**Managing Energy Plus Performance in Data Centers and Battery-Based Devices Using an Online Non-Clairvoyant Speed-Bounded Multiprocessor Scheduling**

#### **Pawan Singh 1, Baseem Khan 2, Om Prakash Mahela 3, Hassan Haes Alhelou 4,5 and Ghassan Hayek 4,5,\***


Received: 5 March 2020; Accepted: 30 March 2020; Published: 3 April 2020

**Abstract:** An e fficient scheduling reduces the time required to process the jobs, and energy managemen<sup>t</sup> decreases the service cost as well as increases the lifetime of a battery. A balanced trade-o ff between the energy consumed and processing time gives an ideal objective for scheduling jobs in data centers and battery based devices. An online multiprocessor scheduling multiprocessor with bounded speed (MBS) is proposed in this paper. The objective of MBS is to minimize the importance-based flow time plus energy (IbFt+E), wherein the jobs arrive over time and the job's sizes are known only at completion time. Every processor can execute at a di fferent speed, to reduce the energy consumption. MBS is using the tradition power function and bounded speed model. The functioning of MBS is evaluated by utilizing potential function analysis against an o ffline adversary. For processors m ≥ 2, MBS is O(1)-competitive. The working of a set of jobs is simulated to compare MBS with the best known non-clairvoyant scheduling. The comparative analysis shows that the MBS outperforms other algorithms. The competitiveness of MBS is the least to date.

**Keywords:** multiprocessor system; online non-clairvoyant scheduling; weighted flow time; potential analysis; energy e fficiency
