The need for fuels of renewable origin is very essential for the countries that are in the development stages. The present condition is that the power generation is purely based on the fossil fuel thermal power plants which share a major source. Next to that is the nuclear power plant, which has its own limitations and problems associated to it. In the field of biofuels, various attempts has been carried out to blend a certain percentage of biofuels obtained from crops such as jathropa, cotton seed and many other varieties. In this review, a possibility of using Algae for the production of biofuels is discussed.
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Maintaining data determined quality in public cloud acts an essential measure in cloud computing. Cloud storage auditing settles the multifaceted nature of data dependability in public cloud. In advance auditing protocols are all standard on the announcement that the customer’s private key for auditing is totally secured. Nonetheless, such proclamation most likely won’t for untouched be seized, in light of the presumably weak rationale of insurance or potentially low security settings at the customer. In the event that such a mystery key for auditing is\ revealed, almost every one of the current auditing protocols would unquestionably form into unable toward effort. In this paper, we meeting point happening this new part of cloud storage auditing. We analyze how to diminish harm of the customer’s key scope in cloud storage auditing, and give the essential sensible answer for this unique trouble setting. We commend the significance and the shelter model of auditing convention with key-scope adaptability and propose such a convention. In our arrangement, we use the preorder traversal method and the twofold tree structure to illuminate the private keys for the buyer. Not with standing grow a novel authenticator structure to maintain the forward security and the advantages of lump less obviousness. The asylum verification and the presentation examination demonstrate that our proposed convention is sheltered and capable.
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In the world of computing, there is always a need for unique values to be generated for numerous applications. Various methods exist with the most common being reliant on an instance of time. But when we need to generate a unique value, based on an input factor such that the exact same value is generated, every time the input factor is the same, cryptographic hashing functions get the job done. Cryptographic hashing functions have many uses like digital signatures, message authentication, checksum generation, digital fingerprinting and securing passwords in a database. In this paper, we review and compare multiple hashing algorithms by different criteria with emphasis on message authentication.
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Aliasing is a typical antique in low-resolution (LR) pictures produced by a down sampling procedure. Recuperating the first high-determination picture from its LR partner while in the meantime evacuating the associating ancient rarities is a testing picture introduction issue. Since a characteristic picture ordinarily contains repetitive comparable patches, the benefits of missing pixels can be accessible at composition applicable LR pixels. In light of this, the paper proposes an iterative multiscale bicubic interpolation technique that can successfully address the associating issue. The proposed technique appraises each missing pixel from an arrangement of surface pertinent semilocal LR pixels with the composition closeness iteratively measured from a succession of patches of differing sizes. In particular, in every emphasis, top surface significant LR pixels are utilized to build an information constancy term in a most extreme a posteriori estimation, and a respective aggregate variety is utilized as the regularization term. Exploratory results contrasted and existing interjection strategies exhibit that our strategy can considerably reduce the associating issue as well as produce better results over an extensive variety of scenes both as far as quantitative assessment and subjective visual quality.
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With an increase in the usage of cloud storage, effective methods need to be employed to reduce hardware costs, meet the bandwidth requirements and to increase storage efficiency. This can be achieved by using Data Deduplication. Data Deduplication is a method to reduce the storage need by eliminating redundant data. Thus by storing less data you would need less hardware and would be able to better utilize the existing storage space. Currently usage of cloud storage is increasing and to overcome increasing data issue, Data deduplication techniques are used. Moreover the Cloud storage service is provided by third party cloud providers thus security of data is needed. Data Deduplication techniques cannot be applied directly with security mechanisms.
To understand the concept and framework of de-duplication process along with application, various methods and technologies involved during the each level implementation of this process. Different chunking algorithm such as fixed, variable and content aware chunking methods are used to decide the chunk size of deduplication. Digital data increase happens in all cloud deployment models and this requires more storage capacity, more costs, manpower and more time to handle data information like backup, replication and disaster recovery, more bandwidth utilization in transmitting the data across the network. If we handle the data effectively like remove the redundant data before storing into the storage device we can avoid data handling overhead and we can improve the system performance. Thus here in this paper we would be discussing data deduplication framework and data deduplication tech iques along with securing techniques thus forming secure deduplication.
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The purpose of this paper is to compare the random access protocols Slotted ALOHA / CDMA mode (used in the GSM since January 2000) and CPCH / W-CDMA mode (used in the future UMTS cellular network).The objective is trying to determine which protocol appears to be the most robust to the scalability of clients simultaneously connected to a cell. To compare these two protocols, modeling in the environment Opnet will simulate the operation of the access to UMTS.
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Due to increase in population, the number of vehicles is increasing rapidly. Increase in vehicles leads to many traffic problems like traffic jams, accidents, money loss, wastage of time, pollution, health problems and many more. So it is necessary to manage and control traffic. Various traffic management techniques are used each having its own advantages and disadvantages. Currently used techniques are not so efficient in terms of performance, cost, maintenance etc. In this paper, we will discuss traffic management system based on Digital Image Processing. Use of digital image processing will help in better traffic management and also it is cost effective.
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The traditional implementation of an E-Voting system, while being superior to the physical voting system, happens to have a potential flaw in its chain of security, particularly the hash functions being used. The system is potentially susceptible towards attacks, such as pre-image attack or collisions, which could compromise the overall integrity and security of the entire E-Voting system. In this paper, we propose a modified version of the E-Voting system, where we replace the flawed hash with a superior one. In unison, the modern hash delivers a superior performance.
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In today’s world internet technology made our life very much easy. Security and reliability of images or information are major factors, but there are security problems. When we transmit the data over the internet the main problem is to secure the data from redundancy. Digital watermarking technique is use to provides security or protection of digital information,so that unauthorized user can’t access the information. Digital watermarking is commonly used in medical applications. Digital watermarking techniques have been developed to protect the copyright of digital media. In this paper our aim is to provide the detailed review of digital watermarking its applications and recent existing techniques for security applications.
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Video surveillance is a widely used process of monitoring secured\ areas like bank vaults, traffic signals, and Jewellery stores, etc. In the modern world with the help of advance technologies in hardware and software systems it has become viable to store large amount of data and process it adequately with high speed. Before the advance in technology video surveillance was done manually by human operators and were saved in tapes to examine later. But with the increase in the number of cameras in surveillance systems it is no longer feasible to ensure proper monitoring of each and every video manually by the human operators. In order to reduce the manual work and increase accuracy and efficiency and response time in surveillance systems to detect and track specific events from live or a recorded video stream object detection has become a very critical requirement. In this paper, we implement a video surveyance system with real time moving object detection and tracking features. The system uses a stationary camera to record the live video stream and process it to detect foreground objects from any video i.e. color or gray scale. A tracking algorithm is used to track the object once it is detected.
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This paper deals with digital watermarking, to protect the digital media such as videos, images and audio from copyright. With the growing and rapid use of internet services, issues like integrity, authenticity, copyright protection have become more important, since the duplication and unauthorized use of the digital content has become easier results in development of various watermarking techniques to maintain originality of data. For different techniques, different algorithms are used such as for image watermarking we divide the image into two parts ROI and RONI, then RONI into three parts and embed watermark into these areas, DWT, DFT and DCT in video watermark and in audio watermark phase coding and sonic watermarking techniques used.Mainly this paper summarizes applications and properties of watermarking.
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In this paper a new approach towards video watermarking is developed, resulting better robustness, data security and higher embedding capacity. Video watermarking is a data hiding technique in which an information or message is hidden inside a signal transparent to the user. Basically digital watermarking involves embedding secret symbols known as watermarks within video data which can be used later for copyright protection, piracy tracing,content authentication, advertisement surveillance, error resilience and so forth.This scheme convert the video into number of frames by using object reader. Select one frame and convert it into RGB to Grey level. Then apply DWT to cover image i.e. selected frame. Similar action will be carried on the text data frame .Using alpha blending technique, cover frame and text frame of their grey format are combined together to get Watermarked Image. Then the IDWT (Inverse discrete wavelet transform) is applied. This Watermarked image is in grey form which will have to be converted into RGB form, by using grey to RGB converter. Lastly recollection of frames takes place by using object reader to obtain a Watermarked Video.
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Botnets are the foremost common vehicle of cyber-criminal activity. They’re used for spamming, phishing, denial-of-service attacks, brute-force cracking, stealing non-public data, and cyber warfare. A botnet (also referred to as a zombie army) may be a range of net computers that, though their homeowners are unaware of it, are got wind of to forward transmissions (including spam or viruses) to alternative computers on the web. During this paper, we propose a two-stage approach for botnet detection. The primary stage detects and collects network anomalies that are related to the presence of a botnet whereas the second stage identifies the bots by analyzing these anomalies. Our approach exploits the subsequent 2 observations: (1) bot masters or attack targets are easier to findbecause of several alternative nodes, and (2) the activities of infected machines are a lot in similar with one another than those of traditional machines.
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Now days, Cloud Computing is the most transpiring trend in Information Technology. Due to its salient features and advantages like scalability, easy and cheap access, throughput and on demand up and down grading of Iaas, Paas and Saas, it is attracting many organizations around the world. Besides all the advantages and pros of cloud environments, there are some risks and challenges also. The biggest of all the challenges is Privacy and Security. In this paper, a review of different security issues like trust, authenticity, encryption, confidentiality, resource sharing and key management are presented along with the efforts made on how to resolve these issues and threats.
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Cloud computing is an emerging technology for providing computing resources and storage to users. It eliminates the need of maintaining costly computing facilities by companies and institutes. But the adoption of Cloud Computing applies only if the security is ensured. So, Security is an important factor in cloud computing for ensuring clients data is placed on the secure mode in the cloud. The security issues such as Confidentiality and integrity of data in data security are essential in the cloud. This paper is mainly focused on security issues in today’s cloud and several cryptographic techniques that can be used to improve the security in cloud environment.
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Cauchy’s Residue Theorem is a powerful tool to evaluate line integrals of analytic functions over closed curves. Cauchy’s Residue Theorem can be used to evaluate various types of integrals of real valued functions of real variable. In this paper we present a new technological approach to solve line integrals of analytical functions using MATLAB.
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Cloud computing is the new generation of networks that uses remote servers hosted on the Internet for various uses such as data storage, data management, software usage etc. There are huge amount of resources provided and users can make use of the resources in any way they want to. Workflow scheduling is the most important task in cloud computing field and users have to pay for resources that were used based in a pay-perusage scheme. Today, researchers attempt to find newer ways for Workflow scheduling which could work well in the cloud environment. Another important element to be considered about cloud computing is Load balancing. Here in this document, we are recommending Firefly criteria for effective fill controlling in reasoning processing. This criterion is based on the travel behavior of the fireflies which go looking for the closest possible maximum alternatives. We employ Firefly algorithm to schedule the jobs and thereby evenly distribute the load and in turn reduce the overall completion time (makespan).
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Voluminous amounts of data have been produced since the past decade as the miniaturization of Internet of things (IoT) devices increases. However, such data are not useful without analytic power. Numerous big data, IoT and analytics solutions have enabled people to obtain valuable insight into large data generated by IoT devices. However, these solutions are still in their infancy, and the domain lacks a comprehensive survey. This study provides a generic overview of big IoT data analytics. The relationship between big data analytics and IoT is explained. Architecture-cumframework for big IoT data analytics with cloud is presented here. Several opportunities brought by data analytics in IoT paradigm are then discussed. Next comes the open research challenges, such as privacy, big data mining, visualization, and integration, presented as future research directions. And lastly, two applications of big Iot data are described as examples of the technology.
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Due to the rapid growth of network infrastructure and sensor, the age of the IoT (internet of things) that can be implemented into the smart car, smart devices, smart home, smart building, and smart city is coming. IoT is a very useful ecosystem that provides various services (e.g., amazon echo); however, at the same time, risk can be huge too. Collecting information to help people could lead serious information leakage, and if IoT is combined with critical control system (e.g., train control system), without quality of service and security attack would cause loss of lives. Furthermore, research on IoT security requirements is insufficient now. Therefore, this paper focuses on Quality of Service and IoT security, and its requirements. First, we propose basic security requirements of IoT by analyzing three basic characteristics (i.e., heterogeneity, resource constraint, dynamic environment). Then, we suggest six key elements of IoT (i.e., IoT network, cloud, user, attacker, service, platform) and analyze their security issues for overall security requirements. In addition, we evaluate several IoT security requirement researches.
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Cloud computing is a buzzword that means different things to different people. For some, it’s just another way of describing “outsourcing” others use it to mean any computing service provided over the Internet or a similar network and some define it as any bought-in computer service you use that sites outside your firewall. Storing, accessing and processing of data in cloud environment are the cutting edge technology used all over the world. Storing and sharing is basic need for enhancing the security. Sensitive data must be more secured during the sharing of data. Data encryption, homo-morphic encryption, secret sharing technique and data partition technique are widely used to share the data in cloud computing environment. In this paper we discuss the two techniques: secret sharing algorithm and information dispersal algorithm.
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This paper presents an approach to the point to point processing of digital images using parallel computing, particularly for grayscale, brightening, darkening, and thresh-holding and contrast change. The point to point technique applies a transformation to each pixel on image concurrently rather than sequentially. This approach used CUDA as parallel programming tool on a GPU in order to take advantage of all available cores. Preliminary results show that CUDA obtains better results in most of the used filters. Except in the negative filter with lower resolutions images Open CV obtained better ones, but using images in high resolutions CUDA performance is better.
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Cloud computing may be defined as management and provision of resources, software, application and information as services over the cloud which are dynamically scalable. The dynamic environments of cloud are more or less prone to failure. So there is an increased requirement for fault tolerance to achieve reliability for the real time computing on cloud infrastructure. Fault tolerance techniques are used to predict these failures and ntake an appropriate action before failures actually occur. Various fault detection methods have been discussed. In this paper, a fault tolerance in real time cloud computing Environment is discussed in which the system tolerates the faults and makes the decision on the basis of reliability of the processing nodes, i.e. virtual machines.
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Distributed vertex-centric model has been recently proposed for large-scale graph processing. Due to the simple but efficient programming abstraction, similar graph computing frameworks based on GPUs are gaining more and more attention. However, prior works of GPU-based graph processing suffer from load imbalance and irregular memory access because of the inherent characteristics of graph applications. In this paper, we propose a generalized graph computing framework for GPUs to simplify existing models but with higher performance. In particular, two novel algorithmic optimizations, lightweight approximate sorting and data layout transformation, are proposed to tackle the performance issues of current systems. With extensive experimental evaluation under a wide range of real world and synthetic workloads, we show that our system can achieve 1.6x to 4.5x speedups over the state-of-the-art.
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Looking at the software engineering principles from a historical perspective, we can see how the software processing methodologies evolved since past 50 years, but probably the most discernible exchange to software business in recent years has been the introduction of evince “Agile”. Agile software development has been used by industry to create a more flexible and lean software development process, i.e making it possible to develop software at a faster rate and with more agility during development. Popular methods in the agile ecosystem have a broad range of characteristics. Methods like SCRUM, Extreme programming (XP), Feature driven Development (FDD), Adaptive software development (ASD) etc are increasingly being used to develop software using an adaptation approach rather than a predictive one. But, there is a scarcity of the resources which describe on how these resources can be integrated with the agile methodologies. This paper basically reviews different agile methods, how they are divergent from the conventional process methods, the pros and cons of applying agile processes to the research projects, and what are the difficulties faced during enforcement of agile methodology in the project.
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