The user demand for device resource ability [45, 46] involved in a process is a sum of all ability demands for virtual device resource.
rs represents the user demand for the virtual device resource ability in the description: rs = dA(ds1).
There was an additional focus on user preferences for devices and resources.
Based on this model, we further derive a multimedia device resource matching technique for ubiquitous computing environments.
A similar framework has been provided by [83] for IoT devices resource management in micro data-centres.
The aforementioned results indicate that the Z-score is most appropriate for devices with resource constraints, followed by the box plot algorithm.
We have developed our proposal for devices with limited resources to allow them to surf the web and share the files and resources inside the spontaneous network.
It improves utilization of mobile resource but execution of MapReduce jobs on mobile phones results in high overhead for devices with limited resources.
We also specify a case study and we use it to evaluate our approach, showing that it is efficient and suitable for devices with scarce resources.
A slight portion of resources used for device discovery and discovery signal which can be broadcasted with a minimum delay is proposed in [9, 10].
Our study also indicates that this group of practitioners may benefit from accessing resources [ 72- 80] that provide guidance on useful drug information resources available for devices such as PDAs.
