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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\u2019s remarkable component is the signal strength analyzer that determines the signal quality (e.g.-60\u2009dBm) 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\u2019s 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.<\/jats:p>","DOI":"10.1186\/s13677-020-0155-6","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T10:02:47Z","timestamp":1581069767000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Efficient resourceful mobile cloud architecture (mRARSA) for resource demanding applications"],"prefix":"10.1186","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3625-3961","authenticated-orcid":false,"given":"Asharul","family":"Islam","sequence":"first","affiliation":[]},{"given":"Anoop","family":"Kumar","sequence":"additional","affiliation":[]},{"given":"Khalid","family":"Mohiuddin","sequence":"additional","affiliation":[]},{"given":"Sadaf","family":"Yasmin","sequence":"additional","affiliation":[]},{"given":"Mohammed Abdul","family":"Khaleel","sequence":"additional","affiliation":[]},{"given":"Mohammad Rashid","family":"Hussain","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,2,7]]},"reference":[{"key":"155_CR1","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.jnca.2018.06.009","volume":"119","author":"F Gu","year":"2018","unstructured":"Gu F, Niu J, Qi Z, Atiquzzaman M (2018) Partitioning and offloading in smart mobile devices for mobile cloud computing: state of the art and future directions. 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