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The recent technological advances in wireless sensor networks lead rapid development towards a new era of research-real time applications. Although quality of service was the primary concern in WSNs, but the requirement of low latency, energy efficiency, and timely delivery of data in communication are becoming more and more important issues in eme...
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The Cluster Head is selected on the basis of maximum number of nodes connected, thus several sensor nodes cannot reach any CH, even though they are in the transmission range. These nodes are called the isolated nodes. To solve this problem, the proposed a sub_cluster protocol, its role is to reduce the sensor nodes which do not belong the cluster....
The main objective of routing protocol is to select the next-hop connection node for packets traveling from source to distention. Greedy algorithm depends on the distance only to select the next-hop connection and it is building one chain only. Delay is considering the main drawback in all chain based routing protocols in the wireless sensor networ...
![Fig.3. Operation of XMAC protocol [6]](profile/Thang-Chien/publication/334623645/figure/fig2/AS:789075137146880@1565141581074/Operation-of-XMAC-protocol-6_Q320.jpg)
This paper will present several research results evaluating the performance of ContikiMAC and XMAC protocols in data collection application with the RPL routing protocol. Simulation results show that ContikiMAC protocol gets better efficiency compared with XMAC protocol in both successful data delivery ratio and average energy consumption in the ne...
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... Designing the sensor network for a particular application requires the basic knowledge about problem definition, knowledge about node's battery health condition, data transfer rate, bandwidth allocation, admission control algorithm, collision avoidance scheme etc. As an example application like temperature monitoring does not require high data rate but fire monitoring system, battle field surveillance, intruder attack requires high rate data transfer [17]. Although quality of service is the primary goal in WSN traffic but low latency in communication and node's energy usage maximization is becoming more and more important in current scenario [5,16]. ...
In the recent decades, computer science and engineering has found an emerging research domain in data communication network field, the WSN. WSN applications are generally deployed in fields where uninterrupted supervisions are required. In WSN applications, thousands of energy-constrained sensor nodes are used to sense the data from the deployed environment and transmit the sensed data to the base station (BS). Recent advances in wireless sensor networks lead to rapid development of real-time applications. The requirement of low latency in communication and maximum utilization of node’s battery power are becoming more and more important issues in emerging applications especially in fire monitoring, medical care, battle field surveillance, etc. The cluster-based routing protocols can improve the energy life of the sensors and hence can prolong the entire network lifetime but uneven load distribution among the clusters, and static BS may lead to energy hole problem to the entire communication network. In this paper, we present a novel real-time energy-efficient routing protocol in a different way so that real-time communication is achieved by allowing low latency, but it must not incur infinite bounded waiting for the non-real-time regular data communications. This paper also considers mobile sink node to avoid the energy hole problem.
... Wireless sensor networks consist of large number of sensor nodes which are usually battery-operated sensing devices with limited energy resources and replacing or recharging the batteries is usually impractical. Thus designing an energy efficient routing protocol is becoming more important for current's applications area of wireless sensor networks [16]. Clustering the network into small groups where each group is controlled by a cluster head is an efficient and way to structure the network with large number of sensor nodes. ...
... So the nodes' die rate will decrease and automatically it will prolong network life time. We optimize LEACH by introducing sleep wakeup based decentralized MAC protocol because we observed that one of the major reason of energy wastes is idle listening of sensor nodes [16] . In major application areas a potential amount of energy of the nodes is lost due to listen the channel for a long time until the target object is detected. ...
The wireless sensor network is consisting of a large number of micro chips with limited energy capacities that are capable of gathering data in different kinds of environments. Clustering sensors into small groups and each group is controlled by a cluster head, so that sensors transmit data to cluster-heads only and then cluster-heads send the aggregated information to the base station, may save some energy. In this paper, we propose an optimal energy-adaptive algorithm which is motivated from the LEACH. We have tried to modify the LEACH's random cluster-head election protocol for ensuring the balanced energy dissipation over the whole network to increase the network lifetime. The modified duty cycle for the sensor nodes has been proposed and to ensure this we optimize TDMA through sleep wakeup based decentralized MAC protocol. Simulation based on power consumption results that our algorithm outperforms LEACH around 30%.
This paper presents an algorithm for feature selection based on particle swarm optimization (PSO) for thermal face recognition. The total algorithm goes through many steps. In the very first step, thermal human face image is preprocessed and cropping of the facial region from the entire image is done. In the next step, scale invariant feature transform (SIFT) is used to extract the features from the cropped face region. The features obtained by SIFT are invariant to object rotation and scale. But some irrelevant and noisy features could be produced with the actual features. Unwanted features have to be removed. In other words, optimum features have to be selected for better recognition accuracy. The PSO helps to identify the optimum features set using local as well as global searches. Here, this process has been implemented to select a subset of features that effectively represents original feature extracted for better classification convergence. Finally, minimum distance classifier is used to find the class label of each testing images. Minimum distance classifier acts as an objective function for PSO. In this work, all the experiments have been performed on UGC-JU thermal face database. The maximum success rate of 98.61 % recognition has been achieved using SIFT and PSO for frontal face images and 90.28 % for all images.
Tuberculosis (TB) is one of the major infectious diseases in the third world countries especially African countries. TB is a curable disease if proper treatment starts on time. Sometimes, it becomes difficult to arrange sufficient infrastructure for diagnosis of the disease in the remote areas of third world countries. Telemedicine partially solves the lack of physician and technicians in the pathological laboratories. The objective of this work is to design a complete setup that can be deployed at the remote areas of the country as a supporting aid of a telemedicine system for the diagnosis of TB. This system performs analysis of images of sputum and cough of patients. Microscopic image of TB bacteria which are stained with pink color is the main criterion for detection of TB disease. This system is still in development stage. A sufficient amount of data are needed for validation of the system.
