Forthcoming and Online First Articles

International Journal of Embedded Systems

International Journal of Embedded Systems (IJES)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

International Journal of Embedded Systems (2 papers in press)

Regular Issues

  • Incentive-based resource management in pervasive mobile cloud computing   Order a copy of this article
    by Yuanhao Ma, Jigang Wen, Yuxiang Chen 
    Abstract: oud computing is a promising technique to conquer the resource limitations of a single mobile device. To relieve the work load of mobile users, computation-intensive tasks are proposed to be offloaded to the remote cloud or local Cloudlet. However, these solutions also face some challenges. It is difficult to support data intensive and delay-sensitive applications in the remote cloud, while the local Cloudlets often have limited coverage. When both of these methods cannot be supported, another option is to relieve the load of a single device by taking advantage of resources of surrounding smart-phones or other wireless devices. To facilitate the efficient operation of the third option, we propose a novel pervasive mobile cloud framework to provide an incentive mechanism to motivate mobile users to contribute their sources for others to borrow and an efficient mechanism to enable multi-site computation partition. More specifically, we formulate the problem as a Stackelberg game, and prove that there exists a unique Nash equilibrium for the game. Based on the unique Nash equilibrium, we propose an offloading protocol to derive the mobile users strategies. Through extensive simulations, we evaluate the performance and validate the theoretical properties of the proposed economy-based incentive mechanism.
    Keywords: cloud computing; resource management.
    DOI: 10.1504/IJES.2025.10070247
     
  • Intelligent workload optimisation based on a protocol-fused cloud robotics physical framework with integrated multi-sensors   Order a copy of this article
    by Songshuang Li, Shengyu Zhu, Kui Qian, Nannan Dong 
    Abstract: Cloud computing significantly improves the performance of robots in data processing and storage, but still faces problems such as high computational loads and high energy requirements for local robots. To address these issues, a protocol-fused physical framework integrating multiple sensors is proposed to simplify sensoring data integration and device deployment. Cloud robotics intelligent workload optimization has also been achieved through accurate sensoring data collection based on this framework. First, a middleware called ProtoFusion is introduced to manage the robot’s local services, facilitating protocol conversion and transmission of multimodal sensory information. Next, the cloud robot’s physical framework, based on ProtoFusion, enables sensing, perception, and control. Finally, ProtoFusion’s task division (e.g., receiving, sending, and controlling) is scheduled using uC/OS-III, optimizing system resource utilization. The effectiveness of the optimisation is verified experimentally. Resource efficiency was improved, energy consumption was reduced and system reliability was enhanced.
    Keywords: cloud computing; ProtoFusion; data driven; robotics physical framework; intelligent workload optimisation.
    DOI: 10.1504/IJES.2025.10070812
     

 

Return to top