Multipath Route Optimization with Multiple QoS Constraints Based on Intuitionistic Fuzzy Set Theory

Table 1

Comparison of multimetric routing protocols.

Protocols	Metrics	Approach	Advantages	Limitations
[17]	Trust relationships	Cloud theory-based decision-making	Implement the conversion between qualitative and quantitative of trust attributes	High computational complexity
[22]	Energy, bandwidth, end to end delay	Vague set theory-based decision-making	Considering multiple attribute constraints	Single path, high computational complexity
[23]	RSSI, delay, and buffer occupancy	QoS attribute criterion-based decision-making	High throughput, low delay, low route lookup frequency	Not solve optimization problems with multiple paths and multiple QoS attributes
[24]	Signal strength, bandwidth, time delay	Analytic hierarchy process-based decision-making	High throughput, low delay	High resource consumption
[25]	Traffic load, mobility, SNR, and transmission delay	Multimetric dynamic weighting-based decision-making	Dynamic adaptation of weight factor	Grade intervals automatically depend on human experience
[26]	Links, paths, subflows	GNN model-based decision-making	High-throughput prediction in multipath routing decisions	Extra overhead for learning