Intrusion Detection in Manet Through Machine Learning Approach

Mobile ad hoc networks (MANETs) have evolved into a leading multi-hop infrastructure less wireless communication technology where every node performs the function of a router. Ad- hoc networks have been spontaneously and specifically designed for the nodes to communicate with each other in locations where it is either complex or impractical to set up an infrastructure. The overwhelming truth is that with IoT emergence, the number of devices being connected every single second keeps increasing tremendously on account of factors like scalability, cost factor and scalability which are beneficial to several sectors like education, disaster management, healthcare, espionage etc., where the identification and allocation of resources as well as services is a major constraint. Nevertheless, this infrastructure with dynamic mobile nodes makes it more susceptible to diverse attack scenarios especially in critical circumstances like combat zone communications where security is inevitable and vulnerabilities in the MANET could be an ideal choice to breach the security. Therefore, it is crucial to select a robust and reliable system that could filter malicious activities and safeguard the network. Network topology and mobility constraints poses difficulty in identifying malicious nodes that can infuse false routes or packets could be lost due to certain attacks like black hole or worm hole. Hence our objective is to propose a security solution to above mentioned issue through ML based anomaly detection and which detects and isolates the attacks in MANETs. Most of the existing technologies detect the anomalies by utilizing static behavior; this may not prove effective as MANET portrays dynamic behavior. Machine learning in MANETs helps in constructing an analytical model for predicting security threats that could pose enormous challenges in future. Machine learning techniques through its statistical and logical methods offers MANETs the learning potential and encourages towards adaptation to different environments. The major objective of our study is to identify the intricate patterns and construct a secure mobile ad-hoc network by focusing on security aspects by identifying malicious nodes and mitigate attacks. Simulation-oriented results establish that the proposed technique has better PDR and EED in comparison to the other existing techniques.

Review on IoT Mobile App based on Rural Development in Terms of Agriculture

As India is still a developing country, it has a lot of rural areas wherein the living conditions and standards are below world standards and may even be on the underdeveloped scale of living standards. In order to achieve development in these regions the first and foremost step to initiate is to improve the agriculture standards and methodologies and bring in new technology to improve the methods used in agriculture which is the major source of income to these people. This project is a four staged project which intends on improving the agriculture standards of India. The first stage of the project is an automated humidity and moisture control for the soil, this will help the farmers in automating certain aspects and hence eliminate certain human errors and improve yield. The second stage of the project is an agriculture auction portal wherein the farmers can directly auction their products to the wholesaler without the need of a middle man/broker. The third stage of the project is an android app which conducts various surveys and suggests a new farmer the type of farming/seeds to be planted / soil information and other such relevant data in respect to agriculture which would help increase the yield for a new farmer. The last part of the project is a seed cum financial bank which helps the farmers by providing financial as well as seed aid in times of financial crisis.

Design and Development of BRRI Solar Powered Light Trap

This research intends to design, assemble and evaluate the performance of an eco-friendly solar light trap to reduce the insect population in rice fields as well as to minimize the use of harmful chemical pesticides. An AutoCAD drawing tool 2016 was used to sketch the design of solar light trap. The main component of this light trap was bulb, solar panel and battery. Design of solar panel and battery was done considering by 5W LED bulb. A total of five bulbs with different colors were selected to test the insect’s reaction by visible light. Study indicated that ultra violet-blue bulb showed the best performance compare to others based on the high percentage of insect trap (31.22%). A 20-watt solar panel and two 4.5 ah batteries of 6 volts were used to operate the solar light trap. The current, voltage, solar intensity was recorded to check overall performance of solar panel. The solar panel generated more power in April than May due to higher solar radiation in the study area. Study suggested that only 4.26 sunshine hours were required to full charge the battery. The solar light trap was operated 5.5 hour in night which was sufficient to reduce the insects in rice field. Moreover, the light sensor was showed 100% functional for ON/OFF purposes. The dominant insects like yellow stem borer (YSB), green leafhopper (GLH) were mostly observed. The average largest numbers of YSB and GLH were 900 and 600 respectively. In conclusion, the solar light trap is eco-friendly, low cost, easy and self-sufficient in term of solar energy. Finally, the newly developed light trap could be helpful for manufactures, decision makers, and engineering community as well as farmers as a best tool to protect nature in comparison to other pesticide using practices.

COVID 19 Data Clustering a nd Testing with K Means Mapper and Reducer

Due to the emergence of a new infectious disease (COVID-19), the worldwide data volume has been quickly increasing at a very high rate during the last two years. Due its infectious, and importance, in this paper, K-Means clustering procedure is applied on COVID data in MapReduce based distributed computing environment. The proposed system is store, process and tests the large volume of COVID-19 data. Experimental results had been proved that this process is adaptable to COVID-19 data in the formation of trusted clusters.

Efficient Resources Allocation and Energy Reduction with Virtual Machines for Cloud Computing

Cloud computing is an internet provisioned method for sharing the resources on demand by network management, storage, services, applications and the serves that necessitate management optimal effort. VMM (virtual machine migration) plays a major role in enhancing the resource utilization, application isolation, processing nodes, fault tolerance in VMs for enhancing nodes portability and for maximizing the efficiency of physical server. For balancing the clouds with resources for the enhanced performance, varied users are served with application deployment in the cloud environment is considered as the major task. The user can rent or request the resources when it becomes significant. The emphasis of this paper is on different energy VM energy efficient module as per machine learning methods. While allocating the VMs to the host machines, MBFD (Modified Best Fit Decreasing) is considered and the classification of host machine capability such as overloaded, normal loaded and underloaded is executed according to SVM (Support vector machine). SVM is utilized as a classifier for analyzing the MBFD algorithm and for the classification of the host as per the job properties. In this procedure, the numbers of jobs that are not allocated are examined via simulation which is computed by means of time consumption, energy consumption and a total number of migrations.

Design o f Wireless Ad Hoc System u sing Adaptive Multi Hop Link State Optimal Routing Protocol

Now a days for the radio network communication multi-hop routing is used. This multi-hop routing technique covers larger coverage area. Therefore to reach at specific location data is transferred in form of packets from one node to other node. But for the transmission of radio signals over the large distance, large number of transreceivers are required and these transreceivers requires large power to operate. As a result, multi-hop routing can saves energy over separate routing. Therefore it is necessity to design a cost effective multi-hop routing technique for successful transmission of ratio packet data. In this paper a hop by hop adaptive link state optional routing (HALO) is explained. It is the first packet transmitting solution with hop by hop and link state routing, which reduces the cost of transporting data across a packet switch network[3]. The triple model is designed for multi hop packet routing. In this work each node of network iteratively and separately improves the small part of traffic bound. This algorithm finds the shortest path of specific location for every iteration and it is calculated by the marginal cost of the various links of network. The marginal link cost is used to calculate the shortest path between the node and the destination location. This marginal link cost is gathered from link state updates. The various networks changes are automatically identified by the adaptive method which is used in this paper. Due to this the exchange between the packets on wrong node is reduced over the overhead traffic. To validate these theoretical results the experimental evaluations and mathematical calculations are also reported in this work. Net beans java is the programmed use in this proposed project.

Comparative Study of Various Iterative Numerical Methods for Computation of Approximate Root of the Polynomials

The aim of this article is to present a brief review and a numerical comparison of iterative methods applied to solve the polynomial equations with real coefficients. In this paper, four numerical methods are compared, namely: Horner’s method, Synthetic division with Chebyshev method (Proposed Method), Synthetic division with Modified Newton Raphson method and Birge-Vieta method which will helpful to the readers to understand the importance and usefulness of these methods.

Flexible Active Power Control Strategy for Photovoltaic System Based on Current Limiting Control Method

India is country with abundant solar energy availability. The annual solar energy output exceeds the total energy output of India's non renewable energy sources. As increasing installation of renewable energy sources into the grid. The fluctuations of power based on operating climate conditions like solar insulation and temperature is highly depends as it is not possible to limit such installations with time the penetration level of renewable sources will increase to meet demand with green energy. This paper proposed a flexibly power point tracking (FPPT) control of active power in photovoltaic system to achieve reserve capacity with Power Limiting Control (PLC) which will provide high stability to existing system without overloading it thus a proper integration to the grid and to mitigate adverse negative effects of high level integrations are possible with modified grid codes in stand of replacement of existing grid . Matlab/Simulink software package is used to make the model and effectiveness of the propose system is tested with Simulink environment..

IIASRH: An Integrative IoT Approach for Smart Rainwater Harvesting

Rainwater harvesting is one of the oldest practices used to conserve and optimize water resources. Nowadays, there are a lot of public and private facilities which have well-constructed Rainwater Harvesting systems. Still, they usually can't test the quality of the water preserved and has no mechanism to purify the impure content to make them consumable. Many known techniques are primitive and conventional for today's standards. The existing systems don't provide connective features, water treatment or contingency measures to counteract any problem. Usually, these systems are integrated onto blockchains, AI, and some other domains to innovate a new paradigm. Still, the results are generally considered a gimmick and are not helpful for general usage. This lack of compatibility and features with no effective solution needs to be rectified, and a real-world upgrade is required to construct a connected, safe and effortless system is imminent. Therefore, an integrative domain approach is necessary to facilitate the process to tackle these problems, where one of the major domains in technology, such as IoT, is used. The proposed model addresses the issues native to the conventional method and provides a connective environment with water treatment capabilities to establish an effortless and connected Rainwater Harvesting system through IoT with precise results and scopes that help the said challenges.

Lightweight VANET Architecture for Efficient Secure Data Transmission using CPABE & IBOOS

Cloud computing is a network access concept that provides simple, on-demand network access to a shared pool of customizable computing resources (such as networks, servers, storage, applications, and services) that can be quickly provided and released with minimal administrative effort or service provider involvement. The idea of having a communication node on-board a vehicle that may make wireless connections with other adjacent communication nodes visible in the radio range is referred to as a Vehicular Adhoc Network (VANET). The main focus of this paper is to design lightweight Vehicular Adhoc Network architecture for efficient secure data transmission. An improved Ciphertext Policy Attribute Based Encryption scheme and Identity Based offline/online Signature scheme are proposed to reduce the computational cost, storage overhead and communication overhead in vehicular ad-hoc network. Finally, concluded that the proposed work yields high performance than the existing work.