Projects & Publications

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Nigam, Aviral, Ankur Singh, Dimpi Saikia, and Mukesh Mali. Information Warfare System. National Institute of Technology, Calicut, Report. Abstractiws_report.pdf

Military system simulations are usually used to train soldiers to perform missions and to learn to work together in teams and across command structures, or carry out the advanced concept technology demonstrations for operational applications of equipment systems on future battlefield.
It is a complex, dynamic, and information centric system with heterogeneous, autonomous members. To simulate its action, multi-agent based modeling technology is applied to set up the mappings from the members in IWS to respective agents, by which the distributed multi-agent system is designed. Thus, the multi-agent interactions centric platform-level virtual battlefield simulation system and its agent model are designed.
The established demonstration system proves the feasibility and efficiency of our model, and shows its advantages in realizing real time platform-level computer simulation for military systems.
The focus of this project is the MAS theory and its application in combat simulation.

Nigam, Aviral, Snehal Chauhan, and Varsha Murali. Rent or Self-execute? Resource Management Strategies for Cloud Providers In Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference. Mysore: IEEE, 2013. Abstractconference.pdf

As Cloud Computing is an emerging field, many
improvements are being proposed to provide users with better
services and facilities. This paper deals with the illusion of infinite
resource availability on demand, one of the new aspect in Cloud
Computing. A new approach has been discussed here to continue
providing this illusion. This work provides an efficient way for
the cloud provider to decide on his strategies to execute a job
i.e., whether to use his own services to execute (self-execute)
or to pay rent to other cloud providers. A utility function has
been formulated that considers the factors related to resource
requirement, execution time and waiting probability. Further, a
combination of forecasting models and game theoretic approaches
have been proposed to identify the best strategy based on the
values from this utility function. The design considers both the
previous as well as current demand to decide on the provider’s
strategy so as to make the results more accurate. The results
obtained show an almost equal distribution of Rent and Selfexecute

Nigam, Aviral, and Manish Kumar Yadav. A Study on Various Methods of Sudoku Solving. National Institute of Technology, Calicut, Report. Abstractgenetic_algorithms.pdf

The Sudoku puzzle is most frequently a 9 X 9 grid made up of 3 X 3 sub-grids. Some cells already contain numbers. The goal is to fill in the empty cells, one number in each, so that each column, row, and sub-grids contain the numbers 1 through 9 exactly once. Each number in the solution therefore occurs only once in each of three directions. Most puzzles are ranked as to difficulty, but the rankings vary from designer to designer. Genetic Algorithms are adaptive heuristic search and an optimization algorithm premised on the mechanism of biological evolution of chromosomes. The basic concept of Genetic Algorithm is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin. Cultural Algorithms are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the population component. In this sense, Cultural Algorithms can be seen as an extension of a conventional Genetic Algorithm. The objective of this paper is to review the concepts of Genetic Algorithm and Cultural Genetic Algorithm and finding an efficient method for solving Sudoku puzzles.

Nigam, Aviral, Snehal Chauhan, and Varsha Murali. Various Methods of Load Balancing in Cloud Computing. National Institute of Technology, Calicut, Report. Abstractproject_report.pdf

Cloud computing is the use of computing resources (hardware and software)
that are delivered as a service over a network. Load balancing is a computer
networking methodology to distribute workload across multiple computers
or a computer cluster, network links, central processing units, disk drives,
or other resources, to optimize resource utilization, maximize throughput,
minimize response time, and avoid overload. With Clouds becoming one of
the most important concept in the field of internet and resource sharing, it is
of utmost importance to optimally balance the tasks and loads in the Cloud.
The objective of this work is to study various load balancing algorithms used
in Clouds and to design a new algorithm for tackling this issue.

Nigam, Aviral. Virtual Chemistry Lab and Interactive Applets. Mumbai: Indian Institute of Technology, Bombay, Report. AbstractVirtual_Chemistry_Lab.pdf

The aim is to illustrate the concepts of chemistry through a Virtual Chemistry Lab (VCL). The VCL will allow students to carry out high school level experiments by utilization of standard equipment such as beakers, burettes, flasks and pipettes, and common chemical reagents like acids and bases. We would be using Java Applet graphics to depict the equipment and student actions in a realistic manner. The VCL would allow teachers to set up demonstration experiments from which the students can observe and learn. Finally all student actions will be automatically captured and the educators will be able to replay the experiments and evaluate the student.

Nigam, Aviral. "Web Crawling Algorithms." International Journal of Computer Science and Artificial Intelligence 4 (2014): 63-67. Abstractweb_crawling_algorithms.pdf

As the size of the Internet is growing rapidly, it has become important to make the search for content much faster and more accurately. Without efficient search engines, it would be impossible to get accurate results. To overcome this problem, software called “Web Crawler” is applied which uses various kinds of algorithms to achieve the goal. These algorithms use various kinds of heuristic functions to increase efficiency of the crawlers. A* and Adaptive A* Search are some of the best path finding algorithms. A* uses a best-first search and finds a least-cost path from a given initial node to a goal node. In this work, a study has been done on some of the existing Web Crawler algorithms and A* / Adaptive A* method has been modified to be used in this domain. A* / Adaptive A* method being heuristic approaches can be used to find desired results in web-like weighted environments. We create a virtual web environment using graphs and compare the time taken to search the desired node from any random node amongst various web crawling algorithms.