Mobile cloud computing can address power consumption problems of the mobile device by offloading application from the mobile device to Remote cloud. But Latency issues are raised due to the long physical distance between a mobile user and Remote cloud. The emerging cloud concept can solve latency issues in mobile cloud computing. Some existing works are focusing on cloudlets section in the multi-cloudlet environment. However, few works considering task allocation in the multi-cloudlet environment to improve user satisfaction. In this paper, we have proposed Response time aware task scheduling in the multi-cloudlet environment (RTTSMCE) to deal with two problems. First, a cloudlet server selection based on response time and second a task scheduling among cloudlets using load balancing algorithms to optimize response time of the cloud server. From the stimulation, the proposed algorithm shows a better performance compared to traditional load balancing algorithms. © 2019, © 2019 Informa UK Limited, trading as Taylor &amp; Francis Group.

Sasikala R

Department of Computational Intelligence

School of Computer Science and Engineering

Vellore Campus

Ramasubbareddy S

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

RTTSMCE: a response time aware task scheduling in multi-cloudlet environment

International Journal of Computers and Applications

Day to day the usage of mobile devices (MD) is growing in people's lives. But still the MD is limited in terms of memory, battery life time, processing capacity. In order to overcome these issues, the new emerging technology named mobile cloud computing (MCC) has been introduced. The offloading mechanism execute the resource intensive application on the remote cloud to save both the battery utilization and execution time. But still the high latency challenges in MCC need to be addressed by executing resource intensive task at nearby resource cloud server. The key challenge is to find optimal cloudlet to execute task to save computation time. In this article, the authors propose a Round Robin algorithm based on cloudlet selection in heterogeneous MCC system. This article considers both load and distance of server to find optimal cloudlet and minimize waiting time of the user request at server queue. Additionally, the authors provide mathematical evaluation of the algorithm and compare with existing load balancing algorithms.

International Journal of Grid and High Performance Computing

A Load and Distance Aware Cloudlet Selection Strategy in Multi-Cloudlet Environment

Proceedings of the 2nd International Conference on Data Engineering and Communication Technology Advances in Intelligent Systems and Computing

POUPR: Properly Utilizing User-Provided Recourses for Energy Saving in Mobile Cloud Computing

Nowadays, the uses of mobile devices have been increasing in many aspects of our life such as playing games, sending documents, transactions, and marketing, business, and conference meetings. But this mobile device has limited the resources in terms of battery lifetime, storage, and processing capacity. The new technology known as mobile cloud computing can help users to increase utilization of mobile cloud resources. The limitation of mobile device can be overcome by MCC. The technique called as offloading can transfer the resource-intensive task to remote cloud for processing, and the result will come back to the mobile device. The mobile device connecting to remote cloud with the help of 3G (or) LTE networks causes latency-related issues bandwidth and cost. In order to overcome these problems, MCC has introduced new technology which can reduce latency problems by providing secured and efficient model based on cloudlet. In this paper, we mainly focus on healthcare applications which can be processed by new cloudlet model for reducing processing time as well as providing enough security to user’s data. Initially, the user connects to the available cloudlet; if the cloudlet is not providing required resources or services, the user will redirect to remote cloud. In our model, the cloudlet is used to analyze patient medical records. © 2019, Springer Nature Singapore Pte Ltd.

Cloudlet Services for Healthcare Applications in Mobile Cloud Computing

The mobile cloud computing has been introduced to address limitations of mobile devices. These limitations include battery lifetime, storage capacity, and processing power. User can offload resource intensive mobile application into cloud for processing can return the result to device. This increases transmission delay and power consumption. The new cloudlet concept has been proposed to address problems such as long delay and huge power consumption. But selection of cloudlet in mobile cloud computing is an important issue for offloading task into cloudlet data center. In this paper, we proposed honey bee inspired cloudlet selection for resource allocation for resource intensive applications from users. The proposed algorithm not only selects low loaded cloudlet but also perform load balancing among cloudlets in such way that the waiting time of user offloading task in queue will be reduced. The experimental result shows that performance of the proposed algorithm optimal compare with existing algorithm. The proposed algorithm represents significant improvement in reduction of user’s waiting time in queue. © Springer Nature Singapore Pte Ltd. 2019.

Smart Intelligent Computing and Applications Smart Innovation, Systems and Technologies

A Honey Bee Inspired Cloudlet Selection for Resource Allocation

The mobile cloud computing (MCC) is an emerging technology, and its popularity is increasing drastically day by day. Mobile device has been constrained from low battery power, processing capabilities, and limited storage capacity, and MCC is facing several security issues. Users are expecting more computing power and security from mobile devices, in order to support user, the mobile computing integrate with cloud computing (CC) to form a MCC. Computation offloading improves computing features of smartphones (battery power, storage, processing capabilities) as well as user experience with device. In this paper, our main focus is to analyze energy consumption by executing on mobile device or remote cloud, and offloading method and level of partitioning are implemented by exploring different parameters based on frameworks. We summarize comparison between different energy offloading techniques. © Springer Nature Singapore Pte Ltd 2019.

Journal	International Journal of Computers and Applications
Publisher	Informa UK Limited
ISSN	1206-212X
Open Access	0