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With the development of mobile Internet technology and the popularity of intelligent mobile terminals, the data traffic load of mobile client users on the smart campus network platform has surged. How to reduce the data traffic of the smart campus network platform is an urgent problem to be solved. First, this paper discussed the key technologies of smart campus network teaching platform under the background of the 5G network, expounded the critical technologies of the transport layer of the Internet of Things (IoT) technology, and analyzed from the development perspective of the IoT platform. Second, by investigating the online classroom data of five types of colleges and universities in China and comparing the advantages and disadvantages of online classroom teaching and traditional classroom teaching, it is found that the number of online courses in colleges and universities has exploded in the second half of 2017. Next, this paper analyzed the demand of smart campus online teaching platform under the background of the 5G network, thus established an online teaching platform based on the four initiatives operation model (government-led, college sponsor, teacher subject, and academic director). Finally, this paper adopted the improved VIRE localization algorithm to obtain the specific location information of the student users in the classroom and, then, compared with the error obtained by the VIRE algorithm, and the error of the improved VIRE algorithm is smaller. In the process of obtaining information, the 5G network technology is used for data transmission, which can shorten the check-in time and can improve the positioning accuracy. INDEX TERMS 5G network, smart campus, online teaching platform, improved VIRE location algorithm.

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Traffic and channel-data rate combined with the stream oriented methodology can provide a scheme for offering optimized and guaranteed QoS. In this work a stream oriented modeled scheme is proposed based on each node's selfscheduling energy management. This scheme is taking into account the overall packet loss in order to form the optimal effective -for the end-to-end connection-throughput response. The scheme also -quantitatively-takes into account the asymmetrical nature of wireless links and the caching activity that is used for data revocation in the ad-hoc based connectivity scenario. Through the designed middleware and the architectural layering and through experimental simulation, the proposed energy-aware management scheme is thoroughly evaluated in order to meet the parameters' values where the optimal throughput response for each device/user is achieved.

SUMMARYAdaptive behaviour of swarm-based agents (BT Technol. J. 1994; 12:104-113; AAMAS Conference '02, Melbourne, Australia, Month 1-2, 2002; Softcomput. J. 2001; 5(4):313-317.) is being studied in this paper with respect to network throughput for a certain amount of data traffic. Algorithmically complex problems like routing data packets in a network need to be faced with a dynamically adaptive approach such as agent-based scheme. Particularly in interconnected networks where multiple networks are participating in order to figure a large-scale network with different QoS levels and heterogeneity in the service of delay sensitive packets, routing algorithm must adopt in frequent network changes to anticipate such situations. 20-24, 2003; 240-247.) where agents are split after their departure to the next node on a hop-by-hop basis. Packets that are delay sensitive are marked as prioritized which agents recognize-as being a part of a packet-and try to influence the two-way routing tables. Thorough examination is made, for the performance of the proposed algorithm in the network and the QoS offered, taking into account a number of metrics. It is shown that the split agent routing scheme applied to interconnected networks offers a decentralized control in the network and an efficient way to increase overall performance and packet control reducing at the same time the packet loss concept.

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Data dissemination in opportunistic networks poses a series of challenges, since there is no central entity aware of all the nodes' subscriptions. Each individual node is only aware of its own interests and those of a node that it is contact with, if any. Thus, dissemination is generally performed using epidemic algorithms that flood the network, but they have the disadvantage that the network overhead and congestion are very high. In this paper, we propose ONSIDE, an algorithm that leverages a node's online social connections (i.e. friends on social networks such as Facebook or Google+), its interests and the history of contacts, in order to decrease congestion and required bandwidth, while not affecting the overall network's hit rate and the delivery latency. We present the results of testing our algorithm using an opportunistic network emulator and three mobility traces taken in different environments.

SUMMARYUsing the idea of probabilistic routing, calls in an ant based decentralized scheme are not routed according to the largest probabilities in the pheromone tables but randomly according to these probabilities. This principle can be particularly helpful in order to further minimize possible node congestion problems. An additional incorporation of the antipheromone mechanism in the operation of artificial ants helps in better biasing the network. This paper examines the behaviour of such a routing scheme using a proper set of suitable metrics.