scholarly journals SCR-CC: A Novel Sensing Clustering Routing Algorithm Based on Collaborative Computing in Heterogeneous Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Zeyu Sun ◽  
Guisheng Liao ◽  
Zhiguo Lv ◽  
Guozeng Zhao ◽  
Chuanfeng Li
Keyword(s):  
Network Lifetime ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Base Station ◽  
Expected Value ◽  
Collaborative Computing ◽  
Simulation Experiments ◽  
Heterogeneous Sensor Networks ◽  
Efficiency And Effectiveness ◽  
Entire Network

In order to better improve the reliability of data transmission and extend the network lifetime, the paper proposes the Sensing Clustering Routing Algorithm Based on Collaborative Computing (SCR-CC). The proposed algorithm uses the characteristics of the perceptual radius, which obey the normal distribution, and gives the process of completing the expected value of the data transmission of any two nodes in the cluster. Secondly, the paper analysed the necessary conditions of the existence for the expected value of the number of neighbour nodes when the redundant nodes are closed and the working nodes meet arbitrary differences. Thirdly, the cluster angle formed by the base station and the cluster is used to optimize the clustering structure and complete the dynamic clustering process to achieve the energy balance of the entire network. Finally, the simulation experiments show that the proposed SCR-CC algorithm compared with the other three algorithms reduces the number of failed nodes by 11.37% on average and increases the network lifetime by 27.09% on average; therefore, the efficiency and effectiveness of the SCR-CC algorithm are verified.

scholarly journals Energy‑harvesting and energy aware routing algorithm for heterogeneous energy WSNs

2021 ◽  
Vol 24 (2) ◽  
pp. 910
Author(s):  
Mohammed Mehdi Saleh ◽  
Ruslan Saad Abdulrahman ◽  
Aymen Jaber Salman
Keyword(s):  
Energy Harvesting ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Energy Levels ◽  
Routing Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Node Activity ◽  
Essential Components

Wireless sensor networks are regarded as the most essential components of contemporary technologies since they are in charge of sensing and monitoring processes, which are the primary functions of these technologies. Because these nodes rely on an unchangeable battery and are randomly deployed in the environment, node energy management is the most essential issue to consider when designing algorithms to enhance the network's life. Clustering is a wireless sensor network (WSN) routing technique that has been implemented in order to extend network lifetime. Also, it is trendy to increase the energy levels of the node battery by utilizing various energy harvesting techniques in order to extend the network lifetime. In this paper, a new energy-aware clustering algorithm (EHEARA) has been proposed. The proposed algorithm is based on a dynamic clustering function and adopts a solar energy harvesting scheme in order to improve network lifetime. Furthermore, the active-sleep mechanism was used to distribute node activity and balance communication among nodes within clusters and cluster heads with the base station. The proposed algorithm is simulated using matrix laboratory (MATLAB), and the results show that it outperforms the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC), and stable election protocol (SEP) algorithms in terms of network lifetime, energy consumption, and network throughput.

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 A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Osama Moh’d Alia
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Transmission ◽  
Energy Efficient ◽  
Base Station ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Cluster Heads ◽  
Transmission Phase

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network’s lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols.

scholarly journals Energy proficient clustering technique for lifetime enhancement of cognitive radio–based heterogeneous wireless sensor network

2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876759 ◽  
Author(s):  
Venkatasubramanian Srividhya ◽  
Thangavelu Shankar
Keyword(s):  
Wireless Sensor Networks ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Heterogeneous Wireless Sensor Network ◽  
Communication Approach

Utilizing the available spectrum in a more optimized manner and selecting a proper routing technique for transferring the data, without any data collision, from the sensor node to the base station play a major role in any network for increasing their network lifetime. Cognitive radio techniques play a major role to achieve the same, and when combined with wireless sensor networks the above-said requirements can be greatly accomplished. In this article, a novel energy-efficient distance-based clustering and routing algorithm using multi-hop communication approach is proposed. Based on distance, the given heterogeneous cognitive radio–based wireless sensor networks are divided into regions and are allocated with a unique spectrum. Dynamic clustering through distance calculation and routing of data through multi-hop communication is done. The simulation results illustrate that the proposed algorithm has improved energy efficiency and is more stable. The first node death and 80% node death illustrate the improved scalability. Also, the increased throughput aids in maintaining the residual energy of the network, which further solves the problem of load balancing among nodes. All the above results combined with half node death analysis show that the proposed algorithm also has an improved network lifetime.

scholarly journals An Efficient Routing Approach to Maximize the Lifetime of IoT-Based Wireless Sensor Networks in 5G and Beyond

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
C. Jothikumar ◽  
Kadiyala Ramana ◽  
V. Deeban Chakravarthy ◽  
Saurabh Singh ◽  
In-Ho Ra
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Network Lifetime ◽  
Data Transmission ◽  
Base Station ◽  
Wireless Sensor ◽  
The Internet ◽  
The Internet Of Things

The Internet of Things grew rapidly, and many services, applications, sensor-embedded electronic devices, and related protocols were created and are still being developed. The Internet of Things (IoT) allows physically existing things to see, hear, think, and perform a significant task by allowing them to interact with one another and exchange valuable knowledge when making decisions and caring out their vital tasks. The fifth-generation (5G) communications require that the Internet of Things (IoT) is aided greatly by wireless sensor networks, which serve as a permanent layer for it. A wireless sensor network comprises a collection of sensor nodes to monitor and transmit data to the destination known as the sink. The sink (or base station) is the endpoint of data transmission in every round. The major concerns of IoT-based WSNs are improving the network lifetime and energy efficiency. In the proposed system, Optimal Cluster-Based Routing (Optimal-CBR), the energy efficiency, and network lifetime are improved using a hierarchical routing approach for applications on the IoT in the 5G environment and beyond. The Optimal-CBR protocol uses the k-means algorithm for clustering the nodes and the multihop approach for chain routing. The clustering phase is invoked until two-thirds of the nodes are dead and then the chaining phase is invoked for the rest of the data transmission. The nodes are clustered using the basic k-means algorithm during the cluster phase and the highest energy of the node nearest to the centroid is selected as the cluster head (CH). The CH collects the packets from its members and forwards them to the base station (BS). During the chaining phase, since two-thirds of the nodes are dead and the residual energy is insufficient for clustering, the remaining nodes perform multihop routing to create chaining until the data are transmitted to the BS. This enriches the energy efficiency and the network lifespan, as found in both the theoretical and simulation analyses.

scholarly journals Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

2018 ◽  
Vol 13 (1) ◽  
pp. 99
Author(s):  
Misbahuddin Misbahuddin ◽  
Anak Agung Putri Ratna ◽  
Riri Fitri Sari
Keyword(s):  
Network Lifetime ◽  
Routing Protocol ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Base Station ◽  
Cluster Heads ◽  
Data Similarity ◽  
Fuzzy Aggregation ◽  
Node Clustering

In multi-hop routing, cluster heads close to the base station functionaries as intermediate nodes for father cluster heads to relay the data packet from regular nodes to base station. The cluster heads that act as relays will experience energy depletion quicker that causes hot spot problem. This paper proposes a dynamic multihop routing algorithm named Data Similarity Aware for Dynamic Multi-hop Routing Protocol (DSA-DMRP) to improve the network lifetime, and satisfy the requirement of multi-hop routing protocol for the dynamic node clustering that consider the data similarity of adjacent nodes. The DSA-DMRP uses fuzzy aggregation technique to measure their data similarity degree in order to partition the network into unequal size clusters. In this mechanism, each node can recognize and note its similar neighbor nodes. Next, K-hop Clustering Algorithm (KHOPCA) that is modified by adding a priority factor that considers residual energy and distance to the base station is used to select cluster heads and create the best routes for intra-cluster and inter-cluster transmission. The DSA-DMRP was compared against the KHOPCA to justify the performance. Simulation results show that, the DSA DMRP can improve the network lifetime longer than the KHOPCA and can satisfy the requirement of the dynamic multi-hop routing protocol.

scholarly journals On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

2010 ◽  
Vol 6 (1) ◽  
pp. 563156 ◽  
Author(s):  
Yunyue Lin ◽  
Qishi Wu ◽  
Xiaoshan Cai ◽  
Xiaojiang Du ◽  
Ki-Hyeon Kwon
Keyword(s):  
Network Lifetime ◽  
Data Transmission ◽  
Optimal Solution ◽  
Base Station ◽  
Sensor Nodes ◽  
Base Stations ◽  
Communication Model ◽  
Multihop Communication ◽  
The One ◽  
Station Location

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In the multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.

scholarly journals Routing Algorithm for Delay Tolerance in Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 64
Author(s):  
Cong Li ◽  
Shujuan Dong
Keyword(s):  
Network Lifetime ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Critical Evaluation ◽  
Correlated Data ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Core ◽  
Group A ◽  
Better Than

<p class="Abstract"><span lang="EN-US">In a regular sensor node, there are three activities that are the core sources of energy consumption i.e. sensing, computation, and radio operations. Multi-Group, a novel routing algorithm based on LEACH (MG-LEACH) that has been utilized in redundant deployed sensor nodes to improve the network lifetime is explored. It has been suppressing the correlated data gathered by the sensor nodes by monitoring the similar event, thus not only reducing the data transmission inside the clusters but also conserving the energy of deployed sensor nodes consequently to improve the overall network lifetime. The proposed routing algorithm has been simulated using MATLAB to verify the efficiency in enhancing network lifetime. A critical evaluation of routing algorithm is conducted to determine the relevance and applicability in increasing network lifetime. Simulation results demonstrated that it has performed better than LEACH and enhanced network lifetime by up to approximately 90%.</span></p>

scholarly journals PEDTARA: Priority-Based Energy Efficient, Delay and Temperature Aware Routing Algorithm Using Multi-Objective Genetic Chaotic Spider Monkey Optimization for Critical Data Transmission in WBANs

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 68
Author(s):  
Omar Ahmed ◽  
Min Hu ◽  
Fuji Ren
Keyword(s):  
Network Lifetime ◽  
Data Transmission ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Spider Monkey ◽  
Area Network ◽  
Multi Objective ◽  
Critical Data ◽  
On Demand ◽  
Spider Monkey Optimization

Software-Defined Wireless Body Area Network (WBAN)s have gained significance in emergency healthcare applications for remote patients. Prioritization of healthcare data traffic has a high influence on the congestion and delay in the WBAN routing process. Currently, the energy constraints, packet loss, retransmission delay and increased sensor heat are pivotal research challenges in WBAN. These challenges also degrade the network lifetime and create serious issues for critical health data transmission. In this context, a Priority-based Energy-efficient, Delay and Temperature Aware Routing Algorithm (PEDTARA) is presented in this paper using a hybrid optimization algorithm of Multi-objective Genetic Chaotic Spider Monkey Optimization (MGCSMO). This proposed optimized routing algorithm is designed by incorporating the benefits of chaotic and genetic operators to the position updating function of enhanced Spider Monkey Optimization. For the prioritized routing process, initially, the patient data transmission in the WBAN is categorized into normal, on-demand and emergency data transmissions. Each category is ensured with efficient routing using the three different strategies of the suggested PEDTARA. PEDTARA performs optimal shortest path routing for normal data, energy-efficient emergency routing for high priority critical data and faster but priority verified routing for on-demand data. Thus, the proposed PEDTARA ensures energy-efficient, congestion-controlled and delay and temperature aware routing at any given period of health monitoring. Experiments were performed over a high-performance simulation scenario and the evaluation results showed that the proposed PEDTARA performs efficient routing better than the traditional approaches in terms of energy, temperature, delay, congestion and network lifetime.

Sign in / Sign up

Export Citation Format

Share Document