## 2 Literature Survey  
Numerous researchers have done some work to analyze and enhance TFRC. They have used simulations as well as real time test beds. A few of the related results are as follows. In [6], authors identified that TFRC suffers from transmitting multimedia applications over the internet. To increase the performance of TCP Friendly Rate Control, authors proposed an enhanced TFRC which substitutes TCP throughput equation recommended for the TFRC with a linear throughput equation. This linear equation avoids the collapse of the TCP connections and allows the TCP to utilize available bandwidth. This enhanced TFRC avoids congestion more aggressively. Results show that the proposed linear throughput equation gives more throughput than the classical throughput equation and it is more suitable for transmitting multimedia applications. In [7], authors identified that TFRC supports fixed packet size flows and is not suitable for some continuous media applications. For that, authors proposed an enhanced TFRC to support variable size packet flows. They modified numerator of TFRC throughput equation to be the Maximum Transmission Unit (MTU) of the path, so it is suitable for variable packet flows. Modified TFRC behaves appropriately in response to congestion for various scenarios. Simulation results show that it is a superior TFRC protocol that has a wider range of viable packages and therefore more chances of being widely followed on the internet. In [8], authors analyzed TFRC performance over wired and wireless networks, and concluded that TFRC suffers from significant performance degradation in terms of throughput. To enhance the performance of TFRC, authors proposed a new enhanced scheme called TFRC Veno. They replaced Reno equation with Veno equation called TFRC Veno. It is also a kind of enhancement which modifies TFRC at the sender side. TFRC Veno equation is derived from TCP Veno. With this addition of veno equation to TFRC, it results in better throughput and good fairness along with reduced packet loss over wireless networks. Simulation results show that, TFRC Veno improves TFRC performance over wireless networks significantly for multimedia transmission. When compared to Multiple TFRC (MULTFRC), the proposed method is friendlier to other network traffic and it achieves good throughput. In [9] authors analyzed that TFRC protocol uses a slow start algorithm which leads to degrading network performance. To adapt network conditions dynamically, authors proposed a variant of slow start algorithm called Bandwidth Estimation-start (BE-Start) method to improve the performance of TFRC protocol. Simulation results show that with the inclusion of BE-Start algorithm to TFRC, throughput is effectively increased and packet loss is reduced. In [10] authors examined the behavior of TFRC-SP (Small Packets) over live streaming data like audio, VOIP, etc. They identified that TFRC-SP uses a slow start algorithm which is inappropriate for real time applications. To overcome this drawback, authors proposed a quick start algorithm to TFRC-SP, which increases sending rate and reduces unnecessary retransmissions. In [11] authors investigated that TFRC suffers from inaccurate sending rate adjustment in multi hop wireless adhoc networks. To overcome this drawback, authors proposed a variant of TFRC called RE-TFRC (Rate Estimation TFRC) to enhance the performance of TFRC in a wireless adhoc network environment. Result show that reduced round-trip time and better throughput than TFRC. In [12], authors identified that conservativeness causes lower throughput and slower response time for TFRC. To eliminate the problems of TFRC, they proposed Adaptive TFRC (ATFRC) for faster responsiveness and convergence time with less conservativeness than TFRC when bandwidth is available. In [13], authors proposed a non-linear min-max averaging operation for finding packet loss event rate using average loss interval method.