In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.
Robust Header Compression (ROHC) is a standardized option defined by the IETF to compress the various transport and communication protocol headers over wireless links. In the present day scenario, when the applications and services are evolving to become more bandwidth hungry, wireless networks are expected to be capable of letting them drive on wireless links and provide required quality of service (QoS). For wireless networks with high bit error rate (BER), it is always a challenge to achieve desired QoS by maximizing true bandwidth utilization. ROHC is an efficient mechanism for effective use of bandwidth. The framework compresses the header size of the protocols, based on redundant information being carried, thereby intelligently using the available bandwidth without drop in QoS. This paper studies and implements the existing ROHC standard and various optimization parameters involved, to finally propose a Modified ROHC Implementation. The paper proposes to reduce the size of the (second order) SO packet, than that of standard ROHC mechanism, by omitting sending of context identifier (ID) in SO packet in modified ROHC alogarithm, and supplementing this absence of information by inbuilt mechanism of algorithm to generate the identification of SO packet at decompressor end. These two ROHC mechanisms are implemented and compared on the basis of average header length and decompression failures.
Nowadays security is major concern for any user connected to the internet. Various types of attacks are to be performed by intruders to obtaining user information as manin-middle attack, denial of service, malware attacks etc. Malware attacks specifically ransomware attack become very famous recently. Ransomware attack threaten the users by encrypting their most valuable data, lock the user screen, play some random videos and by various more means. Finally attacker take benefits by users through paid ransom. In this paper, we propose a framework which prevent the ransomware attack more appropriately using various techniques as blockchain, honeypot, cloud & edge computing. This framework is analysed mainly through the IoT devices and generalized to the any malware attack.
Question Answering (QA) is a focused way of information retrieval. Question Answering system tries to get back the accurate answers to questions posed in natural language provided a set of documents. Basically question answering system (QA) has three elements i.e. question classification, information retrieval (IR), and answer extraction. These elements play a major role in Question Answering. In Question classification, the questions are classified depending upon the type of its entity. Information retrieval component is used to determine success by retrieving relevant answer for different questions posted by the intelligent question answering system. Answer extraction module is growing topics in the QA in which ranking and validating a candidate’s answer is the major job. This paper offers a concise discussion regarding different Question Answering types. In addition we describe different evaluation metrics used to evaluate the performance of different question answering systems. We also discuss the recent question answering systems developed and their corresponding techniques.
Hand gesture recognition system provides a natural, innovative and modern means of non-verbal communication. It has a wide application area in human-computer interaction and sign language. This paper proposes a way to control the position of the cursor, volume control and brightness control with the bare hands without using any electronic device. While operations such as clicking and dragging objects will be performed with different hand gestures, the proposed system will only require a webcam as an input device. The software required to implement the proposed system is OpenCV and Python. The output of the camera will be displayed on the screen of the system and will be further adjustable by the user. The python dependencies that will be used for implementing this system are NumPy, math, WX.
<p>Wireless telecommunication is the backbone of mainstream technologies such as automation, smart vehicles, virtual reality, and unmanned aerial vehicles. Today, we are witnessing a wide-scale adoption of these technologies in our daily lives. The endless opportunities generated due to rapid deployments of new technologies have also brought about new challenges, chief among them is ensuring reliable system performance of cellular networks in mobility scenarios. Beamforming is an integral part of modern mobile networks that enable spatial selectivity and hence improved network quality. However, most of the beamforming techniques are iterative; therefore, they introduce additional unwanted latency into the system. Lately, we are witnessing an ever-increasing interest in exploiting the location of a mobile user to speed up beamforming. This paper comprehensively discusses how location-assisted beamforming strategies improve performance, such as latency and signal-to-noise ratio. Furthermore, we also show how artificial intelligence schemes such as machine learning and deep learning are also used to implement contextual beamforming techniques that exploit the user's location information.</p>
The goal of this paper is to show how swarm intelligence inspired optimization algorithms can take benefit of the parallel computing mechanism supported by general purpose computing ability of a Graphical Processing Unit (GPU). In this paper, Particle Swarm Optimization (PSO) algorithm is implemented both in C (serial) and C-CUDA (parallel) and their performances are compared on a testbed of well-known optimization test functions. Simulation results showed that parallel implementation of PSO using C-CUDA searches near optimal solution in lesser time as compared to that of serial algorithm implemented using C.
INTRODUCTION: In last few years number of internet users and available bandwidth has been increased exponentially. The availability of internet with such a low cost is making audiovisual content a more popular and easier form of information exchange. The internet is having a huge amount of this au
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