As the capabilities and costs of Artificial Intelligence (AI) and of sensors (IoT) continue to improve, the concept of a “control system” can evolve beyond the operation of a discrete technical system based on numerical information and enter the realm of large-scale systems with both technical and social characteristics based on both numerical and unstructured information. This evolution has particular significance for applying the principles of Autonomous Decentralised Systems (ADS) [1]. This article considers the possible roles for ADS in complex technical and social systems extending up to global scales.

With the evolution of autonomous distributed systems such as smart cities, autonomous vehicles, smart control and scheduling systems there is an increased need for approaches to manage the execution of services to deliver real-time performance. As Cloud-hosted services are increasingly used to provide intelligence and analytic functionality to Internet of Things (IoT) systems, Quality of Service (QoS) techniques must be used to guarantee the timely service delivery. This paper reviews state-of-the-art QoS and Cloud techniques for real-time service delivery and data analysis. A review of straggler mitigation and a classification of real-time QoS techniques is provided. Then a mathematical framework is presented capturing the relationship between the host execution environment and the executing service allowing the response-times to predicted throughout execution. The framework is shown experimentally to reduce the number of QoS violations by 21% and provides alerts during the first 14ms provide alerts for 94% of future violations.

Along with the sophistication of society, the requirements for infrastructure systems are also becoming more sophisticated. Conventionally, infrastructure systems have been accepted if they were safe and stable, but nowadays they are required for serviceability as a matter of course. For this reason, not only the expansion of the scope of the control system but also the integration with the information service system has been frequently carried out. In this paper, we describe safety technology based on autonomous decentralized technology as one of the measures to secure safety in a control system integrating such information service functions. And we propose its future studies.

Both placing responsibility of message sending on every IoT object and obfuscating the object's location from other objects are essential to realize a secure and privacy-preserved communication service. Two or more short-lived link identifiers (or pseudonyms) authorized by a trustable authority are often used in related studies, instead of a persistent or long-term use link identifier (i.e. vendor assigned MAC address). However, related studies have limitations in terms of frequently changing pseudonyms to enhance location privacy because the cryptographic algorithms used in them fixedly couple object's identifiers with its security keys. To overcome those limitations, we present a new pseudonym and key management scheme that enables dynamic coupling of pseudonym and key pairs without incurring any adverse impacts. Furthermore, we propose two lightweight pseudonym allocation protocols to effectively reduce the volume of message carrying the allocation parameters. Through qualitative analyses, we verify that the proposed scheme is more scalable than related approaches as it can efficiently allocate enough number of pseudonym/key pairs by reducing the control message overhead by more than 90%.

To enable the vision of precision medicine, evidence-based medicine is the key element. Understanding the natural history of complex diseases like brain aneurysm and particularly investigating the evidences of its rupture risk factors relies on the existence of semantic-enabled data preparation technology to conduct clinical trials, survival analysis and outcome prediction. For personalized medicine in the field of neurological diseases, it is very important that multiple health organizations coordinate and cooperate to conduct evidence based observational studies. Without the means of automating the process of privacy and semantic-enabled data preparation to conduct observational studies at intra-organizational level would require months to manually prepare the data. Therefore, this paper proposes a semantic and privacy enabled, multi-party data preparation architecture and a four-tiered semantic similarity algorithm. Evaluation shows that proposed algorithm achieves a precision of 79%, high recall at 83% and F-measure of 81%.

This work is conducted to solve the current problem in the attribute-based keyword search (ABKS) scheme about how to securely and efficiently delegate the search rights to other users when the authorized user is not online. We first combine proxy re-encryption (PRE) with the ABKS technology and propose a scheme called attribute-based keyword search with proxy re-encryption (PABKS). The scheme not only realizes the functions of data search and fine-grained access control, but also supports search function sharing. In addition, we randomly blind the user's private key to the server, which ensures the confidentiality and security of the private key. Then, we also prove that the scheme is selective access structure and chosen keyword attack (IND-sAS-CKA) secured in the random oracle model. A performance analysis and security proof show that the proposed scheme can achieve efficient and secure data search in the cloud.

In this paper we extend hyperparameter-free sparse signal reconstruction approaches to permit the high-resolution time delay estimation of spread spectrum signals and demonstrate their feasibility in terms of both performance and computation complexity by applying them to the ISO/IEC 24730-2.1 real-time locating system (RTLS). Numerical examples show that the sparse asymptotic minimum variance (SAMV) approach outperforms other sparse algorithms and multiple signal classification (MUSIC) regardless of the signal correlation, especially in the case where the incoming signals are closely spaced within a Rayleigh resolution limit. The performance difference among the hyperparameter-free approaches decreases significantly as the signals become more widely separated. SAMV is sometimes strongly influenced by the noise correlation, but the degrading effect of the correlated noise can be mitigated through the noise-whitening process. The computation complexity of SAMV can be feasible for practical system use by setting the power update threshold and the grid size properly, and/or via parallel implementations.

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.

During a disaster, users will not be able to communicate with their families and friends using mobile terminals, e.g., smartphones, in many cases due to failures of base stations and backhaul of cellular networks. Even when cellular networks normally operate without failure, they will become seriously congested due to dramatically increased traffic demand. To solve these problems, device-to-device (D2D) communications, in which mobile terminals directly communicate without cellular networks, have been investigated. Multi-hop D2D communication using multiple mobile terminals as relay nodes will be effective in maintaining connectivity during a disaster. It is preferable to estimate the success probability of multi-hop D2D communication by using a simple method that offers optimal parameter control, e.g., the ratio of mobile terminals using D2D communications and the maximum hop length. Moreover, when evaluating the reachability of multi-hop D2D communication, we need to consider the evacuation behavior during a disaster because success probability depends on the geographical distribution of mobile terminals. Therefore, in this paper, we derive a formula for estimating the success probability of multi-hop D2D communication in a simple manner and analyze its reachability using a multi-agent simulation that reproduces the evacuation behavior expected during an earthquake in Tokyo Shinjuku Ward.

This paper investigates approaches that can cancel nonlinear phase noise effectively for the phase-conjugate pair diversity transmission of 16-QAM WDM signals through multi-core fiber. The geometric mean is introduced for the combination of the phase-conjugate pair. A numerical simulation suggests that span-by-span chromatic dispersion compensation is more effective at cancelling phase noise in long distance transmission than lumped compensation at the receiver. Simulations suggest the span-wise compensation described herein yields Q-value enhancement of 7.8 and 6.8dB for CD values of 10 and 20.6ps/nm/km, respectively, whereas the lumped compensation equivalent attains only 3.5dB. A 1050km recirculating loop experiment confirmed a Q-value enhancement of 4.1dB for 20.6ps/nm/km, span-wise compensation transmission.

This paper argues that a layered approach is more suitable for Information Centric Networking (ICN) than a narrow-waist approach and proposes an ICN mechanism called ZINK. In ZINK, a location-independent content name is resolved to a list of node IDs of content servers in the application layer and a node ID is mapped to a node locator in the network layer, which results in scalable locator-based routing. An ID/Locator split approach in the network layer can efficiently support client/serever mobility. Efficient content transfer is achieved by using sophisticated functions in the transport layer such as multipath transfer for bandwidth aggregation or fault tolerance. Existing well-tuned congestion control in the transport layer achieves fairness not only among ICN flows but also among ICN flows and other flows. A proof-of concept prototype of ZINK is implemented on an IPv6 stack. Evaluation results show that the time for content finding is practical, efficient content transfer is possible by using multipath transfer, and the mobility support mechanism is scalable as shown in a nationwide experiment environment in Japan.

In this paper, we present an Energy-efficient Mobile Group Clustering (EMGC) protocol that supports group mobility and a group handover scheme. The mobile sensor nodes are divided into three categories, namely cluster heads, group leaders and group members. In our cluster formation and group handover scheme, group leaders and cluster heads do most of the communications to save on energy consumption during which group members are placed in the sleep condition. This scheme will reduce the number of control packets and frequent topology changes in the networks. Simulation results show that the EMGC protocol outperforms MN-LEACH, GMAC, MBC protocols in terms of energy dissipation and the number of data items received at a base station.

Using local time frames to treat non-stationary real world signals as stationary yields Quasi-Stationary Signals (QSS). In this paper, direction of arrival (DOA) estimation of uncorrelated non-circular QSS is analyzed by applying a novel technique to achieve larger consecutive lags using coprime array. A scheme of virtual extension of coprime array is proposed that exploits the difference and sum co-array which can increase consecutive co-array lags in remarkable number by using less number of sensors. In the proposed method, cross lags as well as self lags are exploited for virtual extension of co-arrays both for differences and sums. The method offers higher degrees of freedom (DOF) with a larger number of non-negative consecutive lags equal to MN+2M+1 by using only M+N-1 number of sensors where M and N are coprime with congenial interelement spacings. A larger covariance matrix can be achieved by performing covariance like computations with the Khatri-Rao (KR) subspace based approach which can operate in undetermined cases and even can deal with unknown noise covariances. This paper concentrates on only non-negative consecutive lags and subspace based method like Multiple Signal Classification (MUSIC) based approach has been executed for DOA estimation. Hence, the proposed method, named Virtual Extension of Coprime Array imbibing Difference and Sum (VECADS), in this work is promising to create larger covariance matrix with higher DOF for high resolution DOA estimation. The coprime distribution yielded by the proposed approach can yield higher resolution DOA estimation while avoiding the mutual coupling effect. Simulation results demonstrate its effectiveness in terms of the accuracy of DOA estimation even with tightly aligned sources using fewer sensors compared with other techniques like prototype coprime, conventional coprime, Coprime Array with Displaced Subarrays (CADiS), CADiS after Coprime Array with Compressed Inter-element Spacing (CACIS) and nested array seizing only difference co-array.

In this paper, we present the effects of finite superstrates and asymmetrical grounds on the performance of high gain superstrate antennas. First, when the source of a superstrate antenna is located at an edge of a ground plane, that is, an asymmetric ground plane, the gain of the superstrate antenna can be made to match the gain of the superstrate antenna with a symmetrical ground plane using the PEC (E-plane asymmetric) or the AMC wall (H-plane asymmetric) near the edge. Second, the gain of the superstrate antenna, which has a ground plane with dimensions sufficiently close to infinite, is found to be roughly proportional to the reflection magnitude of a partially reflective surface (PRS). It is found that when the square ground size has a finite dimension of two wavelengths or less, the reflection magnitude of the PRS should have the optimum value for achieving maximum gain. Finally, the gain of the superstrate antenna is studied when the ground plane differs from a PRS. For the above three cases, the performances of the superstrate antenna are verified and compared by analysis, full-wave simulation, and measurement.

This paper presents the characteristics of path loss produced by traffic sign blockage. Multi frequency bands including high frequency bands up to 40 GHz are analyzed on the basis of measurement results in urban microcell environments. It is shown that the measured path loss increases compared to free space path loss even on a straight line-of-sight road, and that the excess attenuation is caused by the blockage effects of traffic signs. It is also shown that the measurement area affected by the blockage becomes small as frequency increases. The blocking object occupies the same area for all frequencies, but it takes up a larger portion of the Fresnel Zone as frequency increases. Therefore, if blockage occurs, the excess loss in high frequency bands becomes larger than in low frequency bands. In addition, the validity of two blockage path loss models is verified on the basis of measurement results. The first is the 3GPP blockage model and the second is the proposed blockage model, which is an expanded version of the basic diffraction model in ITU-R P.526. It is shown that these blockage models can predict the path loss increased by the traffic sign blockage and that their root mean square error can be improved compared to that of the 3GPP two slope model and a free space path loss model. The 3GPP blockage model is found to be more accurate for 26.4 and 37.1GHz, while the proposed model is more accurate for 0.8, 2.2, and 4.7GHz. The results show the blockage path loss due to traffic signs is clarified in a wide frequency range, and it is verified that the 3GPP blockage model and the proposed blockage model can accurately predict the blockage path loss.

We propose a cooperative cognitive radio network (CCRN) with secondary users (SUs) employing two simultaneous transmit and receive (STAR) antennas. In the proposed framework of full-duplex (FD) multiple-input-multiple-output (MIMO) CCRN, the region of achievable rate is expanded via FD communication among SUs enabled by the STAR antennas adopted for the SUs. The link capacity of the proposed framework is analyzed theoretically. It is shown through numerical analysis that the proposed FD MIMO-CCRN framework can provide a considerable performance gain over the conventional frameworks of CCRN and MIMO-CCRN.

In an X channel, multiple transmitters transmit independent signals to different receivers. Separate zero-forcing (ZF) precoding is used at transmitters in the two-user X channel with two transmitters and two receivers. A closed-form optimal power allocation is derived under the sum power constraint (SPC) to maximize the squared minimum distance. The ZF strategy with optimal power allocation achieves a significant signal to noise ratio (SNR) improvement. Under the individual power constraint (IPC), a suboptimal power allocation that achieves better performance compared to the existing algorithms is also proposed.

We propose an analytical model for IEEE 802.11 wireless local area networks (WLANs). The analytical model uses macroscopic descriptions of the distributed coordination function (DCF): the backoff process is described by a few macroscopic states (medium-idle, transmission, and medium-busy), which obviates the need to track the specific backoff counter/backoff stages. We further assume that the transitions between the macroscopic states can be characterized as a continuous-time Markov chain under the assumption that state persistent times are exponentially distributed. This macroscopic description of DCF allows us to utilize a two-dimensional continuous-time Markov chain for simplifying DCF performance analysis and queueing processes. By comparison with simulation results, we show that the proposed model accurately estimates the throughput performance and average queue length under light, heavy, or asymmetric traffic.

A triangular decomposition-based multipath super-resolution method is proposed to improve the range resolution of small unmanned aerial vehicle (UAV) radar altimeters that use a single channel with continuous direct spread waveform. In the engineering applications of small UAV radar altimeter, multipath scenarios are quite common. When the conventional matched filtering process is used under these environments, it is difficult to identify multiple targets in the same range cell due to the overlap between echoes. To improve the performance, we decompose the overlapped peaks yielded by matched filtering into a series of basic triangular waveforms to identify various targets with different time-shifted correlations of the pseudo-noise (PN) sequence. Shifting the time scale enables targets in the same range resolution unit to be identified. Both theoretical analysis and experiments show that the range resolution can be improved significantly, as it outperforms traditional matched filtering processes.