Fuzzy Logic Based Path Stability Forecasting Scheme for Improving Data Dissemination in MANETs
Calarany C.1, Manoharan R2

1C. Calarany*, Assistant Professor, Tagore Govt. Arts and Science College, Pondicherry, India.
2R. Manoharan, Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2768-2775 | Volume-9 Issue-3, February 2020. | Retrieval Number:  C5910029320/2020©BEIESP | DOI: 10.35940/ijeat.C5910.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Path stability of the mobile nodes in MANET plays a vital role in effective data dissemination as it depends on factors such as mobility, energy, signal strength. Several studies reveal that the prediction of path stability might provide solutions thereby routing performance can be increased. In most of the protocols route selection is based on metrics namely hop count, energy, etc. The metric namely mobility factor “MF” is used in some of the protocols. These protocols include nodes with less energy or nodes with high mobility which results in loss of path in a short period of time. Since it preserves the neighbor’s history, more control overhead and maintenance complexity exist. Hence, a new metric namely Active Interactive new Neighbor Rate (AINR) has been considered for optimum path selection. In scenarios of path loss, there is an immediate need for alternative paths for continuous data transfer. From literature it is evident that fuzzy logic is more significant in exploring different possible states under path stability determination. Hence a new prediction mechanism based on fuzzy logic has been proposed by considering the Residual Energy (RE), Hop count (Hop) and proposed metric Active Interactive new Neighbor Rate (AINR) as the factors for the prediction of the optimal path. This prediction mechanism is leveraged in MANET scenarios where alternate paths should be available on hand in situations such as battlefield and natural disaster. From the simulation, it has been proved that fuzzy logic prediction model provides better results in terms of various performance metrics such as Throughput, Packet delivery ratio, End-to-end delay, Energy consumption and routing overhead than the existing protocols.
Keywords: Active interactive new Neighbor rate, Energy, Fuzzy logic, Mobile Ad hoc Networks, Path Stability.