Figure 5 shows the total energy consumption of M-N policy sleeping mode, N policy sleeping mode and no sleeping mode with different average arriving rates.
Fig. 5 Total energy consumption versus average arriving rates of M-N policy sleeping mode, N policy sleeping mode, and no sleeping mode.
Figure 6 shows the relationship between average energy consumption in a packet and average delay in a packet of M−N policy sleeping mode, N policy sleeping mode and no sleeping mode with different average λ.
Fig. 6 Average energy consumption in a packet versus average delay in a packet in different arriving rates of M-N policy sleeping mode, N policy sleeping mode, and no sleeping mode.
In Fig. 6, it shows that the M-N policy sleeping mode and N policy sleeping mode both lead to the reduction of energy consumption but also introduce a longer time delay.
At the beginning of curves of with M-N policy sleeping mode and with N policy sleeping mode, their performance is similar, because when arriving rate is smaller, cluster controllers are often idle, in which case, M-N policy sleeping mode's advantage is not outstanding.
In any case of different arriving rates, we can see in Fig. 5 that the energy consumption of HybridFlow with M-N policy sleeping mode is smaller than N policy sleeping mode and without sleeping mode, which shows the validity of energy consumption management algorithm proposed in this paper.
Compared with N policy sleeping mode, our proposed mode can improve energy efficiency.
However, with improving energy efficiency, M-N policy sleeping mode introduces more time delay.
Local administrators can use the legal governance typology to prevent or break open any deadlocks in the planning and development of heat infrastructures, while national level policy-makers can use the typology in the design of new policies and modes of orchestration towards enhancing decision-making pertaining heat infrastructures.
