Sandeep Singh Rawat

Experiments with CPU Scheduling Algorithm on a Computational Grid

The Grid is an emerging technology for enabling resource sharing and coordinated problem solving in dynamic multi-institutional virtual organizations. The resource-matching problem in the Grid involves assigning resources to tasks in order to satisfy task requirements and resource policies. Just as the World Wide Web has changed the way that society deals with information, researchers and educators now expect the grid to change the way that they deal with computing resources and, ultimately, how they deal with knowledge. It is important to mention that, so far, the computational grid has reached a much higher level of maturity than the other types of grid. This paper deals with the implementation of a computer program, which employs Grid Computing (GCs) technique in the quest for reducing the computational time. The program is written in Java and incorporates a grid-gain strategy for faster evolution. The factors like average turn around time, waiting time, and the execution time has been calculated for the given data set. Comparison has been made between the execution times of this algorithm with and without using grid environment and finally given the best choice for CPU scheduling algorithms (i.e. SJF (shortest job first), PRIORITY, and FCFS (first come first serve)) for given data set. In the future in order to construct large, repeatable experiments, a simulation environment designed to examine application scheduling on the grid such as Simgrid [7] could be used.

Probability apriori based approach to mine rare association rules

It is a difficult task to set rare association rules to handle unpredictable items since approaches such as apriori algorithm and frequent pattern-growth, a single minimum support application based suffers from low or high minimum support. If minimum support is set high to cover the rarely appearing items it will miss the frequent patterns involving rare items since rare items fail to satisfy high minimum support. In the literature, an effort has been made to extract rare association rules with multiple minimum supports. In this paper, we explore the probability and propose multiple minsup based apriori-like approach called Probability Apriori Multiple Minimum Support (PAMMS) to efficiently discover rare association rules. Experimental results show that the proposed approach is efficient.

Discovering Rare Association Rules Using Probability Apriori in Grid Environments

It is necessary to combine different technologies for implementing high performance distributed knowledge discovery systems. We think grids can offer an effective support to the implementation and use of parallel data mining systems. In the literature, an effort has been made to extract rare association rules with multiple minimum supports. This paper proposes the development of probability apriori multiple minimum support (PAMMS) algorithm to discover both frequent and rare and association rules in grid environment. Experimental results show that the proposed approach is efficient.

Performance of distributed apriori algorithms on a computational grid

When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing. Grid applications such as astronomy, chemistry, engineering, climate studies, geology, oceanography, ecology, physics, biology, health sciences and computer science often involve large amounts of computing and/or data. For these reasons, we think grids can offer an effective support to the implementation and use of parallel and distributed data mining systems. This paper describes development of parallel and distributed prior algorithm on grid environment. Apriori algorithm along with FP-growth (Frequent Pattern Growth) is implemented on grid network in each grid node, which finds the local support counts and prunes all infrequent item sets. After completing local pruning, each grid node broadcasts messages containing all the remaining frequent patterns to the coordinator. We have compared the output of conventional method of apriori algorithm with FP-tree in both homogenous and heterogeneous environments. Practical datasets are large in nature and taken from the UCI machine repository and are related to adult, mushroom, and letter recognition, are used to measure the system performance. The detailed experiment procedure and result analysis are also discussed in this paper. In future the security issue among different local datasets and the huge communication cost in data migration can be considered.

Secure ATM Door Locking System Using RFID

The recent incident at one of the ATMs in Bengaluru has challenged the security and safety measures currently used at ATM machines. Anyone can enter the ATM cabin without the knowledge or permission of the person currently using the ATM. This increases the possibility of crime-like attacks and theft at gun points, etc., as another customer can easily enter the ATM at any time. The existing system does not have measures to ensure that when a person is using the ATM, no other person is allowed to enter. The proposed system ensures that no other person is allowed to enter the ATM cabin when a person is using the ATM machine. This system will have an electronic lock that has to be unlocked by swiping the person’s debit card, and once the person has entered the cabin the door automatically locks once it is closed. Now, to open the door the same debit card has to be used from inside the cabin. In this way, a person who is waiting outside has no chance of entering the cabin and attack the person who is currently using the ATM. This system not only ensures safety against attacks and thefts but also creates awareness against antisocial elements. After developing this application a fair amount of revenue can be generated by collaborating with banks and the IT industry.

Tracking Lab Activity in Technical Education System: A Case Study at the Guru Nanak Institutions (India)

Nowadays, it can be observed that computer laboratories have encountered many challenges which prevent them to achieve their quality objectives. The management of computer laboratories is a time-consuming manual process which is often a tedious job of maintaining the records in books. In a university, the systems are maintained by the lab assistant/in-charge. To know about who is using the system, they maintain a lab record in which the user details are stored. But this can easily be modified and is not very reliable. In case of any theft, damage, and breakage of components, it is difficult to trace who the actual culprit is. This work helps the lab assistant/in-charge to trace the person who has committed theft, damage, and breakage to components by identifying the system ID.