MobSched: Customizable scheduler for mobile cloud computing

Abstract

In this paper, we explore how cloud computing techniques can be used on mobile devices. We analyze the reason why Hadoop's performance is poor in MANET, most notably, relying too much on distributed filesystem, and not aware of mobility and multi-hop nature of MANET. Two ways are proposed to deploy mobile cloud computing in an efficient manner: MobSched, a customizable job scheduler; and a mobile friendly MapReduce framework. These two methods enable developers to use MapReduce programming model in the context of MANET. Theoretical analysis suggests that the proposed framework can improve the performance of MapReduce jobs running on top of MANET, and reduce the energy consumption. Simulation results show that the proposed scheduler, MobSched, which is based on a linear programming formulation, can efficiently optimize multiple objectives such as power and (or) throughput, while being constrained with requirements such as minimum quality of service, and (or) maximum bandwidth usage that has to be met by the system. Comparison with other schedulers such as uniform load balancing, FIFO, and clustering types show that the proposed scheduler performs best when it comes to optimizing for a specific criteria such as total power consumption within reasonable latency.

Recent Developments in Mobile Cloud Scheduling: State-of-the-Art, Challenges and Perspectives

“…It provides at the same time maximum QoS and maximum bandwidth of the computational model. The general model is presented in the Formula 3 [5].…”

“…Dynamic Voltage and Frequency Scaling (DVFS) method implemented in IaaS cloud layer is also presented in this charter as a basic hardware methodology for Mobile Cloud energy consumption optimization. Section 4 presents the selected energy-efficient algorithms in MC systems, namely Scavenger [4], MobSched [5] and Scheduler of Mobile Cells [6].…”

An Efficient Scheduling Strategy in Mobile Cloud: Model and Algorithm

“…In [17], Sindia et al explore how cloud computing techniques can be used on mobile devices. Two ways are proposed to deploy mobile cloud computing in an efficient manner: a customizable job scheduler; and a mobile friendly MapReduce framework.…”