Bio: Lovepreet Kaur is an academic researcher. The author has contributed to research in topic(s): Wireless sensor network & Network packet. The author has an hindex of 2, co-authored 5 publication(s) receiving 537 citation(s).
TL;DR: An overview of the different routing strategies used in wireless sensor networks is given and the comparison of these different routing protocols based on metrics such as mobility support, stability, issues and latency is shown.
Abstract: This paper represents energy efficient routing protocols in WSN. It is a collection of sensor nodes with a set of limited Processor and limited memory unit embedded in it. Reliable routing of packets from the sensor node to its base station is the most important task for the networks. The routing protocols applied for the other networks cannot be used here due to its battery powered nodes This paper gives an overview of the different routing strategies used in wireless sensor networks and gives a brief working model of energy efficient routing protocols in WSN. It also shows the comparison of these different routing protocols based on metrics such as mobility support, stability, issues and latency.
TL;DR: This paper examines the various methods of clustering which are centralized, distributed and hybrid utilized in Sensor Networks and presents a comparative study of various clustering algorithms and the issues of clusters in WSNs.
Abstract: Wireless sensor system includes hundreds to thousands of sensor nodes that helps in collecting different information including temperature, sound, area, etc. It’s generally difficult to recharge or change the sensor nodes which may have confined battery capacity. Energy efficiency is therefore a key problem in sustaining the network. Certainly one of the most used alternatives to make WSNs energy-efficient is to cluster the networks. Various clustering techniques are accustomed to effectively optimize or enhance the energy of sensor nodes. In this paper we have examined the various methods of clustering which are centralized, distributed and hybrid utilized in Sensor Networks. This paper also presents a comparative study of various clustering algorithms and the issues of clustering in WSNs.
TL;DR: A new improved NSA based switching median filter which has the capability to decrease the high density of the noise from images and also outperforms over others when input image is noise free and ability to preserves the edges by using the gradient based smoothing.
Abstract: Noise in images has become one of the significant concerns in digital image processing. Many digital image based techniques produce inaccurate results when noise is presented in the digital images. So many researchers have proposed new and modified techniques so far to reduce or remove noise from images. Different kind of enhancement in the filters has been proposed so far. But most of filters put artefacts while doing their work. Many filters fail when noise density in the images is very high. Some filters results poor for edges. This paper has proposed a new improved NSA based switching median filter which has the capability to decrease the high density of the noise from images and also outperforms over others when input image is noise free. The proposed method has also ability to preserves the edges by using the gradient based smoothing. The proposed technique has been designed and implemented in MATLAB tool using image processing toolbox. Different kind of the digital images has been taken for experimental purpose. Comparative analysis has shown that the proposed algorithm is quite effective over the available techniques.
01 Mar 2018
TL;DR: Modified mid-point algorithm along with k-means approach (EECPK) is used to form balanced clusters in wireless sensor networks to enhance the power usage of the nodes.
Abstract: The nodes in wireless sensor networks are operated by batteries. To enhance the power usage of the nodes, clustering is one among the well-known approaches used by the researchers. Clustering is usually done using LEACH protocol, but this selects cluster heads randomly, which causes uneven formation of clusters. This paper proposes modified mid-point algorithm along with k-means approach (EECPK) is used to form balanced clusters. The CHs perform multi-hop communication with BS if distance is greater than threshold value. Also, the concept of threshold energy is used to rotate the CHs and communication range of nodes is also taken in account. The performance has been analyzed based on throughput, packet delivery ratio and energy consumption. The value of PDR obtained was 0.75, throughput's value was around 16875 Kbps and network ran for around 35 seconds.
TL;DR: An attempt to give a wide comparison of EEC PK-means mid-point and Modified EECPK-mean mid- point algorithms to enhance network lifetime, extracting the strengths and weaknesses of both techniques and providing a comparison among them.
Abstract: In previous decades, the utilization of wireless sensor networks (WSN) have grown to a great degree. The nodes in wireless sensor systems are worked by batteries. How the restricted vitality utilized adequately is an essential and vital thought about factor, and the plan objective of most WSN protocols. In wireless sensor networks there is one method utilized for the augmentation of the lifecycle of the system and transfer extra efficient operative technique called as clustering to upgrade the power utilization of the sinks, clustering is one among the well-known approaches used by the researchers. The researchers also proposed many different clustering protocols to achieve the desired network operations. In this paper there is an attempt to give a wide comparison of EECPK-means mid-point and Modified EECPK-means mid-point algorithms to enhance network lifetime. Moreover, extracting the strengths and weaknesses of both techniques, providing a comparison among them, including some metrics like throughput, packet delivery ratio and remaining energy.
TL;DR: This paper proposes a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors and concludes that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges.
Abstract: With the application of Internet of Things and services to manufacturing, the fourth stage of industrialization, referred to as Industrie 4.0, is believed to be approaching. For Industrie 4.0 to come true, it is essential to implement the horizontal integration of inter-corporation value network, the end-to-end integration of engineering value chain, and the vertical integration of factory inside. In this paper, we focus on the vertical integration to implement flexible and reconfigurable smart factory. We first propose a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors. Then, we elaborate the operational mechanism from the perspective of control engineering, that is, the smart artifacts form a self-organized system which is assisted with the feedback and coordination blocks that are implemented on the cloud and based on the big data analytics. In addition, we outline the main technical features and beneficial outcomes and present a detailed design scheme. We conclude that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges.
TL;DR: This paper presents architectural enhancements for providing M2M services in 3GPP LTE/LTE-A networks and reviews the features and requirements of M1M applications, and identifies the issues on diverse random access overload control to avoid congestion caused by random channel access of M 2M devices.
Abstract: Machine-to-machine (M2M) communication is an emerging technology to provide ubiquitous connectivity among devices without human intervention. The cellular networks are considered a ready-to-use infrastructure to implement M2M communications. However, M2M communications over cellular pose significant challenges to cellular networks due to different data transactions, diverse applications, and a large number of connections. To support such a large number of devices, M2M system architecture should be extremely power and spectrum efficient. In this paper, we provide a comprehensive survey on M2M communications in the context of the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) and Long-Term Evolution-Advanced (LTE-A). More specifically, this paper presents architectural enhancements for providing M2M services in 3GPP LTE/LTE-A networks and reviews the features and requirements of M2M applications. In addition, the signal overheads and various quality-of-service (QoS) requirements in M2M communications also deserve our attention. We address M2M challenges over 3GPP LTE/LTE-A and also identify the issues on diverse random access overload control to avoid congestion caused by random channel access of M2M devices. Different application scenarios are considered to illustrate futuristic M2M applications. Finally, we present possible enabling technologies and point out the directions for M2M communications research.
TL;DR: This paper proposes an M2M service platform (M2SP) architecture and its functionalities, and presents the M1M ecosystem with this platform and discusses the issues and challenges of enabling technologies and standardization activities.
Abstract: Machine-to-Machine (M2M) refers to technologies with various applications. In order to provide the vision and goals of M2M, an M2M ecosystem with a service platform must be established by the key players in industrial domains so as to substantially reduce development costs and improve time to market of M2M devices and services. The service platform must be supported by M2M enabling technologies and standardization. In this paper, we present a survey of existing M2M service platforms and explore the various research issues and challenges involved in enabling an M2M service platform. We first classify M2M nodes according to their characteristics and required functions, and we then highlight the features of M2M traffic. With these in mind, we discuss the necessity of M2M platforms. By comparing and analyzing the existing approaches and solutions of M2M platforms, we identify the requirements and functionalities of the ideal M2M service platform. Based on these, we propose an M2M service platform (M2SP) architecture and its functionalities, and present the M2M ecosystem with this platform. Different application scenarios are given to illustrate the interaction between the components of the proposed platform. In addition, we discuss the issues and challenges of enabling technologies and standardization activities, and outline future research directions for the M2M network.
TL;DR: The numerical results on minimal energy consumption and network lifetime of the system indicate that the deployment scheme proposed is more flexible and energy efficient compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment.
Abstract: The Internet of Things (IoT) has been realized as one of the most promising networking paradigms that bridge the gap between the cyber and physical world. Developing green deployment schemes for IoT is a challenging issue since IoT achieves a larger scale and becomes more complex so that most of the current schemes for deploying wireless sensor networks (WSNs) cannot be transplanted directly in IoT. This paper addresses this challenging issue by proposing a deployment scheme to achieve green networked IoT. The contributions made in this paper include: 1) a hierarchical system framework for a general IoT deployment, 2) an optimization model on the basis of proposed system framework to realize green IoT, and 3) a minimal energy consumption algorithm for solving the presented optimization model. The numerical results on minimal energy consumption and network lifetime of the system indicate that the deployment scheme proposed in this paper is more flexible and energy efficient compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment.
TL;DR: The survey aims at clarifying and uncovering the potential of fault diagnosis specifically for wireless sensor networks by providing the technique-based taxonomy.
Abstract: The sensor nodes in wireless sensor networks may be deployed in unattended and possibly hostile environments. The ill-disposed environment affects the monitoring infrastructure that includes the sensor nodes and the network. In addition, node failures and environmental hazards cause frequent topology changes, communication failures, and network partitioning. This in turn adds a new dimension to the fragility of the network topology. Such perturbations are far more common than those found in conventional wireless networks thus, demand efficient techniques for discovering disruptive behavior in such networks. Traditional fault diagnosis techniques devised for multiprocessor systems are not directly applicable to wireless sensor networks due to their specific requirements and limitations. This survey integrates research efforts that have been produced in fault diagnosis specifically for wireless sensor networks. The survey aims at clarifying and uncovering the potential of this technology by providing the technique-based taxonomy. The fault diagnosis techniques are classified based on the nature of the tests, correlation between sensor readings and characteristics of sensor nodes and the network.