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Published Work

Randomized Algorithm to Find Hamiltonian Circuit in Rectangular Grid Graph

Journal Article

Status: Under Review

Analysis of Shortest Path and Minimum Spanning Tree Algorithms

Journal Article

Status: Under Review

Efficient Randomized Algorithms for Graph Theoretic Applications

Doctoral Thesis - July 2016

This thesis provides comprehensive and integrated analysis of randomized algorithms over deterministic algorithms. We have also discussed the detailed literature of the multiobjective shortest path problem and multiobjective spanning tree problem. Deterministic polynomial time algorithms are extensively used for the shortest path and the minimum spanning tree problems. In this thesis, we have presented a randomized algorithm to find Hamiltonian circuit in rectangular grid graphs .

Approach for Processor to Dispatcher Load Balancing in Distributed Networks

Journal Article - March 2016

Kuldeep Sharma & Deepak Garg
International Journal of Next-Generation Computing (IJNGC) Vol 7, Issue 1 MARCH 2016 ISSN 2229-4678 (ESCI Indexed).

Multiobjective - Shortest Path and Spanning Tree

Journal Article - July 2016

Kuldeep Sharma & Deepak Garg
Journal of Engineering Technology Vol 5, Issue 1 JUNE 2016 ISSN 2231-4997.

Randomized Algorithms Methods and Techniques

Journal Article - August 2011

International Journal of Computer Applications, IJCA pp. 29-32 Vol 28 Number 11.

Measure Complexity in Heterogeneous System

Book Chapter - July 2011

Kuldeep Sharma
CCIS 169, pp. 656–663, Springer-Verlag Berlin Heidelberg 2011.

Complexity Analysis in Heterogeneous System

Journal Article - January 2009

Kuldeep Sharma & Deepak Garg
International Journal of Canadian Center of Science and Education Vol.2 Page-48 ISSN 1913-8989.

Complexity Analysis Involving Heterogeneous System

Masters Thesis - June 2009

Complexity analysis is one of the most complicated topics in mathematics. It involves an unusual concept and some tricky algebra. This report is a humble trail to demystify the idea in detail. Heterogonous systems are becoming bigger and more complex. While the complexity of large-scale heterogeneous systems has been acknowledged to be an important challenge, there has not been much work in defining or measuring system complexity. Thus, today, it is difficult to compare the complexities of different systems, or to state that one system is easier to program, to manage or to use than another. Here we try to understand the factors that cause heterogeneous systems to appear very complex to people. We define different aspects of system complexity and propose metrics for measuring these aspects. We also show how these aspects affect the system. Based on the aspects and metrics of complexity, we propose general
guidelines that can help to measure the complexity of systems.

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