Table 3: Performance trade-off made by protocols.

Technique Routing criteriaDistinguished featuresAdvances achievedTrade-offsRemarks

RMSMS with random trajectoryRandom deployment of nodes. Transmit data to MS at minimum distanceHigh Throughput, less end to end delayLess stability, packet dropped, PLMinimizing energy consumption due to absence of clustering

DMSMS with defined trajectoryRandomly deployed nodes with direct transmission to MS on defined trajectoriesLonger stability period, less end to end delay, less PLLess throughputMinimizing end to end delay, energy consumption is minimum due to direct communication with MS

DREEM-MEStatic clustering and multihopStatic clustering, transmission at minimum distance. Uniform random deployment of nodesLonger stability period, less end to end delay, packet droppedLess throughputStatic clustering, transmission at minimum distance. Uniform random deployment of nodes

DYN-NbCClustering and MSAdaptive clustering with sink mobility in specific regions. Random deployment of nodesIncreased throughputMin stability period, end to end delay, packet droppedCH selection is on the basis of LEACH criteria that considers probability only

FTIEEClusteringFixed clustering on the basis of distance from sink. Machine learning criteria for CH selection. Node deployment is randomHigh stability, less packet droppedLonger end to end delayDue to fixed clustering and machine learning technique energy consumption of nodes is minimized. However if sink mobility is introduced, further load from the CH can be reduced

UC-MSUC and MSUneven clustering by following LEACH criteria and MS. Random deployment of nodesEnhanced throughputStability period, E2ED, packet droppedThis protocol uses LEACH criteria for CH selection which do not consider residual energy for CH selection