International Journal on Information Theory (IJIT) - Profile on Academia.edu (original) (raw)
International Journal on Information Theory (IJIT) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Information Theory. Authors are solicited to contribute to the journals by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Information Theory
and applications. Topics of interest include, but are not limited to, the following
The topics suggested by this journal can be discussed in term of concepts, surveys, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal
Address: United States
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Papers by International Journal on Information Theory (IJIT)
This paper presents a lower and upper bound for linear codes which are capable of correcting erro... more This paper presents a lower and upper bound for linear codes which are capable of correcting errors in the form of solid burst of different lengths within different sub blocks. An illustration of such kind of codes has also been provided
Grid computing can involve lot of computational tasks which requires trustworthy computational no... more Grid computing can involve lot of computational tasks which requires trustworthy computational nodes. Load balancing in grid computing is a technique which overall optimizes the whole process of assigning computational tasks to processing nodes. Grid computing is a form of distributed computing but different from conventional distributed computing in a manner that it tends to be heterogeneous, more loosely coupled and dispersed geographically. Optimization of this process must contains the overall maximization of resources utilization with balance load on each processing unit and also by decreasing the overall time or output. Evolutionary algorithms like genetic algorithms have studied so far for the implementation of load balancing across the grid networks. But problem with these genetic algorithm is that they are quite slow in cases where large number of tasks needs to be processed. In this paper we give a novel approach of parallel genetic algorithms for enhancing the overall performance and optimization of managing the whole process of load balancing across the grid nodes.
This paper presents a lower and upper bound for linear codes which are capable of correcting erro... more This paper presents a lower and upper bound for linear codes which are capable of correcting errors in the form of solid burst of different lengths within different sub blocks. An illustration of such kind of codes has also been provided
Grid computing can involve lot of computational tasks which requires trustworthy computational no... more Grid computing can involve lot of computational tasks which requires trustworthy computational nodes. Load balancing in grid computing is a technique which overall optimizes the whole process of assigning computational tasks to processing nodes. Grid computing is a form of distributed computing but different from conventional distributed computing in a manner that it tends to be heterogeneous, more loosely coupled and dispersed geographically. Optimization of this process must contains the overall maximization of resources utilization with balance load on each processing unit and also by decreasing the overall time or output. Evolutionary algorithms like genetic algorithms have studied so far for the implementation of load balancing across the grid networks. But problem with these genetic algorithm is that they are quite slow in cases where large number of tasks needs to be processed. In this paper we give a novel approach of parallel genetic algorithms for enhancing the overall performance and optimization of managing the whole process of load balancing across the grid nodes.