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Since sensor networks can be composed of a very large number of nodes, the developed protocols for these networks must be scalable. Moreover, these protocols must be designed to prolong the battery lifetime of the nodes. Typical existing routing techniques for ad hoc networks are known not to scale well. In multihop wireless networks the nodes generally wireless devices are usually powered by batteries only and have limited computing capability while the number of such devices could be large. Energy conservation and Scalability are probably two most critical issues in designing protocols for multihop wireless networks. The nodes have limited initial amounts of energy that is consumed in different rates depending on the power level and the intended receiver. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. For this reason, an algorithm named Localized Energy-Aware Restricted Neighborhood routing (LEARN), which can guarantee the energy efficiency of its route if it can find the route successfully. We then theoretically study its critical transmission radius in random networks which can guarantee that LEARN routing finds a route for any source and destination pairs asymptotically almost surely is introduced. In a geographical routing algorithm, the packets are forwarded by a node to its neighbour based on their respective energy based technique. Also extend the further routing protocol into 3D three-Dimensional networks.