Scientific Publications
Browse our catalog of peer-reviewed scientific articles
Research Categories
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Computer Science & Engineering
Core computing paradigms, algorithm design, software architectures, advanced computing theory, and hardware engineering.
Computer Networks
Network architectures, wireless ad-hoc protocols, vehicular networks (VANET), buffering, and communications.
Electronics Department
Circuits, semiconductor devices, flexible electronics, solar array modeling, signal processing, and photonics.
Civil Engg
Structural analysis, thermal stability of fluid layers, environmental infrastructure, and applied materials engineering.
Recent Publications (9)
Swarm Intelligence Technique on Ant Colony Optimization Cluster Algorithm
This project proposes an swarm intelligence technique on ant colony optimization cluster algorithm. It introduces new adjustment process, which adjusts the cluster generated by the carry process iteratively. Cluster analysis is a data mining technology designed to derive a good understanding of data to solve clustering problems by extracting useful information from a large volume of mixed data elements. This algorithm can improve the efficiency and the convergence of the cluster theoretically. Ant colony algorithm can form more accurate and stable clusters than the K-modes Algorithm, Information Entropy-Based Cluster Algorithm and LF Algorithm Scalability experiments show that the running time has an obvious linear relationship with the size of data set. This Algorithm can handle large datasets. The system aim is to increase the classification performance through the Ant Colony Optimixation Algorithm and to decrease the false alarm rate.
ONLINE SECURITY FOR PRIVATE CLOUD SECURITY
A cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the Internet. Storing data in a third party’s cloud system causes serious concern over data confidentiality. General encryption schemes protect data confidentiality, but also limit the functionality of the storage system because few operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions are challenging when the storage system is distributed and has no central authority. Propose a threshold proxy re-encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also let a user forward data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and forwarding. Analyze and suggest suitable parameters for the number of copies of a message dispatched to storage servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment between the number of storage servers and robustness.
FIN ALGORITHM FOR GENERATING FREQUENT ITEMSET IN BIG DATA
Big data being an emerging research area, handling issues like storing, searching, sorting, retrieving, securing, analyzing and visualizing are of immense importance. Association rule mining helps to analyze the customer behavior in the market thereby excelling business intelligence. In this paper we propose a novel FIN algorithm with map-reduce concept to mine frequent itemset in big data which helps in increase the performance by parallel processing. The map-reducer function helps in performing the parallel execution on identifying the frequent itemset by using FIN algorithm. The performance of FIN is faster when compared with traditional algorithm Apriori, FP growth. This will also be applicable when it is perform in big data. The effectiveness of the algorithm is increased because of parallelization. This proposed strategy ca
DESIGN OF CLUSTER NETWORK MANAGEMENT PROTOCOL FOR UNDERWATER WIRELESS SENSOR NETWORK
Wireless sensor network is a clustered form of network with comprises of large number of sensor nodes .Nodes that are controlled by clustered node are very efficient for data transmission. Sensor nodes are continuously monitored by the network. The detection of sensor finds the way for the data transmission from the sender to the receiver.A sensor node has the less consumption of energy with it retain or transmit the data in the network.
DISCOVER EMERGING TOPICS IN SOCIAL NETWORKING
Web Mining is the retrieval of useful information from web. The information exchanged in social network posts includes not only text but also images, URLs, and videos. This system focuses on mentions of users – links between users that are generated through replies, mentions, and retweets. The probability model is proposed to detect the emergence of a new topic from the anomalies measured through the model. The technique demonstrated on trained dataset using web application. Aggregating anomaly scores from hundreds of users, shows that detecting emerging topics only based on the reply/mention relationships in social network posts. The experiments show that the proposed mention-anomaly-based approaches can detect new topics at least as early as text-anomalybased approaches.
DETECTION OF MALICIOUS NODES IN MANETs
Mobile Ad hoc Networks (MANETs) is a kind of network composed of mobile devices distributed in a geographic area where there is a lack of fixed infrastructure or centralized administration. Nodes within communication range communicate directly, while those out of range make use of other nodes to forward the message to given destination. In MANETs packet dropping attacks have remarkable consequences among other threats. Malicious nodes drop received data or control messages instead of relaying them, thus by affecting the traffic in the network. Blackhole attacks imply malicious nodes dropping all the packets they receive. Grayhole attacks are similar but malicious nodes drop packets statistically by following a predetermined probability distribution. It should be emphasized that recognizing the actual cause(mobility, collision, errors, malicious behavior)for packet dropping in MANETs is still an open challenge, which is necessarily be addressed in order to reduce the number of false positives in IDS schemes. An Analytical model is introduced in order to distinguish between the legitimate packet dropping and malicious packet dropping behaviors. For that an enhanced windowing method is used for collecting the features from the network. From the features, the probabilities are to be calculated that are involved in analytical model. Based on the dropping probability that is estimated, concluded that the analyzed packet dropping node is malicious or legitimate by comparing with the predefined detection threshold.
CONTENT BASED FILTERING WITH BLACKLIST
One fundamental issue in today’s online social networks (OSNs) is to give users the ability to control the messages posted on their own private space and to avoid the unwanted content that is displayed. Right now, OSNs provide only little support to this requirement. To fill the gap, a system is proposed which allows OSN users to have a direct control on the messages posted on their private space. This is achieved through a flexible rule-based system that allows the users to customize the filtering criteria to be applied to their space, and a Machine Learning-based soft classifier that automatically labels messages in support of content-based filtering. Short-text classifier is used which includes two levels; in the first level short-texts are labeled with crisp Neutral & non-neutral labels. The second level soft classifier acts on the non-neutral short texts, produces estimated appropriateness or “Gradual Membership” for each of the conceived classes, this list of grades is then used by the subsequent phases of the filtering process.
AUTOMATED TESTING TOOL FOR SOFTWARE QUALITY ASSURANCE
The general undertaking of the software engineering is to make sure the deliverance of high quality software to the customer. To certify high quality software, it is mandatory to test software. Testing is an important part of software engineering. In software testing there are number of underlying issues like effective generation of test cases, prioritisation of test cases which need to be handled. This automated testing tool mainly depends on these four perspectives: test strategy, test case generation, test execution and test evaluation. Test strategy is a compilation of events that determines the testing approach to be followed by the testing panel. The test case generation refers to the generation of testcases based on the certain application.The test execution explains about the execution of those tests then comparing the estimated result with tangible result. The test evaluation investigates the test cases and helps us to generate test summary report and software quality assurance report automatically. The intention of producing this tool is to generate test cases automatically and to decrease the cost of testing in addition to mount up the time of deriving test cases manually. Hence this system helps to progress overall eminence of the software.
A Survey of Software Development using optimization techniques
Software is becoming an increasingly critical-competitive factor because of the high cost of developing software and its extra-ordinarily high busi-ness impact. Although there are challenges in software development including accelerated and bug free software delivery which are correlated with business requirements. Now a days, new process models are introduced for different requirements. In this paper, we can discuss software development based optimization techniques.