In the past one week I focus on energy-efficient network processor design. Particularly, I focus on the precise DVS for low power network processor. The existing online DVS for network processor simply changes Vdd to a predefined level every time the scaling is enforced, for example, reduce Vdd by 0.05V everytime we need to lower Vdd. However, with our performance model and SA method we can know exactly what is the optimal Vdd we need to set to each PE. Therefore such precise DVS must perform better than existing heuristic DVS. This one is the nature extension of our previous work. The todo list include: 1. based on call level statistics, generate the incoming packet rate for one second. This has been done individually. 2. based on the packet rate, decide the power-optimal Vdd assignment and frequency assignment. This has also been done individually. 3. run simulation with this frequency assignment to verify the QoS. 4. cumulate the power in this second, and repeat the procedure from 1 to 3. We can compare the power results to the heuristic DVS and DVS without bus impact. The problem of our approach is that it is too time-consuming to obtained an optimal Vdd setting by SA, if such method is to be used for online DVS. Offline DVS is another story. I am reading a few papers to gain acknoledge on offline DVS. My opinion is that we can first target at offline DVS, assuming the application can be profiled ahead of the running time and all optimal Vdd setting are stored in a table. Another topic we may explore is the dynamic scheduling for energy minimization with simultenous QoS and thermal guarantee. Here the thermal guarantee means the maximum on-chip temperature constraint. The basic idea is that, according to the iso-QoS and iso-temperature curves, for given QoS and thermal constraint, any combination of (Vdd, PE number) corresponding to a point in one out of 4 regions partitioned by the iso-QoS and iso-temperature curves: Region I: the (Vdd, PE number) combination leads to high temperature and excessive performance. In this region the scheduling is to reduce Vdd (assuming all PE has the same Vdd), but not turn off existing PE. Region II: high temperature but not enough performance, in this region the scheduling is to increase PE number Region. III: low temperature but not enough performance, in this region the scheduling is to increase Vdd but do not turn on new PE. Region IV: low temperature but excessive performance, in this region the scheduling is to reduce PE number. The results can be compared to dynamic scheduling with only either QoS or thermal constraint. By combining the two topics, we can send out a journal submission.