Balanced Transmissions Based Trajectories of Mobile Sink in Homogeneous Wireless Sensor Networks

Table 3

Performance trade-off made by protocols.

Technique	Routing criteria	Distinguished features	Advances achieved	Trade-offs	Remarks
RMS	MS with random trajectory	Random deployment of nodes. Transmit data to MS at minimum distance	High Throughput, less end to end delay	Less stability, packet dropped, PL	Minimizing energy consumption due to absence of clustering
DMS	MS with defined trajectory	Randomly deployed nodes with direct transmission to MS on defined trajectories	Longer stability period, less end to end delay, less PL	Less throughput	Minimizing end to end delay, energy consumption is minimum due to direct communication with MS
DREEM-ME	Static clustering and multihop	Static clustering, transmission at minimum distance. Uniform random deployment of nodes	Longer stability period, less end to end delay, packet dropped	Less throughput	Static clustering, transmission at minimum distance. Uniform random deployment of nodes
DYN-NbC	Clustering and MS	Adaptive clustering with sink mobility in specific regions. Random deployment of nodes	Increased throughput	Min stability period, end to end delay, packet dropped	CH selection is on the basis of LEACH criteria that considers probability only
FTIEE	Clustering	Fixed clustering on the basis of distance from sink. Machine learning criteria for CH selection. Node deployment is random	High stability, less packet dropped	Longer end to end delay	Due 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-MS	UC and MS	Uneven clustering by following LEACH criteria and MS. Random deployment of nodes	Enhanced throughput	Stability period, E2ED, packet dropped	This protocol uses LEACH criteria for CH selection which do not consider residual energy for CH selection