scholarly journals Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6149
Author(s):  
Jelena Stanulovic ◽  
Nathalie Mitton ◽  
Ivan Mezei
Keyword(s):  
Network Lifetime ◽  
Task Assignment ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Second Phase ◽  
Communication Costs ◽  
Face Routing ◽  
Two Phases ◽  
New Algorithms

Four new algorithms (RFTA1, RFTA2, GFGF2A, and RFTA2GE) handling the event in wireless sensor and robot networks based on the greedy-face-greedy (GFG) routing extended with auctions are proposed in this paper. In this paper, we assume that all robots are mobile, and after the event is found (reported by sensors), the goal is to allocate the task to the most suitable robot to act upon the event, using either distance or the robots' remaining energy as metrics. The proposed algorithms consist of two phases. The first phase of algorithms is based on face routing, and we introduced the parameter called search radius (SR) at the end of this first phase. Routing is considered successful if the found robot is inside SR. After that, the second phase, based on auctions, is initiated by the robot found in SR trying to find a more suitable one. In the simulations, network lifetime and communication costs are measured and used for comparison. We compare our algorithms with similar algorithms from the literature (k-SAAP and BFS) used for the task assignment. RFTA2 and RFTA2GE feature up to a seven-times-longer network lifetime with significant communication overhead reduction compared to k-SAAP and BFS. Among our algorithms, RFTA2GE features the best robot energy utilization.

scholarly journals Maximizing Network Lifetime Operator for Wireless Sensor Networks

2013 ◽  
Vol 4 (2) ◽  
pp. 267-272
Author(s):  
Dr. Deepali Virmani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Topology Control ◽  
Performance Metrics ◽  
Minimum Energy ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Minimum Energy Consumption

Optimizing and enhancing network lifetime with minimum energy consumption is the major challenge in field of wireless sensor networks. Existing techniques for optimizing network lifetime are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols have a significant impact on network lifetime, available energy and connectivity. In this paper we categorize sensor nodes as strong and weak nodes based on their residual energy as well as operational lifetime and propose a Maximizing Network lifetime Operator (MLTO) that defines cluster based topology control mechanism to enhance network lifetime while guarantying the minimum energy consumption and minimum delay. Extensive simulations in Java-Simulator (J-Sim) show that our proposed operator outperforms the existing protocols in terms of various performance metrics life network lifetime, average delay and minimizes energy utilization.

scholarly journals AR-RBFS: Aware-Routing Protocol Based on Recursive Best-First Search Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Farzad Kiani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Data Transmission ◽  
Search Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Second Phase

Energy issue is one of the most important problems in wireless sensor networks. They consist of low-power sensor nodes and a few base station nodes. They must be adaptive and efficient in data transmission to sink in various areas. This paper proposes an aware-routing protocol based on clustering and recursive search approaches. The paper focuses on the energy efficiency issue with various measures such as prolonging network lifetime along with reducing energy consumption in the sensor nodes and increasing the system reliability. Our proposed protocol consists of two phases. In the first phase (network development phase), the sensors are placed into virtual layers. The second phase (data transmission) is related to routes discovery and data transferring so it is based on virtual-based Classic-RBFS algorithm in the lake of energy problem environments but, in the nonchargeable environments, all nodes in each layer can be modeled as a random graph and then begin to be managed by the duty cycle method. Additionally, the protocol uses new topology control, data aggregation, and sleep/wake-up schemas for energy saving in the network. The simulation results show that the proposed protocol is optimal in the network lifetime and packet delivery parameters according to the present protocols.

scholarly journals Iterative Sensor Clustering and Mobile Sink Trajectory Optimization for Wireless Sensor Network with Nonuniform Density

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Joohan Park ◽  
Soohyeong Kim ◽  
Jiseung Youn ◽  
Seyoung Ahn ◽  
Sunghyun Cho
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Trajectory Optimization ◽  
Environmental Changes ◽  
Wireless Sensor ◽  
Second Phase ◽  
Improve Energy Efficiency ◽  
Mobile Sinks ◽  
Two Phases ◽  
Sensor Clustering

Sensor clustering and trajectory optimization are a hot topic for last decade to improve energy efficiency of wireless sensor network (WSN). Most of existing studies assume that the sensor is uniformly deployed or all regions in the WSN coverage have the same level of interest. However, even in the same WSN, areas with high probability of disaster will have to form a “hotspot” with more sensors densely placed in order to be sensitive to environmental changes. The energy hole can be serious if sensor clustering and trajectory optimization are formulated without considering the hotspot. Therefore, we need to devise a sensor clustering and trajectory optimization algorithm considering the hotspots of WSN. In this paper, we propose an iterative algorithm to minimize the amount of energy consumed by components of WSN named ISCTO. The ISCTO algorithm consists of two phases. The first phase is a sensor clustering phase used to find the suitable number of clusters and cluster headers by considering the density of sensor and residual battery of sensors. The second phase is a trajectory optimization phase used to formulate suitable trajectory of multiple mobile sinks to minimize the amount of energy consumed by mobile sinks. The ISCTO algorithm performs two phases repeatedly until the amount of energy consumed by the WSN is not reduced. In addition, we show the performance of the proposed algorithm in terms of the total amount of energy consumed by sensors and mobile sinks.

An Improved Algorithm Based on LEACH Protocol

2013 ◽  
Vol 347-350 ◽  
pp. 2725-2727
Author(s):  
Wei Liu ◽  
Le Le Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Simulation Experiments ◽  
Leach Protocol ◽  
Node Energy ◽  
Improved Algorithm

In this paper, taking into account the shortcomings of wireless sensor networks, LEACH algorithm, the algorithm has been improved on this basis. The design of the E-LEACH algorithm, which extend the network lifetime, improve node energy utilization, and the effectiveness of this algorithm through simulation experiments.

scholarly journals A Survey on Various Clustering Algorithms in WSN for Optimal Energy Utilisation

2021 ◽  
pp. 712-720
Author(s):  
Madhuri N. Khuspare ◽  
Dr. Awani S. Khobragade
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Clustering Algorithms ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Sensor ◽  
Related Data

Wireless sensor networks comprise of an expansive number of distributed sensor gadgets, which are associated and composed through multi-hop steering. Because of the presence of related data and excess in measuring data, data messages can be joined and converged by performing data aggregation work in the steering procedure. To diminish energy utilization is a noteworthy enhancement target of data aggregation approaches, which can be accomplished by diminishing the mandatory correspondence load of steering. To improvise the network lifetime as much as possible in Wireless Sensor Networks (WSNs) the ways for data move are picked in a way that the aggregate energy used along the way is limited. To help high adaptability and better data aggregation, sensor nodes are routinely collected into disjoint, non-covering subsets called clusters. Clusters make various leveled WSNs which consolidate proficient use of constrained assets of sensor nodes and in this manner broadens network lifetime. The objective of this paper is to demonstrate a forefront survey on clustering calculations announced in the writing of WSNs. This paper presents different energy effective clustering calculations in WSNs. From the hypothetical level, an energy show is proposed to approve the advantages of data aggregation on energy utilization. The key parameters which may affect the aggregation execution are additionally examined.

scholarly journals Energy-Efficient Routing for Performance and Network Lifetime Enhancement in Wireless Sensor Networks

2021 ◽  
pp. 113-120
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Multimedia Data ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Energy Efficient Routing ◽  
Efficient Energy

Due to the rapid and quality advancements in the sensor technology and the availability of stumpy cost hardware, the development of Wireless Sensor Networks (WSNs) has emerged as a unique solution. These networks are the composition of source controlled nodes that are wireless, through which the scalar and multimedia data can be sensed, acquired and transmit from the surroundings. However, the resource controlled character of the wireless sensing devices has made the WSNs to face numerous challenges. A multiplicity of WSN applications are underwater, mountain-based, and forest driving. Practically it is not achievable to revitalize or re-establish these nodes throughout the task. To tackle these challenges, efficient energy utilization is a significant confront in these types of networks, as the node energy is constrained. Thus, these available resources of the node must be utilized efficiently for various basic functions like data sensing, processing and transmitting. So, the energy efficient routing protocols are the key factors to decrease the energy consumption and lifetime elaboration of the network. The Cluster-based routing is a widespread method to attain network performance with energy efficiency to enhance network lifetime. Thus, this work gives the development of routing protocol with efficient energy to elaborate systems lifetime. Performance results indicate that the projected work improves the performance.

scholarly journals EDCH: A Novel Clustering Algorithm for Wireless Sensor Networks

2019 ◽  
Vol 4 (3) ◽  
pp. 45-51
Author(s):  
Raj Kumar Pyage ◽  
H. G. Chandrakanth
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Role ◽  
Considerable Decrease

In wireless sensor networks, sensor nodes play the most important role. These sensor nodes are mainly un-chargeable, so it an issue regarding lifetime of the network.  The main objective of this research is concerning clustering algorithms to minimize the energy utilization of each sensor node, and maximize the sensor network lifetime of WSNs. In this paper, we propose a novel clustering algorithm for wireless sensor networks (WSN) that decrease the networks energy consumption and significantly prolongs its lifetime. Here main role play distribution of CHs ( Cluster Heads) across the network. Our simulation result shows considerable decrease in network energy utilization and therefore increase the network lifetime.  

scholarly journals An Optimal Cluster-Head Selection algorithm for Wireless Sensor Networks

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Energy Efficiency ◽  
Network Lifetime ◽  
Environmental Conditions ◽  
Signal Strength ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Control Technique ◽  
The Impact

The energy utilization is one of the most common challenges in Wireless Sensor Network (WSN), as frequent communication between the sensor nodes (SNs) results in huge energy drain. Moreover, optimization and load balancing within the WSN are the significant concern to grant intellect for the extensive period of network lifetime. As a matter of fact, many WSNs are deployed and operating outdoors is exposed to varying environmental conditions, which may further set grounds for severe performance degradation of such networks. Therefore, it is necessary to take into consideration the factors like radio signal strength in order to reduce the impact and to adapt to varying environmental conditions. Since clustering is a topological control technique to reduce the activity of SNs transceivers, it extensively increases overall system scalability and energy efficiency. It selects CH to manage the entire network to achieve longevity in WSN. In this paper, we present an optimal CH selection (OCHS) algorithm which is also based on environmental conditions to achieve energy efficiency and enhanced network lifetime. The originality of this work is that we have taken into consideration the received signal strength index (RSSI) of SNs from the base-station (BS). The OCHS algorithm mainly focuses on maximizing the network lifetime based on RSSI values and residual energy levels of SNs. TheOCHS algorithm is simulated on Cooja Simulator and its performance is compared with existing LEACH and HEED protocols. Simulation analysis and results proved that our OCHS algorithm can effectively enhance the network lifetime by two times and thus it is an energy-efficient way to choose a CH.

scholarly journals Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1540 ◽  
Author(s):  
Ramadhani Sinde ◽  
Feroza Begum ◽  
Karoli Njau ◽  
Shubi Kaijage
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Second Phase ◽  
Network Delay ◽  
Duty Cycling ◽  
Hybrid Particle Swarm Optimization

Over the recent era, Wireless Sensor Network (WSN) has attracted much attention among industrialists and researchers owing to its contribution to numerous applications including military, environmental monitoring and so on. However, reducing the network delay and improving the network lifetime are always big issues in the domain of WSN. To resolve these downsides, we propose an Energy-Efficient Scheduling using the Deep Reinforcement Learning (DRL) (E2S-DRL) algorithm in WSN. E2S-DRL contributes three phases to prolong network lifetime and to reduce network delay that is: the clustering phase, duty-cycling phase and routing phase. E2S-DRL starts with the clustering phase where we reduce the energy consumption incurred during data aggregation. It is achieved through the Zone-based Clustering (ZbC) scheme. In the ZbC scheme, hybrid Particle Swarm Optimization (PSO) and Affinity Propagation (AP) algorithms are utilized. Duty cycling is adopted in the second phase by executing the DRL algorithm, from which, E2S-DRL reduces the energy consumption of individual sensor nodes effectually. The transmission delay is mitigated in the third (routing) phase using Ant Colony Optimization (ACO) and the Firefly Algorithm (FFA). Our work is modeled in Network Simulator 3.26 (NS3). The results are valuable in provisions of upcoming metrics including network lifetime, energy consumption, throughput and delay. From this evaluation, it is proved that our E2S-DRL reduces energy consumption, reduces delays by up to 40% and enhances throughput and network lifetime up to 35% compared to the existing cTDMA, DRA, LDC and iABC methods.

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