This paper proposes deterministic epidemic modeling of future botnet malware named self-evolving botnets, assuming a contact process. The self-evolving botnets discover vulnerabilities of hosts by exploiting the computing resources of infected hosts, which could become serious threats to the future Internet society. The proposed epidemic model represents their infection dynamics on an overlay network consisting of hosts. It predicts the infection spreading of the self-evolving botnets with the use of mean field approximation using the degree distribution of the overlay network. Through numerical calculations, we show that the proposed epidemic model well approximates the infection spreading in short time.

In networked control systems, the quality of performance (QoP), such as in terms of consistent tracking errors, must be maintained at a constant level. A QoP-aware sleep mechanism in network interfaces can reduce the amount of traffic or the communication rate while maintaining the QoP. However, in a QoP-aware sleep mechanism with a fixed sleep period, the sleep period cannot be entered effectively when the length of the steady-state period is changed; e.g., when the command frequency is changed. This study proposes a variable sleep period control method to reduce the communication rate while adapting to the tracking error. The simulations confirm that, when compared to methods with a fixed sleep period, the proposed method reduces the communication rate regardless of the command frequency.

An aggregating switch (SW) network offers cost-effective accommodation to IoT (Internet of Things) traffic by aggregating the traffic. For more efficient accommodation, the microburst traffic must be mitigated, which occurs when massive IoT devices transmit data simultaneously. In this paper, we propose cooperated traffic shaping by SWs with estimation of the input rate from the IoT devices to increase the accommodated data size of microburst traffic and derive equations for optimal configurations. Experimental results show that the data size can be increased by 60%.

In order to deploy a lot of 5G base stations, there is a method of installing them on utility poles and building walls. In this paper, antennas installed on them for 5G base stations are investigated numerically and experimentally. We examine the minimum ground plane size to remove the influence of concrete and embedded reinforced bars. We also verify the effects on the input characteristics and radiation pattern by measurement.

This paper addresses the scalability in the cost of smart contracts, which prevent illegal resource access (control access) in the Internet of Things. In previous studies, smart contracts have been used to avoid having a single point of failure, while maintaining tamper resistance. However, a high cost (called gas) is necessary when the number of subject-object pairs becomes large. In order to reduce cost, this paper proposes an access control method using smart contracts with a hierarchical name space. The proposed method scales well in terms of cost-decisive factors, namely, the complexity of functions and the number of smart contracts, leading to scalability in cost.

This letter proposes adaptive null-space expansion (NSE) for multiuser massive MIMO according to users’ mobility. NSE can improve the robustness of multi-user spatial multiplexing in a time-varying channel by expanding null-steering to multiple past channels. Its superiority was verified under the unified moving speed among users. In a realistic environment, users with different speeds coexist. Null-space dimension, which is the number of nullified channels per user terminal, should be optimized in accordance with users’ mobility so as to maximize the beamforming gain and nullification capability. In our proposal, we first show that user mobility can be classified by observing the singular value of time-varying channels. Computer simulation then clarifies that output SINR can be improved by assigning null space dimensions respective to user moving speeds.

Network bandwidth reservation is an expected service under software-defined network environment, where users directly reserve network resources in an on-demand manner. To provide extensive bandwidth reservation services, instantaneous response to user requests, and high user request acceptance ratio are required. In this study, we propose a novel bandwidth reservation method to meet these two requirements by combining machine learning (ML) and linear programming (LP), for unpredictable bandwidth demands in which the use time is indicated strictly. In the proposed method, a user request is instantaneously judged through ML, and network resource allocation, including traffic routing, is optimally determined through LP. We demonstrate that the proposed method provides a suboptimal acceptance ratio with a difference of less than 1% compared to the optimal solution, and an instantaneous response of less than 0.1ms under a general computation environment.

This letter evaluates inter-system interference reduction effect by the adaptive bandwidth control method for a spectrum sharing multi-band system according to the bands used by an interfered system, the inter-system power ratio of spectrum sharing systems, and interference power from unknown external systems. The method adaptively selects bandwidth control bands among allocated multiple bands to effectively reduce out-of-band distortion noise which interferes to other spectrum sharing systems. The evaluation results clarify appropriate band selection for interfered system band position, and show the effective range of the method to inter-system power ratios and unknown external system interference.

We are investigating the fingerprint method using wireless LAN access points (APs) to estimate user location. We focused on database update as a way to prevent the loss of localization accuracy. Updating a database using user-measured data presents the issue of update errors. In this paper, we have proposed and verified this issues.

In this letter, we propose a new incumbent protection method that considers three-dimensional (3D) aspects of 5G beamforming characteristics in dynamic spectrum access (DSA). We show some computer simulation results in which fixed wireless access (FWA)-based primary system (PS) and 5G-based secondary system (SS) were assumed to be deployed in a 26 GHz band. The results show that the proposed method can increase allowable transmission power of the SS by considering the 3D beamforming aspects, and that PS and SS height deployment information can additionally bring benefits to the proposed method in terms of the allowable transmission power in DSA.

This paper presents a linearly dual-polarized dual-band and wideband multi-ring microstrip antenna fed by two L-probes. The proposed antenna consists of two circular ring patches and two L-probes arranged in a multi-layered dielectric substrate. By using a thick substrate for the L-probe and arranging two ring patches as radiation elements, the proposed antenna exhibits wideband and dual-band characteristics. Furthermore, by arranging two L-probes at the orthogonal positions, the proposed antenna can operate as a linearly dual-polarized planar antenna. The measured fractional bandwidths corresponding to a reflection coefficient below -10dB were 21.7% and 10.6% for the first and second modes, respectively. The measured isolation between two ports of the test antenna in the above bandwidths were larger than 13dB.