# Energy-Aware Online Non-Clairvoyant Scheduling Using Speed Scaling with Arbitrary Power Function
## 6 Conclusions and Future Work  
An online non-clairvoyant job scheduling algorithm Highest Scaled Importance First (HSIF) is proposed with an objective to minimize the sum of scaled importance based flow time and energy consumed. HSIF uses the arbitrary power function and dynamic speed scaling policy for uni-processor system. The working of HSIF is analysed using the amortized potential function analysis against an optimal offline adversary. The competitive ratio of HSIF is 2. The competitive ratio of HSIF is lesser than the non-clairvoyant scheduling algorithms LAPS, SelMig, NC, R\({}^{3}\), EtRR, ALG, and WLAPS; similar to an online clairvoyant scheduling Alg. Additionally, a set of jobs is considered as an illustrative example and the execution of the jobs on a processor is simulated by using HSIF and the best known algorithm NC. The simulation results show that the performance of the HSIF is consistent and better than the other online non-clairvoyant algorithm. On the basis of amortized potential function analysis and simulation results, it is concluded that the HSIF performs better than any other online non-clairvoyant algorithm. Use of HSIF in data centres and in battery based devices will reduce power consumption and improve computing capability. The further enhancement of our study will be to evaluate the working of HSIF in the multi-processor environment and the experiments will be conducted in the real time environment as well as with more number of test cases. Along with the amortized analysis and simulation the result will be analysed using statistical tests. The working of  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Job**} & \multicolumn{2}{c}{**Simple Values**} & \multicolumn{2}{c}{**Z Values**} & \multicolumn{2}{c}{**Sum**} & \multicolumn{1}{c}{**Normalized  
+++ ==WARNING: Truncated because of repetitions==
Sum**} \\ \cline{2-7}  & **NC\_ECij** & **NC\_IbFIj** & **ZNC\_ECij** & **ZNC\_IbFIj** & **(ZNC\_ECij + ZNC\_IbFIj)** & **(in range [0 1])** \\ \hline
**J11** & 14.8231 & 43.402869 & \(-\)0.89328 & \(-\)0.55206 & \(-\)1.44534 & 0.210932 \\
**J12** & 95.4029 & 97.672311 & \(-\)0.74003 & \(-\)0.54633 & \(-\)1.28636 & 0.242728 \\
**J13** & 161.0751 & 1932.70982 & \(-\)0.39072 & \(-\)0.35238 & \(-\)0.7431 & 0.35138 \\
**J14** & 276.5769 & 1565.904674 & 0.00618 & \(-\)0.39115 & \(-\)0.38497 & 0.423006 \\
**J15** & 341.9011 & 4084.84265 & 0.23065 & \(-\)0.12524 & 0.10541 & 0.521082 \\
**J16** & 444.0417 & 2652.137073 & 0.58288 & \(-\)0.27634 & 0.30564 & 0.561308 \\
**J17** & 607.6676 & 17099.83442 & 1.14391 & 1.25064 & 2.39455 & 0.978971 \\
**J18** & 431.6038 & 2838.699032 & 0.5389 & \(-\)0.25663 & 0.28227 & 0.556454 \\
**J19** & 376.2169 & 4628.367088 & 0.34857 & \(-\)0.06048 & 0.28109 & 0.556218 \\
**J20** & 58.0914 & 265.635671 & \(-\)0.7446 & \(-\)0.52858 & \(-\)1.27318 & 0.243546 \\
**J21** & 396.6757 & 8940.40525 & 0.41888 & 0.38827 & 0.80715 & 0.66143 \\
**J22** & 1136.468 & 3899.694292 & 2.96103 & 3.52297 & 6.484 & 1.7968 \\
**J23** & 1206.1447 & 3890.043814 & 3.2046 & 3.55515 & 6.75561 & 1.851122 \\
**J24** & 1213.1371 & 37422.77458 & 3.22448 & 3.39859 & 6.62307 & 1.824614 \\
**J25** & 264.6327 & 968.407357 & \(-\)0.03486 & 0.07416 & 0.0393 & 0.50786 \\
**J26** & 502.4527 & 1181.9171 & 0.868483 & 0.69281 & 1.55764 & 0.811528 \\  
++  
HSIF will be evaluated in the cloud/fog environment for resource allocation and energy optimization. One open problem is to reduce the competitive ratio that is achieved in this paper. In the further extension of this work, the number of jobs may be increased significantly to enhance the analysis of the algorithmic evaluation.  
All authors have worked on this manuscript together and all authors have read and approved the final manuscript. This research received no external funding.  
The authors declare no conflict of interest.