scholarly journals Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Haleem Farman ◽  
Huma Javed ◽  
Jamil Ahmad ◽  
Bilal Jan ◽  
Muhammad Zeeshan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Hybrid Network ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Grid Based ◽  
Efficient Consumption

Wireless sensor networks (WSN) empower applications for critical decision-making through collaborative computing, communications, and distributed sensing. However, they face several challenges due to their peculiar use in a wide variety of applications. One of the inherent challenges with any battery operated sensor is the efficient consumption of energy and its effect on network lifetime. In this paper, we introduce a novel grid-based hybrid network deployment (GHND) framework which ensures energy efficiency and load balancing in wireless sensor networks. This research is particularly focused on the merge and split technique to achieve even distribution of sensor nodes across the grid. Low density neighboring zones are merged together whereas high density zones are strategically split to achieve optimum balance. Extensive simulations reveal that the proposed method outperforms state-of-the-art techniques in terms of load balancing, network lifetime, and total energy consumption.

scholarly journals Cluster Head Relocation Based on Selfish Herd Hypothesis for Prolonging the Life Span of Wireless Sensor Networks

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 403 ◽  
Author(s):  
Goran Popovic ◽  
Goran Djukanovic ◽  
Dimitris Kanellopoulos
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Network Performance ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Selfish Herd

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed of several sensor nodes, one of them selected as the cluster head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. In such a hierarchical WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. The mobility of sensor nodes can improve network performance and prolong network lifetime. This paper presents the idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network is reduced and the network lifetime is extended. The positioning of CHs is made in each round based on a selfish herd hypothesis, where the leader retreats to the center of gravity. Based on this idea, the CH-active algorithm is proposed in this study. Simulation results show that this algorithm has benefits in terms of network lifetime and in the prolongation of the duration of network stability period.

scholarly journals Nonuniform Grid-Based Coordinated Routing in Wireless Sensor Networks

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Robert Akl ◽  
Priyanka Kadiyala ◽  
Mohamad Haidar
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Path Loss ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nonuniform Grid ◽  
Uniform Grids ◽  
Grid Based

A nonuniform grid-based coordinated routing design in wireless sensor networks is presented. The conditions leading to network partition and analysis of energy consumption that prolongs the network lifetime are studied. We focus on implementing routing in densely populated sensor networks. By maintaining constant values for parameters such as path loss exponent, receiver sensitivity and transmit power, and varying between uniform and non-uniform grids, we observe energy consumption patterns for each of the grid structures and infer from the network lifetime the better suited grids for uniformly and randomly deployed sensor nodes.

Event Based Data Gathering in Wireless Sensor Networks

2012 ◽  
pp. 445-462 ◽  
Author(s):  
Asfandyar Khan ◽  
Azween Abdullah ◽  
Nurul Hasan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Savings ◽  
Detection System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Detection Model ◽  
Physical Environments ◽  
Event Based

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.

scholarly journals Energy Efficient Trust Node Based Routing Protocol (EETRP) to Maximize the Lifetime of Wireless Sensor Networks in Plateaus

2019 ◽  
Vol 15 (06) ◽  
pp. 113 ◽  
Author(s):  
Nandoori Srikanth ◽  
Muktyala Sivaganga Prasad
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Mobile Nodes ◽  
Energy Limitation

<p>Wireless Sensor Networks (WSNs) can extant the individual profits and suppleness with regard to low-power and economical quick deployment for numerous applications. WSNs are widely utilized in medical health care, environmental monitoring, emergencies and remote control areas. Introducing of mobile nodes in clusters is a traditional approach, to assemble the data from sensor nodes and forward to the Base station. Energy efficiency and lifetime improvements are key research areas from past few decades. In this research, to solve the energy limitation to upsurge the network lifetime, Energy efficient trust node based routing protocol is proposed. An experimental validation of framework is focused on Packet Delivery Ratio, network lifetime, throughput, energy consumption and network loss among all other challenges. This protocol assigns some high energy nodes as trusted nodes, and it decides the mobility of data collector.  The energy of mobile nodes, and sensor nodes can save up to a great extent by collecting data from trusted nodes based on their trustworthiness and energy efficiency.  The simulation outcome of our evaluation shows an improvement in all these parameters than existing clustering and Routing algorithms.<strong></strong></p>

Performance Analysis of Multi-Hop Routing Protocol With Optimized Grid-Based Clustering for Wireless Sensor Network

2020 ◽  
pp. 254-282
Author(s):  
Saloni Dhiman ◽  
Deepti Kakkar ◽  
Gurjot Kaur
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Performance Analysis ◽  
Sensor Network ◽  
Routing Protocol ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Grid Based

Wireless sensor networks (WSNs) consist of several sensor nodes (SNs) that are powered by battery, so their lifetime is limited, which ultimately affects the lifespan and hence performance of the overall networks. Till now many techniques have been developed to solve this problem of WSN. Clustering is among the effective technique used for increasing the network lifespan. In this chapter, analysis of multi-hop routing protocol based on grid clustering with different selection criteria is presented. For analysis, the network is divided into equal-sized grids where each grid corresponds to a cluster and is assigned with a grid head (GH) responsible for collecting data from each SN belonging to respective grid and transferring it to the base station (BS) using multi-hop routing. The performance of the network has been analyzed for different position of BS, different number of grids, and different number of SNs.

scholarly journals Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Baniata ◽  
Jiman Hong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Chain Length ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Smart Cities ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities. These advances are also helping to monitor smart cities and making our living environments workable. However, sensor nodes are constrained in energy supply if they have no constant power supply. Moreover, communication links can be easily failed because of unequal node energy depletion. The energy constraints and link failures affect the performance and quality of the sensor network. Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN. In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime. Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.

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 An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

Lifetime Maximization Routing Based on Genetic Algorithm for Wireless Sensor Networks

2011 ◽  
Vol 230-232 ◽  
pp. 283-287
Author(s):  
You Rong Chen ◽  
Tiao Juan Ren ◽  
Zhang Quan Wang ◽  
Yi Feng Ping
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Gathering ◽  
Transmission Probability ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Lifetime Maximization

To prolong network lifetime, lifetime maximization routing based on genetic algorithm (GALMR) for wireless sensor networks is proposed. Energy consumption model and node transmission probability are used to calculate the total energy consumption of nodes in a data gathering cycle. Then, lifetime maximization routing is formulated as maximization optimization problem. The select, crosss, and mutation operations in genetic algorithm are used to find the optimal network lifetime and node transmission probability. Simulation results show that GALMR algorithm are convergence and can prolong network lifetime. Under certain conditions, GALMR outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.

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