One of the challenging issues in a distributed computing system is to reach on a decision with the presence of so many faulty nodes. These faulty nodes may update the wrong information, provide misleading results and may be nodes with the depleted battery power. Consensus algorithms help to reach on a decision even with the faulty nodes. Every correct node decides some values by a consensus algorithm. If all correct nodes propose the same value then all the nodes decide on that. Every correct nodes must agree on the same value. Faulty nodes do not reach on the decision that correct nodes agreed on. Binary consensus algorithm and average consensus algorithm are the most widely used consensus algorithm in a distributed system. We apply binary consensus and average consensus algorithm in a distributed sensor network with the presence of some faulty nodes. We evaluate these algorithms for better convergence rate and error rate.
This thesis report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2016.
Cataloged from PDF version of thesis report.
Includes bibliographical references (page 41-42).
Department:
Department of Computer Science and Engineering, BRAC University
