scholarly journals AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4036 ◽  
Author(s):  
Muhammad K. Shahzad ◽  
S. M. Riazul Islam ◽  
Kyung-Sup Kwak ◽  
Lewis Nkenyereye
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Fitness Function ◽  
Dynamic Network ◽  
Key Distribution ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Aware

Static sink-based wireless sensor networks (WSNs) suffer from an energy-hole problem. This incurs as the rate of energy consumption on sensor nodes around sinks and on critical paths is considerably faster. State-of-the-art en-routing filtering schemes save energy by countering false report injection attacks. In addition to their unique limitations, these schemes generally do not examine energy awareness in underlying routing. Mostly, these security methods are based on a fixed filtering capacity, unable to respond to changes in attack intensity. Therefore, these limitations cause network partition(s), exhibiting adverse effects on network lifetime. Extending network lifetime while preserving energy and security thus becomes an interesting challenge. In this article, we address the aforesaid shortcomings with the proposed adaptive en-route filtering (AEF) scheme. In energy-aware routing, the fitness function, which is used to select forwarding nodes, considers residual energy and other factors as opposed to distance only. In pre-deterministic key distribution, keys are distributed based on the consideration of having paths with a different number of verification nodes. This, consequently, permits us to have multiple paths with different security levels that can be exploited to counter different attack intensities. Taken together, the integration of the special fitness function with the new key distribution approach enables the AEF to adapt the underlying dynamic network conditions. The simulation experiments under different settings show significant improvements in network lifetime.

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-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Parvinder Singh ◽  
Rajeshwar Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Large Scale ◽  
Fitness Function ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

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

2014 ◽  
Vol 5 (4) ◽  
pp. 39-51
Author(s):  
Carlos Abreu ◽  
P. M. Mendes
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
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%.

INERTIA PARTICLE SWARM OPTIMIZATION WITH DYNAMIC VELOCITY BASED CLUSTERING TECHNIQUE IN WIRELESS SENSOR NETWORKS

2021 ◽  
Vol 10 (1) ◽  
pp. 433-442
Author(s):  
R. Sathiya Priya ◽  
K. Arutchelvan ◽  
C. T. Bhuvaneswari
Keyword(s):  
Wireless Sensor Networks ◽  
Particle Swarm Optimization ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Fitness Function ◽  
Particle Swarm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Swarm Optimization ◽  
Clustering Technique

Wireless Sensor Networks (WSN) comprises a collection of nodes commonly employed to observe the physical environment. Different sensor nodes are linked to an inbuilt power unit to carry out necessary operations and data transmission between nearby nodes. The maximization of network lifetime and minimization of energy dissipation are considered as the major design issue of WSN. Clustering is a familiar energy efficient technique and the choice of optimal cluster heads (CHs) is considered as an NP hard problem. This paper presents an Inertia Particle Swarm Optimization algorithm with dynamic velocities (IPSO-DV) algorithm based clustering technique in WSN. The aim of the IPSO-DV technique is to select the CHs in such a way to maximize network lifetime. The IPSO-DV algorithm derives a fitness function (FF) to select CHs using distance to BS and remaining energy level. The application of dynamic velocities helps to improvise the effectiveness of the conventional PSO algorithm. To assure the performance of the presented IPSO-DV algorithm, a series of experiments were carried out and the results are investigated under several aspects. The experimentation outcome ensured the effective performance of the IPSO-DV algorithm over the compared clustering techniques.

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.

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).

scholarly journals Design and Performance Analysis of Energy Aware Routing Protocol for Delay Sensitive Applications for Wireless Sensor Networks

2013 ◽  
Vol 1 (2013) ◽  
pp. 46-53
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Selection Process ◽  
Optimal Path ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Aware ◽  
Efficient Manner ◽  
Efficient Operation

Wireless Sensor Networks (WSNs) are emerging network technology with innumerable applications. But security and energy constraints reduce its successful deployments. The nodes in network are greatly involved in transmissions and other processing operations for maintenance other than establishing or handling a call. Due to limited processing ability, storage capacity and most importantly the available battery power of the nodes, it is required to minimize the transmission power and the amount of data transmitted, for efficient operation. This paper presents a power aware routing protocol designed for wireless sensor networks. The proposed routing protocol is an extended and enhanced version of Dynamic Source Routing protocol. It adds energy awareness to the existing implementation of DSR protocol. Energy metric is considered during route selection process to choose an optimal path in terms of overall energy of the nodes along the path, and “low energy notification” method is used during route maintenance process to increase the lifetime of the bridge nodes to avoid network partitioning. The performance of DSR protocol and Energy Aware DSR (EADSR) protocol are compared through NS2 simulation under different scenarios. In all the cases, it is seen that EADSR protocol out-performs DSR protocol by energy saving in efficient manner

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2016 ◽  
pp. 79-114
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2020 ◽  
pp. 372-399
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

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