its QoS requirements. Contextual Model and their corresponding parameters Figure 31: has been adopted to design the objective function of each entity in Cost-benefit approach the end to end communications. For example, SNR allocated to user is in network cost perspective, while throughput achieved is corresponding The relation between benefit. is not linear. Cost investment after a does not translate into knee point (Q) proportional benefit. Figure 3.2 shows a scenario involving knee point. After Q, the cost investment at the input resources does not translate into proportional benefits at the output. Aim of the optimization is to find Q of all of the objective functions of each entity and use them to maximize/minimize the objective function. Figure 32: Cost-Benefit optimization model and Knee Point We have to exploit all those in the end to end communication scenario. In knee points this way, we aim to design the objective functions such that we obtain maximum benefit from the minimum cost investment. In other words, objective functions maximizes the term denoted in the equation below. It finds those from the feasible solutions complete solution set. (3.1) Maximizing a single objective function is simple, but scenarios where multiple objective functions are involved and input/output parameters are conflicting in the objective functions, then finding the optimum solution which satisfy all the objective functions is quite difficult. This eventually promises to deliver required QoS with minimum system resource investments. An overview of the end-to-end communication system has been depicted in Figure 3.3. The Figure the interaction of mobile network and cloud computing infrastructure in view of user and application context. Corresponding parameters of each module has been described. In section 3.1-5, we elaborate the behavior of each contextual model in view of the mentioned parameters. Then in section 3.6, we define the outer blue boundary depicted in Figure 3.3, i.e. In the end, in view of the simulation results, we multi-objective optimization. formulate and propose model in section 3.7. a comprehensive single user optimization Contextual Models in optimization domain Figure 33:
its QoS requirements. Figure 31: Contextual Model and their corresponding parameters Cost-benefit approach has been adopted to design the objective function of each entity in the end to end communications. For example, SNR allocated to user is cost in network perspective, while throughput achieved is corresponding benefit. The relation between is not linear. Cost investment after a knee point (Q) does not translate into proportional benefit. Figure 3.2 shows a scenario involving knee point. After Q, the cost investment at the input resources does not translate into proportional benefits at the output. Aim of the optimization is to find Q of all of the objective functions of each entity and use them to maximize/minimize the objective function. Figure 32: Cost-Benefit optimization model and Knee Point We have to exploit all those knee points in the end to end communication scenario. In this way, we aim to design the objective functions such that we obtain maximum benefit from the minimum cost investment. In other words, objective functions maximizes the term denoted in the equation below. It finds those feasible solutions from the complete solution set. (3.1) Maximizing a single objective function is simple, but scenarios where multiple objective functions are involved and input/output parameters are conflicting in the objective functions, then finding the optimum solution which satisfy all the objective functions is quite difficult. This eventually promises to deliver required QoS with minimum system resource investments. An overview of the end-to-end communication system has been depicted in Figure 3.3. The Figure the interaction of mobile network and cloud computing infrastructure in view of user and application context. Corresponding parameters of each module has been described. In section 3.1-5, we elaborate the behavior of each contextual model in view of the mentioned parameters. Then in section 3.6, we define the outer blue boundary depicted in Figure 3.3, i.e. multi-objective optimization. In the end, in view of the simulation results, we formulate and propose a comprehensive single user optimization model in section 3.7. Figure 33: Contextual Models in optimization domain
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