Long Term Evolution (LTE) was designed to provide fast data rates to replace 3G service for mobile devices. As LTE networks and the user base for those networks grow, it becomes necessary for the resources used for those networks to be used as efficiently as possible. This thesis presents an implementation which utilizes an algorithm extended upon the Frank Kelly algorithm to determine resource allocation for UEs and shapes traffic for each UE to meet those allocation limits. The implementation's network represents what an LTE network would do to manage data rates for a UE through a distributed algorithm for rate allocation. The main focus of the implementation is on the UE, where traffic shaping limits application rates by an elastic or inelastic classification through the use of Hierarchical Token Bucket (HTB) queuing disciplines.