Wireless Communications and Mobile Computing

Review Article

A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

Table 1

Classification of the hierarchical-based routing protocols for MWSNs.
ProtocolControl manner Mobile elementMobility patternNetwork architectureClustering attributesProtocol operationPath establishmentCommunication
paradigm		Radio modelProtocol objectivesApplications
Cluster propertiesSensor capability
Cluster sizeCluster densityIntra/intercluster routingStability
LEACH-Mobile 2006 [27]DSensor nodesNABlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode centricFirst OrderMaximizing lifetime; support mobilityTime-driven applications
LEACH-ME 2008 [28]DSensor nodesRandom using RPGMBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode centricFirst OrderImproving the packet delivery rateTime-driven applications
MSRP 2010 [29]HOne sinkControlledTree-basedEqVSH/MHVHomoQuery-basedProactiveData centricNAMaximizing lifetime; solving the hotspotOn-demand applications
such as intrusion detection
CBR-Mobile 2011 [30]DSensor nodesRandom using RWPBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode centricRealisticMaximizing the delivery ratio; minimizing the average delayMonitoring and tracking applications
MBC 2011 [31]DSensor nodesRandom using RWPTree-basedEqVSH/MHVHomoCoherent-basedProactiveNode centricFirst OrderImproving packet delivery rate, energy consumption, and control overheadExploration, wildlife protection, and traffic control application
EECC 2012 [32]DOne sinkPredefinedBlock-basedEqVSH/MHVHomoCoherent-basedProactiveNode centricFirst OrderMaximizing lifetime; solving the hotspotOn-demand applications
MIEEPB 2013 [33]COne sinkPredefinedChain-based——MH/SH—HomoQuery/noncoherentProactiveData centricFirst OrderImproving energy utilization and delayTime-driven applications
ECBR-MWSN 2013 [34]CSensor nodesRandom using RWPTree-basedEqVSH/MHVHomoCoherent-basedReactiveNode centricFirst OrderMaximizing lifetime; balancing loadMonitoring and tracking applications
MACRO 2014 [35]DSensor nodesRandom using RWPTree-basedEqVSH/MHVHomoQuery-basedHybridData centricRealisticIncreasing the route reliabilityOn-demand applications
CIDT 2014 [36]CSensor nodesRandom using RWPTree-basedEqVSH/MHVHomoCoherent-basedProactiveNode centricFirst OrderImproving the lifetime, throughput, delivery ratio, and link stabilityCivil and military applications
VELCT 2015 [37]CSensor nodesRandom using RWPTree-basedEqVSH/MHVHomoCoherent-basedProactiveNode centricFirst OrderImproving the lifetime, throughput, delivery ratio, delay, and link stabilityCivil and military applications
PHASeR 2015 [38]DSensor nodesRandom using RWPTree-basedEqVMHVHomoMultipath-basedProactiveNode centricRealisticEnhancing the delay and packet delivery ratioTime-driven applications such as radiation mapping
Optimizing LEACH 2015 [39] DOne sinkPredefinedBlock-basedUneqVSH/SHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; minimizing energy consumptionTime-driven applications
Ring protocol 2015 [40]HOne sinkRandomBlock-basedEqVMH/SHVHomoNegotiation-basedReactiveNode/location centricRealisticMaximizing lifetime; minimizing packet delay; solving hotspot problemEvent-driven applications
Time-driven applications
EMMS 2016 [41]CMultiple sinksControlledTree-based——MH—HomoCoherent-basedProactiveNode centricRealisticMaximizing lifetime; balancing loadTime-driven applications
Anycast 2016 [42]DSensors & multiple sinksRandomTree-based——MH—HomoCoherent-basedHybridNode centricFirst OrderMaximizing lifetime; reducing network trafficOn-demand applications
PSO-MBS 2011 [43]COne sinkControlledBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; improving data deliveryTime-driven applications
GAROUTE 2011 [44]CSensor nodesRandom using RWPBlock-basedEqVSH/MHVHomoCoherent-basedProactiveNode centricFirst OrderMaximizing lifetime; improving stabilityTime-driven applications
Rendezvous algorithms 2012 [45]COne sinkRandom
Controlled		Tree-basedEqVMH/SHVHomoCoherent-basedProactiveNode/location centricRealisticData collection, energy savingTime-driven applications
Sudarmani and Kumar  2013 [46]COne sinkControlledBlock-basedEqVSH/SHVHeteroCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; solving hotspot problem; load balancingTime-driven applications
CAGM 2015 [47]COne sinkRandomBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; energy consumption balancingTime-driven applications
NSGAII-RP 2015 [48]CSensor nodesControlledBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime and coverageMonitoring and tracking-based applications
OZEEP 2015 [49]HSensor nodesRandom using RWPBlock-basedEq/UneqVSH/MHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; load balancing; fault tolerance; scalabilityTime-driven applications
LOA-MSN 2015 [50]HMultiple sinksControlledBlock-basedEqVSH/SHVHomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; solving hotspot problemTime-driven applications
MLS 2015 [51]COne sinkPredefinedTree-based——MH—HomoCoherent-basedProactiveNode/location centricFirst OrderMaximizing lifetime; solving hotspot problemTime-driven applications
Yue et al. 2016 [52]COne sinkControlledBlock-basedEqVMH/SHVHomoCoherent-basedProactiveNode/ location centricFirst OrderEfficient data collection; improving throughput; maximizing lifetimeTime-driven applications
C: centralized, D: distributed, H: hybrid, Eq: equal, Uneq: unequal, F: fixed, V: variable, SH: single-hop, MH: multihop, Homo: homogeneous, Hetero: heterogeneous.