Abstract-We consider the problem of transmitting multicast flows with hard deadlines over unreliable wireless channels. Every user in the network subscribes to several multicast flows, and requires a minimum throughput for each subscribed flow to meet the QoS constraints. The network controller schedules the transmissions of multicast traffic based on the instant feedback from the users. We characterize the multicast throughput region by analyzing its boundary points, each of which is the solution to a finite-horizon dynamic programming problem over an exponentially large state space. Using backward induction and interchange arguments, we show that the dynamic programming problems are solved by greedy policies that maximize the immediate weighted sum throughput in every slot. Furthermore, we develop a dynamic throughput-optimal policy that achieves any feasible throughput vector by tracking the running performance perceived by the users.
Abstract-In this paper we consider a wireless network composed of a base station and a number of clients, with the goal of scheduling real-time traffic. Even though this problem has been extensively studied in the literature, the impact of delayed acknowledgment has not been assessed. Delayed feedback is of increasing importance in systems where the round trip delay is much greater than the packet transmission time, and it has a significant effect on the scheduling decisions and network performance.Previous work considered the problem of scheduling realtime traffic with instantaneous feedback and without feedback. In this work, we address the general case of delayed feedback and use Dynamic Programming to characterize the optimal scheduling policy. An optimal algorithm that fulfills any feasible minimum delivery ratio requirements is proposed. Moreover, we develop a low-complexity suboptimal heuristic algorithm which is suitable for platforms with low computational power. Both algorithms are evaluated through simulations.
-Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.
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