An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource request queue to satellites with idle processing resources. Finally, we simulate the efficient resource scheduling capability in the spatial information network and empirically compare our approaches against two representative swarm intelligence baseline approaches and show that our approach has significant advantages in terms of performance and time consumption during resource scheduling.

Resource System with Losses in a Random Environment

The article deals with queueing systems with random resource requirements modeled as bivariate Markov jump processes. One of the process components describes the service system with limited resources. Another component represents a random environment that submits multi-class requests for resources to the service system. If the resource request is lost, then the state of the service system does not change. The change in the state of the environment interacting with the service system depends on whether the resource request has been lost. Thus, unlike in known models, the service system provides feedback to the environment in response to resource requests. By analyzing the properties of the system of integral equations for the stationary distribution of the corresponding random process, we obtain the conditions for the stationary distribution to have a product form. These conditions are expressed in the form of three systems of nonlinear equations. Several special cases are explained in detail.

Device Identification Interoperability in Heterogeneous IoT Platforms

With the continuous improvement of Internet of Things (IoT) technologies, various IoT platforms are under development. However, each IoT platform is developed based on its own device identification system. That is, it is challenging to identify each sensor device between heterogeneous IoT platforms owing to the resource request format (e.g., device identifier) varying between platforms. Moreover, despite the considerable research focusing on resource interoperability between heterogeneous IoT platforms, little attention is given to sensor device identification systems in diverse IoT platforms. In order to overcome this problem, the current work proposes an IoT device name system (DNS) architecture based on the comparative analysis of heterogeneous IoT platforms (i.e., oneM2M, GS1 ‘Oliot’, IBM ‘Watson IoT’, OCF ‘IoTivity’, FIWARE). The proposed IoT DNS analyzes and translates the identification system of the device and resource request format. In this process, resource requests between heterogeneous IoT platforms can be reconfigured appropriately for the resources and services requested by the user, and as a result, users can use heterogeneous IoT services. Furthermore, in order to illustrate the aim of the proposed architecture, the proposed IoT DNS is implemented and tested on a microcomputer. The experimental results show that a oneM2M-based device successfully performs a resource request to a Watson IoT and FIWARE sensor devices.