## 2 Background and Related Work
A complexity analysis of H.264/AVC entropy decoder is presented in [41] to facilitate the encoder to effectively trade off bit rate, distortion, and decoding-complexity during the encoding process. However, mechanisms to dynamically allocate and control the decoding-complexity levels across video frames and macroblock units have been overlooked in these state-of-the-art algorithms. The MPEG-DASH-based energy-aware HEVC streaming solutions [20] that exist in the literature only consider the decoding energy in PU mode decision and motion vector selection (i.e., integer-pel vs. fractional-pel). Hence, the reduction in energy consumption is marginal with respect to the similar approaches. In addition, the encoding techniques targeting energy-efficient HEVC decoding proposed in [42] consider the inverse transform and inverse quantization operations to reduce the decoding energy consumption. In this regard, our previous work in [24] takes a step ahead by introducing a decoding-complexity-rate-distortion model which is capable of determining the optimal combination of Langrangian multipliers that minimizes a cost function that constitutes all three parameters (i.e., rate, distortion, and decoding-complexity). The solution presented in [24] is capable of determining the coding modes for given content that minimize the decoding-complexity, and by extension the decoding energy, have minimal impact to the coding efficiency in a fixed QP encoding scenario. However, this solution lacks the capability to arbitrarily allocate rate and decoding-complexity levels to frames or CTUs, and control them in order to generate bit streams with multiple bit rate decoding-complexity levels, which is crucial for video streaming applications that target resource-constrained video decoding devices with high quality HD/UHD video contents. Furthermore, the network-aware and receiver-aware adaptation algorithms and the complexity-rate-distortion models [14; 15; 16] which have been introduced based on the previous coding standards typically focus on creating spatial, temporal, and quality scalable video bit streams. These approaches lack a comprehensive analysis of the decoding-complexity, rate, and distortion trade-offs with respect to the features available to the modern coding standards such as HEVC. Finally, it has been shown that the increasingly popular HTTP-based video streaming solutions are sufficiently flexible to incorporate decoding-energy in their content prefetch logic [20]. This is typically achieved by utilizing an algorithm that monitors the device's remaining energy level to determine the next most appropriate video segment to meet that energy level. However, as discussed above, the content creation algorithms used in these solutions consider bit rate, QP, and spatial resolution changes as means for generating bit streams at different energy levels [19; 21; 22; 23]. This is primarily due to the lack of a direct approach to generate rate-controlled bit streams at specified decoding-complexities--a crucial missing element in the state-of-the-art. Therefore, it is clear that a need exists for a mechanism to generate decoding-complexity and rate-controlled bit streams at the encoder to fully realize the energy efficiency goals of standards such as Green-MPEG [32; 33] that can also co-exist with current streaming solutions and decoder-side energy efficiency initiatives such as DVFS.