Satellite communications (SATCOM) systems play important roles in wireless communication systems. In the future, they will be required to accommodate rapidly increasing communication requests from various types of users. Therefore, we propose a framework for efficient resource management in large-scale SATCOM systems that integrate multiple satellites. Such systems contain hundreds of thousands of communication satellites, user terminals, and gateway stations; thus, our proposed framework enables simpler and more reliable communication between users and satellites. To manage and control this system efficiently, we formulate an optimization problem that designs the network structure and allocates communication resources for a large-scale SATCOM system. In this mixed integer programming problem, we allow the cost function to be a combination of various factors so that SATCOM operators can design the network according to their individual management strategies. These factors include the total allocated bandwidth to users, the number of satellites and gateway stations to be used, and the number of total satellite handovers. Our numerical simulations show that the proposed management strategy outperforms a conventional strategy in which a user can connect to only one specific satellite determined in advance. Furthermore, we determine the effect of the number of satellites in the system on overall system performance.

This paper proposes a component ranking method to identify important components which have great impact on the system reliability. This method, which is opposite to an existing method, believes components which frequently invoke other components have more impact than others and employs component invocation structures and invocation frequencies for making important component ranking. It can strongly support for improving the reliability of software systems, especially large-scale systems. Extensive experiments are provided to validate this method and draw performance comparison.

In a large queuing system, the effect of the ratio of the filled data on the queue and waiting time from the head of a queue to the service gate are important factors for process efficiency because they are too large to ignore. However, many research works assumed that the factors can be considered to be negligible according to the queuing theory. Thus, the existing queuing models are not applicable to the design of large-scale systems. Such a system could be used as a product classification center for a home delivery service. In this paper, we propose a tree-queue model for large-scale systems that is more adaptive to efficient processes compared to existing models. We analyze and design a mean waiting time equation related to the ratio of the filled data in the queue. Based on simulations, the proposed model demonstrated improvement in process-efficiency, and it is more suitable to realistic system modeling than other compared models for large-scale systems.

We propose a distributed data management approach in this paper for a large-scale position-tracking system composed of multiple small systems based on wireless tag technologies such as RFID and Wi-Fi tags. Each of these small systems is called a domain, and a domain server manages the position data of the users belonging to its managing domain and also to the other domains but temporarily residing in its domain. The domain servers collaborate with each other to globally manage the position data, realizing the global position tracking. Several domains can be further grouped to form a larger domain, called a higher-domain, so that the whole system is constructed in a hierarchical structure. We implemented the proposed approach in an experimental environment, and conducted a performance evaluation on the proposed approach and compared it with an existing approach wherein a central server is used to manage the position data of all the users. The results showed that the position data processing load is distributed among the domain servers and the traffic for position data transmission over the backbone network can be significantly restrained.

Reliable Multicast has been applied to large-scale contents delivery systems for distributing digital contents to a large number of users without data loss. Reliable contents distribution is indispensable for software updates and management data sharing in actual delivery services. This paper evaluates the implementation and performance of RMTP; a reliable multicast protocol for bulk-data transfer, through the developments of contents delivery systems. Software configuration is also examined including operation functions such as delivery scheduling. Furthermore, applicability of reliable multicast to emerging broadband networks is also discussed based on the experimentation results. Through the deployment of the protocol and the software, performance estimation has played a key role for constructing the delivery systems as well as for designing the communication protocol.

In this paper, we present new stability conditions for a class of large-scale hybrid dynamical systems composed of a number of interconnected hybrid subsystems. The stability conditions are given in terms of discontinuous Lyapunov functions of the stable hybrid subsystems. Furthermore, the stability conditions are represented by LMIs (Linear Matrix Inequalities) which are computationally tractable.

In this paper, we present a dynamic output feedback controller design technique for robust decentralized stabilization of uncertain large-scale systems with time-delay in the subsystem interconnections. Based on Lyapunov second method, a sufficient condition for the stability, is derived in terms of three linear matrix inequalities (LMI). The solutions of the LMIs can be easily obtained using efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.