Machine Intelligence Research Labs

Gwalior, India

Machine Intelligence Research Labs

Gwalior, India

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Shrivastava L.,Madhav Institute of Technology and Science | Tomar G.S.,Machine Intelligence Research Labs | Bhadauria S.S.,Madhav Institute of Technology and Science
International Journal of Grid and High Performance Computing | Year: 2011

Grid computing came into existence as a manner of sharing heavy computational loads among multiple computers to be able to compute highly complex mathematical problems. The grid topology is highly flexible and easily scalable, allowing users to join and leave the grid without the hassle of time and resource-hungry identification procedures, having to adjust their devices or install additional software. The goal of grid computing is described as "to provide flexible, secure and coordinated resource sharing among dynamic collections of individuals, institutions and resources". AODV is an on-demand (reactive) algorithm capable of both unicast and multicast routing. In this paper, AODV has been modified by varying some of the configuration parameters used in this algorithm to improve its performance. This modified protocol i.e. A-AODV (advanced ad hoc on demand distance vector) has been compared with AODV in grid environment. The simulations have shown that A-AODV is able to achieve high throughput and packet delivery ratio and average end-to-end delay is reduced. © 2011, IGI Global.


Bouaziz S.,University of Sfax | Alimi A.M.,University of Sfax | Abraham A.,Machine Intelligence Research Labs | Abraham A.,VSB - Technical University of Ostrava
2013 IEEE International Conference on Cybernetics, CYBCONF 2013 | Year: 2013

In this paper, a new hybrid learning algorithm based on the global optimization techniques, is introduced to evolve the Flexible Beta Basis Function Neural Tree (FBBFNT). The structure is developed using the Extended Immune Programming (EIP) and the Beta parameters and connected weights are optimized using the Opposite-based Particle Swarm Optimization (OPSO) algorithm. The performance of the proposed method is evaluated for time series prediction area and is compared with those of associated methods.


Tomar G.S.,Machine Intelligence Research Labs
Proceedings - 2011 International Conference on Communication Systems and Network Technologies, CSNT 2011 | Year: 2011

Use of discontinuities in ground planes or in microstrip lines is currently employed to improve the performance of different passive circuits. It includes size reduction of amplifiers; enhancement of filter characteristics and applications to suppress harmonics in patch antennas. This paper presents an improved method of size reduction of a microstrip antenna using Defected Microstrip Structure. It does so by introducing imperfections in the microstrip antenna on the conducting layer using a DMS designed defect. The design was simulated using IE3D Electromagnetic Simulator. The results are very encouraging as it increases the number of components in a given constant area. On the other hand, a new proposal, called defected microstrip structure (DMS), has been successfully used in reducing the size of, and can be further used as tuning technique for, rectangular patch antennas. © 2011 IEEE.


Shrivastava L.,Madhav Institute of Technology and Science | Tomar G.S.,Machine Intelligence Research Labs | Bhadoria S.S.,Madhav Institute of Technology and Science
Proceedings - 2011 International Conference on Computational Intelligence and Communication Systems, CICN 2011 | Year: 2011

The explosive growth of multimedia data and real time applications have put unexpected load on network and have increased congestion in network, which occurs due to flooding of packets to intermediate node and increase in aggregate demand as compared to the accessible capacity of the resources. In mobile adhoc networks (MANETs) congestion, leads to packet loss, transmission delay, bandwidth degradation and also wastes time and energy on congestion recovery and network maintenance. Most of the existing routing algorithms are not designed to adapt to congestion control for busty traffic. In this paper, a load balanced congestion adaptive (LBACA) routing algorithm has been proposed in the metric: traffic density of neighboring nodes have been used to determine the congestion status of the route and the traffic is distributed to the routes according to traffic density. The proposed algorithm has been simulated on Qualnet 4.5 simulation tool. © 2011 IEEE.


Chaurasia B.K.,ITM University | Verma S.,IIIT Allahabad | Tomar G.S.,Machine Intelligence Research Labs
Proceedings - 2013 International Conference on Communication Systems and Network Technologies, CSNT 2013 | Year: 2013

In this work, we study the application of Perron-Frobenius theorem for computing trust in the VANET environment. Safety critical and safety related messages in a VANET can lead to major changes in the behavior of vehicles moving on the road which can prevent unpleasant traffic situations. False messages can result in serious conditions like collisions. Trust management in VANETs is necessary to deter broadcast of selfish or malicious messages and also enable other vehicles to filter out such messages. A decentralized dynamic trust management system must be scalable with an ability to cope with sparsity of direct interactions. In this work, it is shown that messaging behavior of vehicles can be modeled as a primitive graph. This allows the application of Perron-Frobenius theorem. It is found that the eigenvalues of the matrix corresponding to the interaction graph can be used to compute trust values in the VANET setting. © 2013 IEEE.


Izakian H.,University of Isfahan | Abraham A.,Machine Intelligence Research Labs
Expert Systems with Applications | Year: 2011

Fuzzy clustering is an important problem which is the subject of active research in several real-world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement. However, FCM is sensitive to initialization and is easily trapped in local optima. Particle swarm optimization (PSO) is a stochastic global optimization tool which is used in many optimization problems. In this paper, a hybrid fuzzy clustering method based on FCM and fuzzy PSO (FPSO) is proposed which make use of the merits of both algorithms. Experimental results show that our proposed method is efficient and can reveal encouraging results. © 2010 Elsevier Ltd. All rights reserved.


Liu H.,Dalian Maritime University | Liu H.,Dalian University of Technology | Liu H.,Machine Intelligence Research Labs | Abraham A.,Norwegian University of Science and Technology | And 3 more authors.
Future Generation Computer Systems | Year: 2010

Grid computing is a computational framework used to meet growing computational demands. This paper introduces a novel approach based on Particle Swarm Optimization (PSO) for scheduling jobs on computational grids. The representations of the position and velocity of the particles in conventional PSO is extended from the real vectors to fuzzy matrices. The proposed approach is to dynamically generate an optimal schedule so as to complete the tasks within a minimum period of time as well as utilizing the resources in an efficient way. We evaluate the performance of the proposed PSO algorithm with a Genetic Algorithm (GA) and Simulated Annealing (SA) approach. Empirical results illustrate that an important advantage of the PSO algorithm is its speed of convergence and the ability to obtain faster and feasible schedules. © 2010 Elsevier B.V. All rights reserved.


Liu H.,Dalian Maritime University | Liu H.,Dalian University of Technology | Liu H.,Machine Intelligence Research Labs | Abraham A.,Machine Intelligence Research Labs | And 4 more authors.
Information Sciences | Year: 2012

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.


Zhang X.,Dalian Maritime University | Liu H.,Dalian Maritime University | Abraham A.,Machine Intelligence Research Labs
IEEE Transactions on Services Computing | Year: 2013

Context-aware web services have been attracting significant attention as an important approach for improving the usability of web services. In this paper, we explore a novel approach to model dynamic behaviors of interacting context-aware web services, aiming to effectively process and take advantage of contexts and realize behavior adaptation of web services and further to facilitate the development of context-aware application of web services. We present an interaction model of context-aware web services based on context-aware process network (CAPN), which is a data-flow and channel-based model of cooperative computation. The CAPN is extended to context-aware web service network by introducing a kind of sensor processes, which is used to catch contextual data from external environment. Through modeling the register link's behaviors, we present how a web service can respond to its context changes dynamically. The formal behavior semantics of our model is described by calculus of communicating systems process algebra. The behavior adaptation and context awareness in our model are discussed. An eXtensible Markup Language-formatted service behavior description language named BML4WS is designed to describe behaviors and behavior adaptation of interacting context-aware web services. Finally, an application case is demonstrated to illustrate the proposed model how to adapt context changes and describe service behaviors and their changes. © 2008-2012 IEEE.


Bagwari A.,Uttarakhand Technical University | Tomar G.S.,Machine Intelligence Research Labs
Proceedings - 5th International Conference on Computational Intelligence and Communication Networks, CICN 2013 | Year: 2013

Cognitive radio is the key technology for future wireless communication. Spectrum sensing is one of the most important functions in cognitive radio (CR) applications. It involves the detection of primary user (PU) transmissions on a preassigned frequency band. PU licensed band can be sensed via appropriate spectrum sensing techniques. In this paper, we propose an energy detector utilizing adaptive double-threshold (ED-ADT) for spectrum sensing. Using simulations, a comparative analysis of the Adaptive Double-Threshold Based Energy Detection and Cyclostationary feature detection technique has been carried out in terms of probability of detection alarm (Pd), and total error probability (Pe). Numerical results show that proposed ED-ADT scheme outperforms cyclostationary feature detection by 44.1 % at - 8 dB signal to noise ratio (SNR) in terms of probability of detection alarm (Pd). © 2013 IEEE.

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