Research papers

Following are the research papers published from the department:

1) Evolution Induced Secondary Immunity: An Artificial Immune System based Intrusion Detection System 

Authors: Divyata Dal, Siby Abraham, Ajith Abraham, Sugata Sanyal and Mukund Sanglikar 

Abstract: The analogy between Immune Systems and Intrusion Detection Systems encourage the use of Artificial Immune Systems for anomaly detection in computer networks. This paper describes a technique of applying Artificial Immune System along with Genetic algorithm to develop an Intrusion Detection System. Far from developing Primary Immune Response, as most of the related works do, it attempts to evolve this Primary Immune Response to a Secondary Immune Response using the concept of memory cells prevalent in Natural Immune Systems. A Genetic Algorithm using genetic operators- selection, cloning, crossover and mutation- facilitates this. Memory cells formed enable faster detection of already encountered attacks. These memory cells, being highly random in nature, are dependent on the evolution of the detectors and guarantee greater immunity from anomalies and attacks. The fact that the whole procedure is enveloped in the concepts of Approximate Binding and Memory Cells of lightweight of Natural Immune Systems makes this system reliable, robust and quick responding

2) Finding numerical solution to a Diophantine Equation:simulated annealing as a viable search strategy 

Authors: Siby Abraham ,  Mukund Sanglikar  

Abstract: This paper introduces Simulated Annealing as a viable informed search strategy to find numerical solutions to Diophantine Equations, for which there exists no general method of finding solutions. The methodology proposed uses a tried and tested heuristic as the energy function to guide the search process. It behaves like a typical steepest valley descending till it reaches states facing only worse states as possible successors. Then the difference in heuristic function values of the current state and the candidate successor state is taken as the energy difference (ΔE). The heuristic function value of the initial state is taken as the time-varying parameter ‘Temperature’ (T), which is reduced gradually using a domain dependent annealing schedule. Here, the transition from a current state to a successor state depends on the satisfaction of the probability condition e - (ΔE / T). Experimental results performed on Diophantine Equations of varied types validate the effectiveness of the procedure.

3) Solution to Diophantine Equation: A Genetic Algorithm Application 

Authors: Siby Abraham ,  Mukund Sanglikar  

Abstract:  This paper attempts to develop a Diophantine Equation Solver using Genetic Algorithm. It shows how the directed random search procedure of Genetic Algorithm (GA) reduces the search procedure substantially and comes to a solution. The GA developed in this paper obtains quick solutions to the general diophantine equation given by f(a1, a2, ……., an,x1,x2,…….,xk)=N, where ai and N are integers. A chromosome is represented by integers within the supplied range of values. The evolution process is carried out by generating off-springs using genetic operators - mutation and crossover - on a population of five chromosomes. The pure random selection of these operators and subsequent random exchange of genes, in case of mutation or swapping of genes from the randomly generated crossover point onwards, in case of crossover results in diverse nature of chromosomes in the evolution process. In order to overcome plateau and reduce premature convergence in the fitness landscape, we apply biological concept of host-parasite co-evolution. The evaluation function constructed acts as an automatically defined function, which restricts the occurrence of unwanted and already tested chromosomes. The GA developed offers solutions to a diophantine equation within a given range. The methodology also offers an option to switch over to a new initial population of chromosomes when the existing population becomes obsolete.

4) Nature’s way of Avoiding Premature Convergence: A case study of Diophantine Equations 

Authors: Siby Abraham ,  Mukund Sanglikar  

Abstract: This paper proposes natural phenomenon of Host Parasite Co-Evolution as a strategy to avoid premature convergence in the fitness landscape of a Genetic Algorithm developed to find numerical solutions to diophantine equations given by

f(a₁, a₂, a₃, …, a_n, x₁, x₂, x₃,…, x_n) = N where a _i and N are integers.

The procedure described avoids the occurrence of local hilltops as premature converging points in the search space of the GA developed. It uses selection, inversion and crossover as genetic operators. As the genetic process is evolved, the procedure gets converged prematurely. These premature converging points are taken as attacks by parasites. The candidate solutions are trained to be defensive to these attacks using a composite evaluation function. The parasites, in turn, develop new attacks in the form of creating new converging points. This continuous process of avoidance by hosts and attacks by parasites reciprocally induce evolution. The pressure of this evolving attacks and counter attacks works effectively as a powerful optimization tool and hence directs the procedure to discover a solution by generating untested, diverse and fresh candidates. The paper tries to establish statistically the diversity of attacks of parasites as it happens in nature. It also attempts to demonstrate the inherent relation between number of attacks by parasites and number of generations produced irrespective of the degree of the equation and the number of variables used.

5) Finding Solution to a Hard Problem: An Evolutionary and Coevolutionary Approach  

Authors: Siby Abraham, Mukund Sanglikar  

 Abstract: This paper introduces a strategy, which uses Genetic Algorithm as an evolutionary technique and Competitive Two-population Co-evolution as a co-evolutionary technique for finding a solution to a hard problem. The strategy is applied to find numerical solution to a Diophantine Equation, for which there does not exist a method to solve. The GA uses selection, inversion and crossover as genetic operators and helps to undergo evolution on a population of twenty-five chromosomes. The local optimum points encountered in the fitness landscape during the evolution are tackled using Competitive Two-population Co-evolution by creating populations of local optimum points and fitness values of new untested and fit chromosomes. The paper shows that the strategy is continuous, random, evolutionary and adaptive in nature and is open to the concept of introduction of a fresh population in the rare event that the present population looses its diversity and hence becomes obsolete

6)  Particle swarm optimisation based Diophantine equation solver 

Authors:Siby Abraham ,  Sugata Sanyal, Mukund Sanglikar  

Abstract: The paper introduces particle swarm optimization as a viable strategy to find numerical solution of Diophantine equation, for which there exists no general method of finding solutions. The proposed methodology uses a population of integer particles. The candidate solutions in the feasible space are optimized to have better positions through particle best and global best positions. The methodology, which follows fully connected neighbourhood topology, can offer many solutions of such equations. 

7) Defect-based Reliability Analysis Model for Business Systems      Deployed on a large Scale

Authors: Nita Sarang, Mukund A. Sanglikar 

Abstract: Quality of software releases is paramount in business systems deployed on a large-scale. As the deployed software systems grow in functionality, the software maintenance task becomes increasingly complex; maintaining quality control over the life of the software is a challenge. We undertake an analysis of defect data from two product-lines in a specific business domain. We use hypothesis testing to understand the underlying software maintenance process and establish the defect models. The defect models are used to define an optimal level of testing that meets the software reliability requirements. 

8) An Analysis of Effort Variance in Software Maintenance Projects

Authors: Nita Sarang, Mukund A. Sanglikar 

Abstract: Quantitative project management, understanding process variations and improving overall process capability, are fundamental aspects of process improvements and are now strongly propagated by all best-practice models of process improvement. Organizations are moving to the next level of quantitative management where empirical methods are used to establish process predictability, thus enabling better project planning and management. In this paper we use empirical methods to analyze Effort Variance in software maintenance projects. The Effort Variance model established was used to identify process improvements and baseline performance.

9) Computational Diagnosis of Learning Disability 

Authors: Kavita Jain, Pooja Manghirmalani, Jyotshna Dongardive and Siby Abraham  

Abstract:  The paper proposes a perceptron based artificial neural   network model for diagnosing learning disability using curriculum based test conducted by special educators in medical environment. The model comprises of a single input layer with eleven units which correspond to different sections of a conventional test and one output unit. The method is not only devoid of typical computational complexity and sophistication associated with other methods but gives comparable experimental results on detection measures like accuracy, sensitivity and specificity.

10) Building Consensus of Human Papillomavirus using Genetic Algorithm

Authors:  Aditya Bir, Jyotsna Dongerdive, Suruchi Jamkhedkar, Siby Abraham.

Abstract: The paper introduces novel three tier architecture to
build consensus of Human Papillomavirus (HPV). The proposed procedure is based on simulation and uses all complete genomic DNA sequences of registered HPV strains available in NCBI GenBank. It uses the multiple sequence alignment tool Clustal X to align these sequences.  Genetic Algorithm (GA) is used to evolve an optimized population of complete genomic DNA sequences. The GA, which uses domain specific genetic operators like migration, rank selection, mutation and crossover, adopts a novel methodology in defining the fitness function. A modified approach of the Weight Matrix Algorithm is applied on the optimized and evolved population to find a consensus of HPV. The effectiveness of the procedure is validated with experimental results.

11) Finding Motifs Using Harmony Search

Authors:  Jyotsna Dongerdive, Aarti Patil, Aditya Bir, Suruchi Jamkhedkar, Siby Abraham. 

Abstract:  The paper proposes a novel methodology for finding motifs of biological sequences. It uses music inspired meta-heuristic optimization technique called harmony search to find Motif. The model is based on randomly generated l-mers as the initial harmony memory. Pitch adjustment and random selection are used to generate new l-mers, which are adjudged by a defined objective function. The proposed method is experimentally validated using sequences of Human Papillomavirus strains obtained from accredited and authorized sources.

12) Envelope Model: Data Access from any where 

Authors:  Sushil Kulkarni  

Abstract In this paper, a definition of mobile database and mobile transaction with illustrations from spatial and temporal databases are given. Corresponding to mobile transaction mobile query is defined. New model called Envelope model is presented to execute a mobile query using various base stations of the closed spheres. A mobile query is defined as the union of jumping queries and contains only one unary or binary operator operating on database. A mobile transaction is the union of jumping transactions where each jumping transaction is the unit of execution at the base station. The jumping condition is checked prior to the starting of each jumping query at the base station. This model is implemented using developed environment called Data Invoking Capsule. It is located at every base station and its main job is to transfer the messages from one base station to another, executing jumping queries and storing envelopes. A mobile unit makes a request to execute mobile query to base station called initializer, who creates a basket that store jumping query number and the directed parse tree. This basket is carried by the mobile unit till mobile query is completely executed. Directed parse tree is created by an initalizer using parse tree. It gives guidelines for execution of jumping query at the respective base stations. After the jumping query is executed an envelope is created, that store jumping query number and the result obtained by executing jumping query. Envelope flies from one base station to another as required by another base station for executing next jumping query under the guidelines of directed parse tree. Every base station may not have the required database on which jumping query is executed so the method is proposed to execute it. Algorithms for creating directed parse tree and an envelope model are provided. Parallel execution of jumping transaction at a base station is also discussed. Envelope model for mobile transaction is introduced.

13) Spatio-Temporal Schema Model and Carrie and Courier mobile query processor for Spatio-Temporal database 

Authors:  Sushil Kulkarni, Dr. M.A. Sangalikar  

Abstract:  Geographical Information Systems and their underlying support, spatio-temporal database systems, deal with data related to changes in geographical space according to time. The space of interest is two dimensional abstraction of the surface of the earth and the change of attribute instances related to it. In this paper, we propose Y- schema, which will enable to handle spatio-temporal data. Also we know that in urban area, mobile users are increasing day by day and there is a demand of retrieving, manipulating spatio-temporal data. Here we are proposing a query processor called Carrier and Courier processor to handle the spatio-temporal mobile queries.

13) Envelope Transaction Mobile Model 

Authors:  Sushil Kulkarni, Dr. M.A. Sangalikar  

Abstract:  A long lived mobile transaction is divided into different sub-transactions called jumping transactions. The proposed model explains the commit of jumping transaction at the server or at mobile unit. Model takes care of disconnection because of jumping nature of mobile unit. This model relaxes isolation property using intension commit of jumping transaction.

14) Lock Mechanism for a cluster of peers 

Authors:  Sushil Kulkarni, Dr. M.A. Sangalikar  

Abstract:  A new approach for caching data objects and locks by a centroid from a server in a cluster of peers using ad hoc transactions is presented. A cluster of peers is formed by a set of mobile hosts, which are clustered around a single mobile host called a centroid. A set of mobile hosts are called peers. A centroid is formed as a temporary work group for processing and exchanging information. In life cycle of a mobile transaction processing system, data is cached from the server and a centroid is disconnected from the server to create its own cluster of peers.  A dynamically configurable data processing space, called an envelope repository, is created to process various transactions at the centroid. The processed data is kept in an envelope at the private work space of the centroid and is brought to the envelope repository whenever required. 

15) Envelope Transaction Mechanism for a Cluster of Peers

Authors:  Sushil Kulkarni, Dr. M.A. Sangalikar  

Abstract:  A new approach for mobile transaction processing is presented in a cluster of peers. A cluster is a dynamic collection of mobile hosts called peers and are clustered around a single mobile host called a centroid to form a temporary work group for processing and exchanging information. All peers are connected to the centroid using a short range wireless network. All peers and the centroid are members of a peer connected set. The centroid is chosen in such a way that it has a strong connection to the mobile support station. After collecting data from a server, the centroid is free to disconnect from the server and ready to create its own cluster of peers. A dynamically configurable data processing space, called envelope repository, is created to process various transactions at the centroid. The processed data is kept in an envelope at a private work space of the centroid and is brought to the envelope repository whenever required. Peer initiates a jumping transaction to fetch data objects to the centroid. The jumping transaction initiates an envelope transaction to acquire the necessary locks on data objects at envelope repository. After getting the locks, pseudo transaction processes the data objects to give the result stored in an envelope. Envelope pseudo write protocol is designed to make jumping transactions globally serialized.