consumption load to be more uniformly among all nodes, thus the FNL can be prolonged evidently. Simulation results show that the proposed EWSHORTORN outperforms the SHORT scheme with double lifetime of FND.Keywords: wireless sensor networks, network lifetime, cross layer protocol, load balance.

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>

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 Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianpo Li ◽  
Xue Jiang ◽  
I-Tai Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Virtual Mimo ◽  
Head Node

Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

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