A Self-Cloning Agents Based Model for High-Performance Mobile-Cloud Computing

Date

2015-07-02

Author

Angın, Pelin
Jin, Zhongjun

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

235
views

0
downloads

The rise of the mobile-cloud computing paradigm in recent years has enabled mobile devices with processing power and battery life limitations to achieve complex tasks in real-time. While mobile-cloud computing is promising to overcome the limitations of mobile devices for real-time computing, the lack of frameworks compatible with standard technologies and techniques for dynamic performance estimation and program component relocation makes it harder to adopt mobile-cloud computing at large. Most of the available frameworks rely on strong assumptions such as the availability of a full clone of the application code and negligible execution time in the cloud. In this paper, we present a dynamic computation offloading model for mobile-cloud computing, based on autonomous agents. Our approach does not impose any requirements on the cloud platform other than providing isolated execution containers, and it alleviates the management burden of offloaded code by the mobile platform using stateful, autonomous application partitions. We also investigate the effects of different cloud runtime environment conditions on the performance of mobile-cloud computing, and present a simple and low-overhead dynamic makespan estimation model integrated into autonomous agents to enhance them with self-performance evaluation in addition to self-cloning capabilities. The proposed performance profiling model is used in conjunction with a cloud resource optimization scheme to ensure optimal performance. Experiments with two mobile applications demonstrate the effectiveness of the proposed approach for high-performance mobile-cloud computing.

Subject Keywords

Mobile-cloud computing, Autonomous agents, Context, Performance

URI

https://hdl.handle.net/11511/42134

DOI

https://doi.org/10.1109/cloud.2015.48

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Tamper-Resistant Autonomous Agents-Based Mobile-Cloud Computing Angın, Pelin; Ranchal, Rohit (2016-01-01) The rise of the mobile-cloud computing paradigm has enabled mobile devices with limited processing power and battery life to achieve complex tasks in real-time. While mobile-cloud computing is promising to overcome limitations of mobile devices for real-time computing needs, the reliance of existing models on strong assumptions such as the availability of a full clone of the application code and non-standard system environments in the cloud makes it harder to manage the performance of mobile-cloud computing...
An agent-based optimization framework for mobile-cloud computing Angın, Pelin (2013-01-01) The proliferation of cloud computing resources in the recent years offers a way for mobile devices with limited resources to achieve computationally intensive tasks in real-time. The mobile-cloud computing paradigm, which involves collaboration between mobile and cloud resources, is expected to become increasingly popular in mobile application development. Dynamic partitioning of applications between mobile and cloud platforms based on resource availability is crucial in achieving the best performance for a...
An adaptive mobile cloud computing framework using a call graph based model Kaya, Mahir; Koçyiğit, Altan; Eren, Pekin Erhan (2016-04-01) The use of mobile applications and their functionality are increasing day by day but mobile devices are still inferior to ordinary computers in terms of memory and processor capacity. Furthermore, the rapid depletion of the mobile devices' energy is still a major problem. Performance and energy shortcomings of mobile devices can be improved by using surrogate or cloud computing technologies. In particular, computation and memory intensive real time applications would be efficiently run by utilizing the reso...
A Distributed Monitoring and Reconfiguration Approach for Adaptive Network Computing Bhargava, Bharat; Angın, Pelin; Ranchal, Rohit; Lingayat, Sunil (2015-01-01) The past decade has witnessed immense developments in the field of network computing thanks to the rise of the cloud computing paradigm, which enables shared access to a wealth of computing and storage resources without needing to own them. While cloud computing facilitates on-demand deployment, mobility and collaboration of services, mechanisms for enforcing security and performance constraints when accessing cloud services are still at an immature state. The highly dynamic nature of networks and clouds ma...
A reconfigurable computing platform for real time embedded applications Say, Fatih; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2011) Today’s reconfigurable devices successfully combine ‘reconfigurable computing machine’ paradigm and ‘high degree of parallelism’ and hence reconfigurable computing emerged as a promising alternative for computing-intensive applications. Despite its superior performance and lower power consumption compared to general purpose computing using microprocessors, reconfigurable computing comes with a cost of design complexity. This thesis aims to reduce this complexity by providing a flexible and user friendly dev...

Citation Formats

P. Angın and Z. Jin, “A Self-Cloning Agents Based Model for High-Performance Mobile-Cloud Computing,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42134.