Residual Energy Prediction Scheme for Wireless Sensor Devices

Author(s):  
Sungro Yoon ◽  
Chongkwon Kim
2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.


2020 ◽  
Vol 17 (12) ◽  
pp. 5447-5456
Author(s):  
R. M. Alamelu ◽  
K. Prabu

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.


Author(s):  
Yakubu Abdul-Wahab Nawusu ◽  
Alhassan Abdul-Barik ◽  
Salifu Abdul-Mumin

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.


2017 ◽  
Vol 16 (7) ◽  
pp. 7031-7039
Author(s):  
Chamanpreet Kaur ◽  
Vikramjit Singh

Wireless sensor network has revolutionized the way computing and software services are delivered to the clients on demand. Our research work proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. The cluster head election mechanism will include various parameters like maximum residual energy of a node, minimum separation distance and minimum distance to the mobile node. Each CH will create a TDMA schedule for the member nodes to transmit the data. Nodes will have various level of power for signal amplification. The three levels of power are used for amplifying the signal. As the member node will send only its own data to the cluster head, the power level of the member node is set to low. The cluster head will send the data of the whole cluster to the mobile node, therefore the power level of the cluster head is set to medium. High power level is used for mobile node which will send the data of the complete sector to the base station. Using low energy level for intra cluster transmissions (within the cluster) with respect to cluster head to mobile node transmission leads in saving much amount of energy. Moreover, multi-power levels also reduce the packet drop ratio, collisions and/ or interference for other signals. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, multiple experiments have been conducted using different values of initial energy.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Fengyin Li ◽  
Pei Ren ◽  
Guoyu Yang ◽  
Yuhong Sun ◽  
Yilei Wang ◽  
...  

Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. As an important part of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in military, transportation, medical, and household fields. However, in the applications of wireless sensor networks, the adversary can infer the location of a source node and an event by backtracking attacks and traffic analysis. The location privacy leakage of a source node has become one of the most urgent problems to be solved in wireless sensor networks. To solve the problem of source location privacy leakage, in this paper, we first propose a proxy source node selection mechanism by constructing the candidate region. Secondly, based on the residual energy of the node, we propose a shortest routing algorithm to achieve better forwarding efficiency. Finally, by combining the proposed proxy source node selection mechanism with the proposed shortest routing algorithm based on the residual energy, we further propose a new, anonymous communication scheme. Meanwhile, the performance analysis indicates that the anonymous communication scheme can effectively protect the location privacy of the source nodes and reduce the network overhead.


2014 ◽  
Vol 573 ◽  
pp. 424-428 ◽  
Author(s):  
S. Pavalarajan ◽  
R. Krishna Moorthy

Object tracking is a noteworthy application in the field of wireless sensor networks that has attracted major Research attention recently. Most object tracking schemes uses prediction scheme to minimize the energy consumption and to maintain low missing rate in a sensor network. However objects need to be localize, when object was found missing during tracking process. In this article, we proposed a swarm intelligence mechanism, such as particle swarm optimization (PSO) to accurately estimate the location of the missing object, using updated object position and velocity and the extensive simulations are also shown to demonstrate the effectiveness of the proposed algorithm against the centroid and weighted centroid methods to evaluate its performance in terms of localization error.


2012 ◽  
Vol 182-183 ◽  
pp. 823-828
Author(s):  
Xiang Ping Gu ◽  
Rong Lin Hu

ECRPW (energy-efficient clustering routing protocol based on weight) routing protocol is presented to avoid the characteristic of limited energy for wireless sensor networks. It takes nodes’ residual energy into consideration during the process of cluster heads being elected. The constraint of distance threshold is used to optimize cluster scheme. Furthermore, it also sets up the routing tree based on cluster heads’ weight. We simulate and analyze LEACH and ECRPW in NS2. The results show that the performance of ECRPW is better than LEACH.


Author(s):  
Hirokazu Miura ◽  
Yosuke Shimazaki ◽  
Noriyuki Matsuda ◽  
Fumitaka Uchio ◽  
Koji Tsukada ◽  
...  

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