scholarly journals An Energy-Efficient and Fault-Tolerant Topology Control Game Algorithm for Wireless Sensor Network

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1009 ◽  
Author(s):  
Yongwen Du ◽  
Jinzong Xia ◽  
Junhui Gong ◽  
Xiaohui Hu
Keyword(s):  
Utility Function ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Topology Control ◽  
Resource Constraints ◽  
Fault Tolerant ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Potential Game ◽  
Game Model

Due to resource constraints and severe conditions, wireless sensor networks should be self-adaptive to maintain certain desirable properties, such as energy efficiency and fault tolerance. In this paper, we design a practical utility function that can effectively balance transmit power, residual energy, and network connectivity, and then we investigate a topology control game model based on non-cooperative game theory. The theoretical analysis shows that the topology game model is a potential game and can converge to a state of the Nash equilibrium. Based on this model, an energy-efficient and fault-tolerant topology control game algorithm, EFTCG, is proposed to adaptively constructs a network topology. In turn, we present two subalgorithms: EFTCG-1 and EFTCG-2. The former just guarantees network single connectivity, but the latter can guarantee network biconnectivity. We evaluate the energy-efficient effect of EFTCG-1. Meanwhile, we also analyze the fault-tolerant performance of EFTCG-2. The simulation results verify the validity of the utility function. EFTCG-1 can efficiently prolong the network lifetime compared with other game-based algorithms, and EFTCG-2 performs better in robustness, although does not significantly reduce the network lifetime.

scholarly journals A Distributed Energy-Balanced Topology Control Algorithm Based on a Noncooperative Game for Wireless Sensor Networks

2018 ◽  
Author(s):  
Yongwen Du ◽  
Junhui Gong ◽  
Zhangmin Wang ◽  
Ning Xu
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Topology Control ◽  
Control Algorithm ◽  
Wireless Sensor ◽  
Theil Index ◽  
Potential Game ◽  
Game Model

In wireless sensor networks, there is no a central controller to enforce cooperation between nodes. Therefore, nodes may generate selfish behavior to conserve their energy resources. In this paper, we address the problems of transmission power minimization and energy balance in wireless sensor networks using a topology control algorithm. We considered the energy efficiency and energy balance of the nodes, and an improved optimization-integrated utility function is designed by introducing the Theil index. Based on this, a topological control game model of energy balance is established, and it is proved that the topological game model is an ordinal potential game with Pareto optimality. Additionally, an energy-balanced topology control game algorithm (EBTG) is proposed to construct topologies. The simulation and comparison show that, compared with other topological control algorithms based on game theory, the EBTG algorithm can improve energy balance and energy efficiency while reducing the transmitting power of nodes, thus prolonging the network lifetime.

scholarly journals FLECHA: a Forecasting eLEction meCHAnism for semantic collectors sensor nodes

2020 ◽  
Author(s):  
Mauricio M. Neto ◽  
Leonardo O. Moreira ◽  
Danielo G. Gomes
Keyword(s):  
Wireless Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Resource Constraints ◽  
Arima Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Depletion ◽  
Energy Hole ◽  
Semantic Clustering

Due to the resource constraints of the sensor nodes, energy provisioning in wireless sensor networks remains a challenging task, particularly in outdoor scenarios. Among the literature proposals to mitigate this problem, we highlight semantic clustering as a recent energy-efficient technique for prolonging the network lifetime. In semantic clustering, each cluster has a semantic leader (collector) which is periodically elected according to an energy-related criterion. However, since collectors’ energy depletion is faster than the others members of their cluster, suitable election mechanisms are required to avoid the energy hole problem. Here we propose FLECHA, a mechanism based on the ARIMA model to predict semantic collectors elections with leader-node alternation. Our hypothesis is that by anticipating the best candidates to semantic leaders, we can improve the energy-saving at the node-level, and hence allow the network lifetime to be further extended.

scholarly journals Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987763 ◽  
Author(s):  
Jing Zhang ◽  
Li Lei ◽  
Xin Feng
Keyword(s):  
Game Theory ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Potential Game ◽  
Game Model ◽  
Sidelobe Level ◽  
Long Distance ◽  
Minimum Number ◽  
Cooperative Nodes

A group of collaborative nodes can efficiently complete spatial long-distance transmission tasks using beamforming technology. However, a high sidelobe level interferes with communication quality, and uneven energy consumption of nodes affects network lifetime. This paper proposes an energy-efficient collaborative transmission algorithm based on potential game theory for beamforming. First, the minimum number of cooperative nodes is determined in accordance with the energy consumption and spacing limitation condition. A group of nodes satisfying the node spacing condition is selected as cooperative nodes based on the ring array to minimize communication interference among nodes. Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. Finally, the game process is continuously executed until the Nash equilibrium is reached. According to simulation results, the sidelobe level caused by the cooperative nodes is reduced and the transmission conflicts are lessened. Thus, the quality of communication links in between nodes in the network is improved. Energy efficiency is also promoted because a balancing of energy consumption is involved in the proposed potential game model, and network lifetime is effectively prolonged accordingly.

An Algorithm with Efficiently Collecting and Aggregating Data for Wireless Sensor Networks

2021 ◽  
Author(s):  
Peng Xiong ◽  
Qinggang Su
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Battery Capacity

Due to the resource constraint, in wireless sensor network, the node processing ability, wireless bandwidth and battery capacity and other resources are scarcer. For improving the energy efficient and extend the lifetime of the network, this paper proposes a novel algorithm with the distributed and energy-efficient for collecting and aggregating data of wireless sensor network. In the proposed protocol, nodes can autonomously compete for the cluster head based on its own residual energy and the signal strength of its neighbouring nodes. To reduce the energy overhead of cluster head nodes, with a multi-hop way among cluster heads, the collected data from cluster heads is sent to a designated cluster head so as to further send these data to a base station. For improving the performance of the proposed protocol, a new cluster coverage method is proposed to fit the proposed protocol so that when the node density increases, network lifetime can be increased linearly as the number of nodes is increased. Simulations experiments show that network lifetime adopting the proposed protocol is sharply increased. And, the proposed protocol makes all the nodes die (network lifetime is defined as the death of last one node) in the last 40 rounds so that networks adopting the proposed protocol have higher reliability than networks adopting compared protocols.

Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 168-172
Author(s):  
Ravi Kumar Poluru ◽  
M. Praveen Kumar Reddy ◽  
Syed Muzamil Basha ◽  
Rizwan Patan ◽  
Suresh Kallam
Keyword(s):  
Network Lifetime ◽  
Routing Protocols ◽  
Energy Efficient ◽  
High Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Stability Period ◽  
Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

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