Efficient resourceful mobile cloud architecture (mRARSA) for resource demanding applications

• Published in: Journal of cloud computing : advances, systems and applications systems and applications, 2020-02, Vol.9 (1), p.1-21, Article 9
• Main Authors: Islam, Asharul, Kumar, Anoop, Mohiuddin, Khalid, Yasmin, Sadaf, Khaleel, Mohammed Abdul, Hussain, Mohammad Rashid
• Format: Article
• Language: English
• Subjects: Algorithms; Cloud computing; cloud service provisioning; Computer architecture; Computer Communication Networks; Computer Science; Computer System Implementation; Computer Systems Organization and Communication Networks; Electronic devices; Energy efficiency; executable code switching; Information Systems Applications (incl.Internet); Mobile cloud architecture; Multiple criterion; Performance evaluation; Power efficiency; Signal quality; Signal strength; signal strength analyzer; Software Engineering/Programming and Operating Systems; Special Purpose and Application-Based Systems; wireless communication channel; Wireless communications
• ISSN: 2192-113X; 2192-113X
• DOI: 10.1186/s13677-020-0155-6

For mobile clients, sufficient resources with the assurance of efficient performance and energy efficiency are the core concerns. This article mainly considers this need and proposes a resourceful architecture, called mRARSA that addresses the critical need in a mobile cloud environment. This architecture consists of cloud resources, mobile devices, and a set of functional components. The performance efficiency evaluates implementing the proposed context-aware multi-criteria decision offloading algorithm. This algorithm considers both device context (network parameters) and application content (task size) at run time when offloading an executable code to allocate the cloud resources. The appropriate resources select based on offloading decisions and via the wireless communication channels. The architecture’s remarkable component is the signal strength analyzer that determines the signal quality (e.g.-60 dBm) and contributes to performance efficiency. The proposed prototype model has implemented several times to monitor the performance efficiency, mobility, performance at communication barriers, and the outcomes of resource-demanding application’s execution. Results indicate performance improvement, such as the algorithm appropriately decides the cloud resources based on device network context, application content, mobility, and the signal strength quality and range. Moreover, the results also show significant improvement in achieving performance and energy efficiency. Sufficient resources and performance efficiency are the most significant features that distinguish this framework from the other existing frameworks.