## 2 Related Work
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline
**Year** & **Existing Work** & **Network** & **Topology Used** & **Issues Handled** & **Mathematical Model Used** & **Input Conditions** & **Performance Metric** \\ \hline
2009 & Generic model [11] & WSN & Single-hop & Energy replenishment & Markov model & Energy status & Battery capacity, reward rate \\ \hline
2010 & Transmission strategies [12] & WHAN & Single-hop & Energy harvesting, energy efficiency, reliability & Markov model & Current energy level, state of data generation process, battery recharge, packet error probability & Quality of coverage \\ \hline
2011 & Selective forwarding [22] & WSN & Multi-hop & Energy efficiency & Markov Decision Process & available battery of the radio, the energy cost of retransmitting a message of the importance of messages & Suboptimal scheme and reduced computational cost of messages \\ \hline
2012 & Transmission policies [13] & WSN & Single-hop & Energy harvesting & Markov model & Current energy level of sensors, data importance & Transmission probability, energy level \\ \hline  & Routing protocol [18] & WHAN & Multi-hop & Energy efficiency, power control, transmission reliability, low overhead & CTP & Changing link quality, end to end delay, packet loss & Packet reception ratio, delay, energy consumption, energy balancing \\ \hline
2013 & Transmission policies [14] & WSN & Single-hop & Energy harvesting & Markov model & battery capacity, data transmission & Asymptotic average reward as a function of SNR, transmission probability \\ \hline  & Routing protocol [17] & WHAN & Multi-hop & Energy efficiency, power control, lifetime & - & Distance of the receiver & Remaining energy \\ \hline
2015 & Transmission policies [24] & WSN & Energy harvesting & Markov model & Energy level, data queue & Buffer size and battery, large data buffer case, low complexity policy \\ \hline  & Transmission policies [27] & WHAN & Single-hop & Energy efficiency & Circuit energy, transmission energy on distance & Energy consumption, recovery energy, transmission time, day cycle \\ \hline
2016 & Transmission policies [26] & WSN & Multi-hop & Energy efficiency & Network coding & No. of relay, encoding between fed size, source and relay transmission & Mean transmission, medium access probability \\ \hline
2017 & Transmission strategies [28] & WHAN & Energy efficiency & Discrete Markov arrival Process & Channel state, battery state, no. of buffered packet in the system & Transmission success rate, packet size, sensed data & percent, burden packets per rate, transmission reliability, energy efficiency, energy consumption speed, energy balance degree, lifetime \\ \hline  & Optimizing transmission [7] & WHAN & Multi-hop & Transmission power, energy efficiency, body movement & Energy level, event generation, packet transmission rate, link quality & Packet received by sink, consumed energy, packet delivery ratio, heating ratio \\ \hline  & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} & \multicolumn{1}{p{42.7 pt}}{} \\ \end{tabular}
\end{table} 
Table 1: Research work on developing transmission strategies published since 2009. In [27], authors reported a system level energy consumption model associated with transmission distance and transmission data rate over on body communication link. Then, they derived a threshold distance for energy saving in WBAN based on the analysis of tradeoff between circuit energy and transmission energy. According to the work in [27], for a distance less than or equal to threshold distance, circuit energy is comparable to the transmission energy consumption and as such total energy expenditure could be restricted by optimizing the transmission data rate.