scholarly journals A Twofold Sink Based Data Collection for Continuous Object Tracking in Wireless Sensor Network

Author(s):  
Sajjad Hussain Chauhdary ◽  
Ali Hassan ◽  
Mohammed A Alqarni ◽  
Abdullah Alamri

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

2011 ◽  
Vol 216 ◽  
pp. 621-624
Author(s):  
Xin Lian Zhou ◽  
Jian Bo Xu

This paper first proposed an energy-efficient distributed clustering technology for mobile sensor nodes and sink node mobility, select the higher residual energy and the nearest node from fixed nodes as cluster heads responsible for collecting sensed data, and all the fixed nodes form routing backbone to forward data, both can save energy and avoid cluster head away. Then, proposed a cross-layer scheduling mechanism to avoid the impact of mobile node and meet expectations cluster coverage. With energy-efficient clustering technology, efficient network topology control technology and mobile sink node, the data collection algorithm MSDBG, not only has considered mobility of nodes and energy saving, but also has achieved prolonging network lifetime.


2012 ◽  
Vol 524-527 ◽  
pp. 815-818
Author(s):  
Deng Yuan Xu ◽  
Zhong Wei Hou

As one of important technologies of IOT (Internet of Things), WSN (Wireless Sensor Networks) has been used in tunnel environmental monitoring. Tunnel environment monitoring has its particularity that WSN nodes show linear topologies. Traditional routing algorithms in WSN do not consider the linear topology of sensor nodes in tunnel and are difficult to realize long-time data transmission in limited battery power. In this paper, we propose Power Control Dynamic Source Routing algorithm (PC-DSR) by the thought of cross-layer design. Routing table is established according to the distance between nodes and the residual energy of nodes and optimum transmission power is calculated in order to save nodes’ power and prolong the life-time of the whole networks. Simulation results show that the novel algorithm can save node's transmission power, which increase the WSN lifetime of 12.3%.


Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Yanan Wang ◽  
Fuxing Song ◽  
Wenyu Zhang

In wireless sensor networks (WSNs), energy-constrained sensor nodes are always deployed in hazardous and inaccessible environments, making energy management a key problem for network design. The mechanism of RNTA (redundant node transmission agents) lacks an updating mechanism for the redundant nodes, causing an unbalanced energy distribution among sensor nodes. This paper presents an energy-balanced mechanism for hierarchical routing (EBM-HR), in which the residual energy of redundant nodes is quantified and made hierarchic, so that the cluster head can dynamically select the redundant node with the highest residual energy grade as a relay to complete the information transmission to the sink node and achieve an intracluster energy balance. In addition, the network is divided into several layers according to the distances between cluster heads and the sink node. Based on the energy consumption of the cluster heads, the sink node will decide to recluster only in a certain layer so as to achieve an intercluster energy balance. Our approach is evaluated by a simulation comparing the LEACH algorithm to the HEED algorithm. The results demonstrate that the BEM-HR mechanism can significantly boost the performance of a network in terms of network lifetime, data transmission quality, and energy balance.


In this paper, data collection is the operation of gathering a lot of details from the sensor nodes and shipping it to the sink node. The use of Network is increasingly required to perform these processes, so, increases energy consumption. A lot of WSN architectures are designed to solve this complex problem. By using a technique called Decision Tree Classifier using Adaboost (DTCA) algorithm, can extension that data collection efficiency, as well as reducing the delay and Power consumption. In the proposed methodology, the power of each sensor node should be estimated at the outset. Then the mobile sink node receives the information from the high power sensor nodes with minimal delay. The mobile sink node classifies the data pockets using the Decision Tree Classifier. This classifies based on the relationship between the sensor nodes in WSN. That relationship is measure using the method of population Pearson product moment correlation coefficient. Adaboost algorithm is a combination of several weak non-linear classifiers to create a higher classification. Then finally, it sends classified particulars to Base Station. The operation of the DTCA system is convey out with divergent parameters such as classification time, EC, (Network Lifetime) NL, data collection capability, Classification Accuracy (CA), (FPR) false positive rate and delay.


Wireless sensor network (WSN) is an emerging area in which numbers of sensor nodes are deployed in two ways random and deterministic for data gathering. WSNs have expedited human life in diverse emerging fields: military, agriculture, structural health, perimeter access control, forest fire detection. A physical stimulus such as pressure, sound, light act as an environmental parameter on which the system is design to monitor and detect it for controlling the coverage area for assigned task. The nodes are deployed in the random manner in the given area for gathering the information and they may be overlapped so that the total area may not be covered. The proposed protocol uses radius and the residual energy as a function to increase the total coverage area so that the whole coverage area may be achieved. It also increases the life time of the network using Sleep and Wakeup protocol. Therefore the overall life time of the network increases.


Author(s):  
Heba Hussain Hadi, Et. al.

Multi-hope is widely used for data aggregation and transmission in various applications. The resource availability determines the life time of a WSN. Sensor nodes are powered by a tiny battery that supplies the required energy for the sensor and transmitter. The residual energy available at any moment decides the fitness of the sensor node. The sensor node senses the environment and transmits the data to the sink. Efficient data transmission and aggregation with less energy consumption can prolong the lifetime of the sensor network. The sensor node that is inside the coverage area of the sink can directly transmit the data to sink in a single-hop transmission. The sensor node that is not inside the coverage area should transmit the data to the neighbor node which is in the coverage area of the sink. The data is then turn transmitted by the node close to it fall in multi-hop transmission involving a number of intermediate nodes to forward the data to the sink and consumes extra energy for the forwarding process. The formation clusters and data transmission of data by Cluster Heads (CH) can eliminate many nodes involved in the transmission of same data. Clusters are a group of self-organized nodes in a geographic location that can communicate among them. A node in a cluster with higher residual energy will be acting as CH and all other nodes in the cluster transmit the data to the CH. The CH transmits the aggregated data to the sink. The CH transmits the data to the sink either in single-hop transmission or multi-hop transmission. The cluster head consumes more energy than other nodes in the cluster as it is involved in aggregation and transmission process.


Managing the energy is very challenging in wireless multimedia sensor networks because of heavy consumption of energy by the sensor nodes. Multimedia data transmission contains heavy energy consumption operations such as sensing, aggregating, compressing and transferring the data from one sensor node to neighbour sensor node. Many routing techniques considers residual energy of a neighbour node to forward the data to that node. But, in reality a critical situation occurs where required energy is greater than individual neighbour node’s residual energy. In this situation it is not possible to select any neighbour node as a data forwarder. The proposed greedy knapsack based energy efficient routing algorithm (GKEERA) can address this critical situation very efficiently. And also a Two-in-One Mobile Sink (TIOMS) is used to provide the power supply and to collect the data from a battery drained sensor node. GKEERA improves the life time of a network by balancing the energy consumption between the neighbour nodes.


2019 ◽  
Vol 8 (2) ◽  
pp. 2238-2247

The expeditious growth in manufacturing anvils industries has lead towards the development of tiny devices. This growth has motivated to develop small and battery-operated sensor nodes that are widely adopted for establishing the reliable wireless communication. The wireless sensor based communication is generally divided into hierarchal and geographical deployment. Hierarchical system based approaches are widely studied in this field, limited work is present in the field of geographical WSN. In this work, we focus on the geographical WSN. Generally, these networks suffer from energy efficiency and security related issues. Hence, in this work we preset a combined approach to address these challenges. In order to mitigate the energy sparsity issue, we develop geographical routing scheme which selects the neighboring node based on residual energy of the node and distance from the sink node i.e. the maximum residual energy node from the neighboring node which is having less distance from the sink node is selected as next-hop. Due to this approach, the path computation and other network parameters computation is not required hence it reduces the power consumption. Further, we address the security issues where we present Hash modeling to secure the location, Key Exchange model for authentication by using ECDH approach , later we present ECIS based encapsulation method for data security and finally, a trust model based security system is developed. The trust computation of node helps to the routing whether to select the node for next hop or not. This multistage security approach is called as Secure Hash, Authentication and Cryptography based geographical routing (SHAC-GR) protocol. The proposed approach is simulated using MATLAB simulation tool and the performance of proposed approach is compared with existing technique that shows that the proposed approach improves the network performance in terms of network lifetime, energy and packet delivery rate.


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