International Journal on Future Revolution in Computer Science & Communication Engineering
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Enhancing Security and Privacy on Smart City’s Collected Data: A Fog Computing Perspective
Get PDFSmart cities use information and communication technologies to deliver services to their citizens. Use of ICT makes them to be more intelligent and efficient in usage of resources, resulting in cost and energy savings, improved service delivery and quality of life. Smart cities are expected to be the fundamental pillars of continued economic growth and improved services delivery. Smart City technology is having ability to constantly gather information about the city, sharing the data with people, devices and technologies or borrowing relevant data from elsewhere, for analysis to enable informed decision making. For instance internet of things has emerged as a technological driving force in real time service delivery in smart cities. These applications provide new abilities, enhancing monitoring, and provision of action oriented process on control and device management. Smart devices are a major source of big data in smart cities. With expected increase of billions of smart devices and sensors in smart city by the year 2020, more data will be generated which will reduce efficiency of cloud access, due to increased volume. Security and privacy of data is a challenge in smart city, negligence in data security and privacy can be amplified in folds resulting to faulty applications, services along with paralyzing the entire city through Denial of Service (DDoS) attack, Spear Phishing Attacksand Brute-Force Attacks among others.Fog computing FC is a new paradigm that is intended to extend cloud computing CC through deployment of processing and localized units into the network edge, enabling low latency, offering location awareness and latency sensitiveness. Homomorphism for encryption, authorization, authentication, and classification are performed on collected data in smart cities to improve security and privacy. In this paper assimilation and analysis, is performed with fog computing aspects of decentralization, different policies for datacenter transferstrategies being analyzed.Processing time, access time, request time, response time and cost analysis show system efficiency
A Study of Effective Factors Over Routing Protocols for MANET
Get PDFA network which does not require any fixed pre-existing infrastructure and can be defined as a set of mobile nodes is called MANET. In MANET mobile nodes are communicating through wireless medium. In MANET all mobile nodes behaves as router and when required they takes part in discovery and maintenance of the route to the other node. One of the major challenges in designing a routing protocol for the MANET is to determine a packet route; a node needs to know at least about its neighbors. On the other hand in MANET wireless networks conditions changes frequently with time due to the mobile nodes thus routing becomes a challenging task. To serve this purposes various proactive, reactive and hybrid routing protocols are developed by researchers. Among all AODV, DSR, DYMO and ZRP are well known popular routing protocols and have been standardized by the IETF MANET WG. ZRP is a well known hybrid routing protocol. To understand its suitability we must understand its behavior under various real time conditions. This paper study some propagation model and fading model and also describes two main characteristic of wireless channel path loss and fading. This paper also focuses on some other important factors that affect the performance of MANET. These important factors are battery model, Radio Model, Queue model and Mobility model. Thus, the goal is to carry out a systematic performance comparison of ad-hoc routing protocols under these factors in terms of QoS metrics such as average end-to-end delay, throughput and average jitter
Smart Health Predicting System Using Data Mining
Get PDFAn overview of the data mining techniques with its applications, medical, and educational aspects of Clinical Predictions. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. Such a large amount of data cannot be processed by humans in a short time to make diagnosis, and treatment schedules. A major objective is to evaluate datamining techniques in clinical and health care applications to develop accurate decisions. It also gives a detailed discussion of medical data mining techniques which can improve various aspects of Clinical Predictions. It is a new powerful technology which is of high interest incomputer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of machine learning and database management to extract new patterns from large datasets and the knowledge associated with these patterns. The actual task is to extract data by automatic orsemi- automatic means. The different parameters included in data mining include clustering, forecasting, path analysis and predictive analysis. It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Health Prediction system is an end user support and online consultation project. Here we propose a system that allows users to get instant guidance on their health issues through an intelligent health care system online. The system is fed with various symptoms and the disease/illness associated with those systems. The system allows user to share their symptoms and issues. It then processes userssymptoms to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s symptoms. If the system is not able to provide suitable results, it informs the user about the type of disease or disorder it feels user’s symptoms are associated with. If users symptoms do not exactly match any disease in our database
A Hybrid of Improved Bulls and Weighted Round Robin to optimize the Leader and Load Balancing in Cloud and Distributed Computing Environment
Get PDFDay by Day there is increase of internet users which leads to increase the traffic in the network which causing the generation of huge data. It requires the balancing of network load on the network servers with different Load balancing techniques. It is also required to have efficient algorithm to analysis the huge data in distributed manner to identify the leader to act as centralized point of contact for services. If we audit on the heap adjusting systems, there are a few potential outcomes to upgrade the methods. In the present scenario, we have the methods, round robin algorithm (static load adjusting), Weighted Round Robin algorithm and Least Load algorithm (Dynamic Load Balancing). A researcher D. Chitra Devi .et .al has given the idea of enhanced weighted round robin algorithm (EWRR) which gives much better reaction when contrasted with basic round robin calculation. Another scholar Rashmi Saini et. al recommended the half breed of round robin calculation and minimum Load Algorithm. From the above scholars� articles, I hereby propose a resolution by improved Bulls algorithm along with Weighted Round Robin (WRR) algorithm to achieve high performance in Distributed and Cloud Computing domain in terms of leader election from a group of distributed and non-failed processes, load balancing dynamically and coordinate other nodes. Bulls algorithm uses the following message types: � Election Message: Sent to announce election. � Answer (Alive) Message: Responds to the Election message. � Coordinator (Victory) Message: Sent by winner of the election to announce victory. When coordinator fails to recover a process P, from failure or detecting before failure, the process P performs the following actions: 1. If P has the highest process id, it sends a Victory message to all other processes and becomes the new Coordinator. Otherwise, P broadcasts an Election message to all other processes with higher process IDs than itself. 2. If P does not receive any Election message, then it broadcasts a Victory message to all other processes and becomes the Coordinator. 3. If P receives an Answer from a process with a higher ID, it sends no further messages for this election and waits for a Victory message. When there is no Victory message after a stipulated period, it restarts the process from the beginning. 4. If P receives an Election message from another process with a lower ID it sends an Answer message back and starts the election process at the beginning, by sending an Election message to higher-numbered processes. 5. If P receives a Coordinator message, it treats the sender as the coordinator
A Survey on Techniques to Protect Video files Using Watermarking
Get PDFIn this advanced age the principle issue with multimedia documents like picture and video is theft. The Radical increment in trades of information over the web and the incessant utilization of advanced medium has been watched. Computerized data can be shielded from unapproved get to and sharing through watermarking. Digital watermarking is the methodology of inserting some applicable data in the host signal. With the utilization of watermarking systems on unique medium, licensed innovation rights can be saved over web. An investigation deals with various elements and techniques for computerized watermarking has been carried out and introduced in this paper
An Efficient Approach of Review Sentiment Analysis
Get PDFThis paper investigates the utility of linguistic feature for detecting the sentiments of review messages. We take a supervised approach to the problem and 50,000 movie reviews for building our training data. We investigate an efficient method to build a strong model for extracting the features that contain sentimental information
Forecasting Future Customer Call Volumes: Case study
Get PDFForecasting future volumes of customer calls in call centers has proved to be a tedious and challenging task. This study, using time series analysis proposes two adequate ARIMA (p, d, q) models that are suitable to forecast two volumes of customer calls, IVR Hits Volumes and Offered Call volumes. 1472 times series data points from date 01/01/2014 to 11/01/2018 were obtained from a call center based in Kenya on the two variables of interest (IVR Hits Volumes and Offered Call volumes). The appropriate orders of the two models are picked based on the examination of the results of the ACF and PACF plots. The AIC criterion is used to select the best model for the data. The best ARIMA model for log IVR Hits volumes is ARIMA (5, 1, 3) with and the best ARIMA model for log Offered Call Volumes is ARIMA (6, 1, 3) with . The two models are recommended to model and forecast the daily arrival volumes of customer call data. The obtained forecast will be used in providing insights for appropriate workforce management
Twitter Sentiment and Statement Reality Analysis Considering Pre-Current and Post Event Tweets
Get PDFAs we know that twitter is one of the main internet applications which have pulled many internet users into messaging, sharing tweets etc. The day to day increase of internet usage by the means of Desktop�s, Laptops, and Smartphone�s etc. which made following, follows and favorites hit count to a maximum extent. This has given many un-ethnic users an advantage on making a message or an event to hype, or fake so as to make business or an event a profitable economically or on monetarily. This makes a user or viewers a frustration on the belief. To decrease such activities and increase the reliability and belief a Tweet/ Event Reality Analysis has to be imposed by Considering Tweet Sentiment on Pre-Current and Post Event Tweets based on Event Date. In this paper, we focus on the Tweet Sentiment and Statement Reality Analysis by Pre-Current and Post Event Tweets based on the event Date. The tweet sentiments have to be categorized based on the sentiment and sub categorized on whether the tweet was before the Event date, or on Current Date and or on Post Event Date, which gives the Reality Analysis of the Tweeted Statement without affecting the tweet sentiment
A Framework for Detecting Malicious Node in VANET
Get PDFVehicular ad hoc network (VANET) is a vehicle to vehicle (VVC) and roadside to vehicle (RVC) communication system. The technology in VANET incorporates WLAN and Ad Hoc networks to achieve the regular connectivity. The ad hoc network is brought forth with the objectives of providing safety and comfort related services to vehicle owners. Collision warning, traffic congestion warning, lane-change warning, road blockade alarm (due to construction works etc.) are among the major safety related services addressed by VANET. In the other category of comfort related services, vehicle users are equipped with Internet and Multimedia connectivity. The major research challenges in the area lies in design of routing protocol, data sharing, security and privacy, network formation etc. We aim here to study the overview of VANET and its security issues