Abstract

A nearby virtual machine (VM) based cloudlet is proposed for mobile cloud computing (MCC) to enhance the performance of real-time resource-intensive mobile applications. Generally, when a mobile device (MD) discovers a cloudlet in the vicinity, it takes time to set up a VM inside the cloudlet before data offloading from the MD to the VM starts. The time between the discovery of the cloudlet and actual offloading of data is considered as the service initiation time. When multiple cloudlets are present in a nearby geographical location, initiating a service with each cloudlet may be frustrating for cloudlet users that moving from one location to another. In order to eliminate the delay caused by the service initiation time after moving away from the source cloudlet, this paper proposes a seamless live VM migration between neighbouring cloudlets. A seamless live VM migration is achieved with the prior knowledge of the migrating VM IP address in the destination cloudlet and more importantly with multipath TCP (MPTCP). We have performed a number of experiments to validate the proposed approach using Linux KVM hypervisor. The experimental results demonstrate the feasibility of the proposed approach and also show performance improvement. Specifically, there is almost zero downtime at the destination cloudlet after the migration is completed.

Highlights

  • The high demand for mobile applications has encouraged software and mobile developers to bring the desktop level applications to mobile devices (MDs)

  • This paper proposes the use of multipath transport control protocol (TCP) (MPTCP) in both the client and the server to reduce the delay caused by TCP re-establishment

  • This paper presented an approach for live server virtual machine (VM) migration using MPTCP

Read more

Summary

Introduction

The high demand for mobile applications has encouraged software and mobile developers to bring the desktop level applications to mobile devices (MDs). Computational offloading and cloudlets Mobile Cloud Computing (MCC) brings together cloud computing, mobile computing, wireless networks, and cloud services to provide MD users rich computational resources. MCC overcomes the resource limitation of wireless MDs by leveraging fixed infrastructure Resources, such as CPU, RAM, data storage and battery energy, are limited resources in MDs. Resources, such as CPU, RAM, data storage and battery energy, are limited resources in MDs Resource intensive applications, such as speech recognition, natural language processing, computer vision and graphics, machine learning, augmented reality, planning, and decision-making become common in MDs. In order to enhance the performance of these resource-intensive applications, offloading from the MDs to resource-rich servers in the vicinity or to a distant server is a common solution for mobile computing

Objectives
Methods
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call