Internet was once used to link ideas, then people and now it is starting to connect all things. IoT constitutes a good paradigm to enable people to design and modify things, and then share their designs and modifications. Through the internet, things nowadays are able to exchange raw data and information, thus enabling the development of a new class of interconnected smart objects. Smart building block toy systema are a newly proposed concept that combines internet technology into educational blocks. It is composed of the IoT environment that has attracted attention recently.In this paper, we design a system using starUML, one of the program development tools in the system design process. Educational content can be shared to learners via the proposed service of the IoT, while also being interesting for young child learners.
In order to achieve faster content distribution speed and stronger fault tolerance, a P2P peer can connect to multiple peers in parallel and receive chunks of the data simultaneously. A critical issue in this environment is selecting a set of nodes participating in swarming sessions. Previous related researches only focus on performance metrics, such as downloading time or the round-trip time, but in this paper, we consider a new performance metric which is closely related to the network and propose a peer selection algorithm that produces the set of peers generating optimal worst link stress. We prove that the optimal algorithm is practicable and has the advantages with the experiments on PlanetLab. The algorithm optimizes the congestion level of the bottleneck link. It means the algorithm can maximize the affordable throughput. Second, the network load is well balanced. A balanced network improves the utilization of resources and leads to the fast content distribution. We also notice that if every client follows our algorithm in selecting peers, the probability is high that all sessions could benefit. We expect that the algorithm in this paper can be used complementary to existing methods to derive new and valuable insights in peer-to-peer networking.
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