The problem caused by fake news continues to worsen in today's online social networks. Intuitively, it seems effective to issue corrections as a countermeasure. However, corrections can, ironically, strengthen attention to fake news, which worsens the situation. This paper proposes a model for describing the interaction between fake news and the corrections as a reaction-diffusion system; this yields the mechanism by which corrections increase attention to fake news. In this model, the emergence of groups of users who believe in fake news is understood as a Turing pattern that appears in the activator-inhibitor model. Numerical calculations show that even if the network structure has no spatial bias, the interaction between fake news and the corrections creates groups that are strongly interested in discussing fake news. Also, we propose and evaluate a basic strategy to counter fake news.

Active measurement is an end-to-end measurement technique that can estimate network performance. The active measurement techniques of PASTA-based probing and periodic-probing are widely used. However, for the active measurement of delay and loss, Baccelli et al. reported that there are many other probing policies that can achieve appropriate estimation if we can assume the non-intrusive context (the load of the probe packets is ignored in the non-intrusive context). While the best policy in terms of accuracy is periodic-probing with fixed interval, it suffers from the phase-lock phenomenon created by synchronization with network congestion. The important point in avoiding the phase-lock phenomenon is to shift the cycle of the probe packet injection by adding fluctuations. In this paper, we analyse the optimal magnitude of fluctuations corresponding to the given autocovariance function of the target process. Moreover, we introduce some evaluation examples to provide guidance on designing experiments to network researchers and practitioners. The examples yield insights on the relationships among measurement parameters, network parameters, and the optimal fluctuation magnitude.

In recent years, with the rapid development of the Internet and cloud computing, an enormous amount of information is exchanged on various social networking services. In order to handle and maintain such a mountain of information properly by limited resources in the network, it is very important to comprehend the dynamics for propagation of information or activity on the social network. One of many indices used by social network analysis which investigates the network structure is “node centrality”. A common characteristic of conventional node centralities is that it depends on the topological structure of network and the value of node centrality does not change unless the topology changes. The network dynamics is generated by interaction between users whose strength is asymmetric in general. Network structure reflecting the asymmetric interaction between users is modeled by a directed graph, and it is described by an asymmetric matrix in matrix-based network model. In this paper, we showed an oscillation model for describing dynamics on networks generated from a certain kind of asymmetric interaction between nodes by using a symmetric matrix. Moreover, we propose a new extended index of well-known two node centralities based on the oscillation model. In addition, we show that the proposed index can describe various aspect of node centrality that considers not only the topological structure of the network, but also asymmetry of links, the distribution of source node of activity, and temporal evolution of activity propagation by properly assigning the weight of each link. The proposed model is regarded as the fundamental framework for different node centralities.

Mobile ad hoc networks (MANETs) consist of mobile terminals that directly connect with one another to communicate without a network infrastructure, such as base stations and/or access points of wireless local area networks (LANs) connected to wired backbone networks. Large-scale disasters such as tsunamis and earthquakes can cause serious damage to life, property as well as any network infrastructure. However, MANETs can function even after severe disasters have destroyed regular network infrastructure. We have proposed an autonomous decentralized structure formation technology based on local interaction, and have applied it to implement autonomous decentralized clustering on MANETs. This method is known to configure clusters that reflect the network condition, such as residual battery power and the degree of each node. However, the effect of clusters that reflect the network condition has not been evaluated. In this study, we configure clusters using our method, the back-diffusion method, and a bio-inspired method, which is a kind of autonomous decentralized clustering that cannot reflect the network condition. We also clarify the importance of clustering that reflects the network condition, with regard to power consumption and data transfer efficiency.

In ATM networks Connection Admission Control (CAC) is a key part of traffic control but several challenging problems still remain. One is how to assign sufficient bandwidth fast enough to achieve real-time CAC. Although solutions to the bandwidth assignment problem have been proposed, they require a lot of calculations depending on the number of VCs and on the number of different VC types. Therefore, it is difficult to apply these solutions to real-time CAC decisions, This paper presents a cell-loss ratio evaluation algorithm that takes the peak and the average cell rates as inputs, and providers the upper-bound of the cell-loss ratio. The most remarkable characteristic of this algorithm is that it does not require exhaustive calculation and its calculation load is independent of the number of VCs and the number of different VC types. Using this approximation, we propose a real-time CAC. The experimental results show that call processing of the proposed CAC using a processor, whose pertormance is almost the same as that of a processor in a conventional PBX, terminates within several milliseconds.

Recently, ABR has been attracting attention as a new service category of ATM, and the methodology to realize ABR is being actively discussed in the ATM Forum. ABR is expected to become a suitable class for supporting LAN services on ATM networks. To this end, a technical foundation must be established in which bandwidth is effectively utilized and quality is guaranteed. In order for ABR to use a portion of the bandwidth that is not used by high-priority classes (CBR, VBR), it is necessary to appropriately estimate the unused portion of the bandwidth. Due to the fact that the unused portion of the bandwidth in ATM networks fluctuates, such fluctuations must be taken into account. This paper describes ABR connection admission control and design of the congestion detecting point in an ABR buffer using Allan variance of the unused portion of the bandwidth.

This paper focuses on flow control in high-speed networks. Each node in a network handles its local traffic flow on the basis of only the information it is aware of, but it is preferable that the decision-making of each node leads to high performance of the whole network. To this end, we investigate the relationship between the flow control mechanism of each node and network performance. We consider the situation in which the capacity of a link in the network is changed but individual nodes are not aware of this. Then we investigate the stability and adaptability of the network performance, and discuss an appropriate flow control model on the basis of simulation results.

Connection Admission Control (CAC) is a key part of traffic control and still leaves several challenging problems peculiar to ATM networks. One of these problems is how to assign sufficient bandwidth for any cell arrival process that satisfies the source traffic descriptor values specified by negotiation between the network and a user at the connection setup. Because the source traffic descriptor cannot describe the actual source traffic characteristics completely, it has already been studied extensively that how to estimate sufficient bandwidth under the assumption that the actual traffic parameter values in the source traffic descriptor are equal to the negotiated values. This paper extends the studies in the literature to how to estimate sufficient bandwidth only assuming that the actual values satisfy the negotiated values, that is the actual values is less than or equal to the negotiated values. We show the sufficient condition for negotiated source traffic descriptors ensuring that the cell-loss ratio calculated from the negotiated values is always the upper-bound of the actual cell-loss ratio. Using this condition, we propose a CAC that can guarantee cell-loss ratio objective so far as a user satisfies the source traffic descriptor values.

This paper describes a realtime cell-loss ratio evaluation algorithm for ATM connection admission control. This algorithm gives an efficient evaluation of cell-loss ratio from traffic descriptors such as peak cell rate, sustainable cell rate, and maximum burst size for each VC. The most remarkable characteristics of this algorithm are that it terminates within a millisecond and that its time is independent of both the number of VCs and the capacity of a cell buffer.

The phenomenon known as social polarization, in which a social group splits into two or more groups, can cause division of the society by causing the radicalization of opinions and the spread of misinformation, is particularly significant in online communities. To develop technologies to mitigate the effects of polarization in online social networks, it is necessary to understand the mechanism driving its occurrence. There are some models of social polarization in which network structure and users' opinions change, based on the quantified opinions held by the users of online social networks. However, they are based on the interaction between users connected by online social networks. Current recommendation systems offer information from unknown users who are deemed to have similar interests. We can interpret this situation as being yielded non-local effects brought on by the network system, it is not based on local interactions between users. In this paper, based on the spectral graph theory, which can describe non-local effects in online social networks mathematically, we propose a model of polarization that user behavior and network structure change while influencing each other including non-local effects. We investigate the characteristics of the proposed model. Simultaneously, we propose an index to evaluate the degree of network polarization quantitatively, which is needed for our investigations.