The　tradeoff　between　energy　conservation　and　traffic　balancing　is　a　dilemma　problem　in　Wireless　Sensor　Networks　(WSNs).　By　analyzing　the　intrinsic　relationship　between　cluster　properties　and　long　distance　transmission　energy　consumption,　we　characterize　three　node　sets　of　the　cluster　as　a　theoretical　foundation　to　enhance　high　performance　of　WSNs,　and　propose　optimal　solutions　by　introducing　rendezvous　and　Mobile　Elements　(MEs)　to　optimize　energy　consumption　for　prolonging　the　lifetime　of　WSNs.　First,　we　exploit　an　approximate　method　based　on　the　transmission　distance　from　the　different　node　to　an　ME　to　select　suboptimal　Rendezvous　Point　(RP)　on　the　trajectory　for　ME　to　collect　data.　Then,　we　define　data　transmission　routing　sequence　and　model　rendezvous　planning　for　the　cluster.　In　order　to　achieve　optimization　of　energy　consumption,　we　specifically　apply　the　economic　theory　called　Diminishing　Marginal　Utility　Rule　(DMUR)　and　create　the　utility　function　with　regard　to　energy　to　develop　an　adaptive　energy　consumption　optimization　framework　to　achieve　energy　efficiency　for　data　collection.　At　last,　Rendezvous　Transmission　Algorithm　(RTA)　is　proposed　to　better　tradeoff　between　energy　conservation　and　traffic　balancing.　Furthermore,　via　collaborations　among　multiple　MEs,　we　design　Two-Orbit　Back-Propagation　Algorithm　(TOBPA)　which　concurrently　handles　load　imbalance　phenomenon　to　improve　the　efficiency　of　data　collection.　The　simulation　results　show　that　our　solutions　can　improve　energy　efficiency　of　the　whole　network　and　reduce　the　energy　consumption　of　sensor　nodes,　which　in　turn　prolong　the　lifetime　of　WSNs.