The Smart City paradigm has become one of the most important research topics around the globe. Particularly in Europe, it is considered as a solution for the unstoppable increase of high density urban environments and the European Commission has included the Smart City research as one of the key objectives for the FP7 (Seventh Framework Program) and H2020 (Horizon 2020) research initiatives. As a result, a considerable amount of quality research, with particular emphasis on information and communication technologies, has been produced. In this paper, we review the current efforts dedicated in Europe to this research topic. Particular attention is paid in the review to the platforms and infrastructure technologies adopted to introduce the Internet of Things into the city, taking into account the constraints and harshness of urban environments. Furthermore, this paper also considers the efforts in the experimental perspective, which includes the review of existing Smart City testbeds, part of wider European initiatives such as FIRE (Future Internet Research and Experimentation) and FIWARE. Last but not least, the main efforts in providing interoperability between the different experimental facilities are also presented.

This research aims to find the best practice of prototyping a smart Lingzhi mushroom farm in Thailand. This research applied the use of NodeMCU with a humidity sensor and IOT platform to measure and monitor the humidity in the Lingzhi mushroom farm. The humidity data proceeds through NETPIE was developed and provided by NECTEC, Thailand as a free service for IOT. The humidity data was stored into a NET FEED (a sub service from NETPIE) and displayed on mobile devices and computers through NET FREEBOARD (another sub service of NETPIE). This technology also automatically controlled the sprinkler, fog pumps, and the functional status (switching on and off periodically) of push notifications through LINE API on the LINE Application. The equipment and tools used in this research were NodeMCU, humidity sensor, RTC (real time clock), relay module, sprinkler and fog pumps. C++ and Node.JS were used for programming. The services and protocol used were NETPIE (Network Platform for internet of everything) with subservices such as NETPIE FEED, NETPIE FREEBOARD, and NETPIE REST API. The LINE API was also included. The results of the research show that using NodeMCU with the humidity sensor and IOT platform demonstrates the best practice of smart farming.

In this paper, we use the MCA (Multi-Cache Approximation) algorithm to numerically determine cache hit probability in a multi-cache network. We then analytically obtain performance metrics for Content-Centric networking (CCN). Our analytical model contains multiple routers, multiple repositories (e.g., storage servers), and multiple entities (e.g., clients). We obtain three performance metrics: content delivery delay (i.e., the average time required for an entity to retrieve a content through a neighboring router), throughput (i.e., number of contents delivered from an entity per unit of time), and availability (i.e., probability that an entity can successfully retrieve a content from a network). Through several numerical examples, we investigate how network topology affects the performance of CCN. A notable finding is that content caching becomes more beneficial in terms of content delivery time and availability (resp., throughput) as distance between the entity and the requesting repository narrows (resp., widens).

Information-centric networking (ICN) has received increasing attention from all over the world. The novel aspects of ICN (e.g., the combination of caching, multicasting, and aggregating requests) is based on names that act as addresses for content. The communication with name has the potential to cope with the growing and complicating Internet technology, for example, Internet of Things, cloud computing, and a smart society. To realize ICN, router hardware must implement an innovative cache replacement algorithm that offers performance far superior to a simple policy-based algorithm while still operating with feasible computational and memory overhead. However, most previous studies on cache replacement policies in ICN have proposed policies that are too blunt to achieve significant performance improvement, such as first-in first-out (popularly, FIFO) and random policies, or impractical policies in a resource-restricted environment, such as least recently used (LRU). Thus, we propose CLOCK-Pro Using Switching Hash-tables (CUSH) as the suitable policy for network caching. CUSH can identify and keep popular content worth caching in a network environment. CUSH also employs CLOCK and hash-tables, which are low-overhead data structure, to satisfy the cost requirement. We numerically evaluate our proposed approach, showing that our proposal can achieve cache hits against the traffic traces that simple conventional algorithms hardly cause any hits.

In recent years, software-defined networking (SDN), which performs centralized network management with software, has attracted much attention. Although packets are transmitted based on flow entries in SDN switches, the number of flow entries that the SDN switches can handle is limited. To overcome this difficulty, this paper proposes a flow-based routing method that performs flexible routing control with a small number of flow entries. The proposed method provides mixed integer programming. It assigns common paths to flows that can be aggregated at intermediate switches, while considering the utilization of network links. Because it is difficult for mixed integer programming to compute large-scale problems, the proposed method also provides a heuristic algorithm for them. Through numerical experiments, this paper shows that the proposed method efficiently reduces both the number of flow entries and the loads of congested links.

In this paper, we focus on two-layer wireless sensor networks (WSNs) that consist of sensor-concentrator and inter-concentrator networks. In order to collect as much data as possible from a wide area, improving of network capacity is essential because data collection applications often require to gather data within a limited period, i.e., acceptable collection delay. Therefore, we propose a two-stage scheduling method for inter-concentrator networks. The proposed method first strictly schedules time slots of links with heavy interference and congestion by exploiting the combination metric of interference and traffic demand. After that, it simply schedules time slots of the remaining sinks to mitigate complexity. Simulation-based evaluations show our proposal offers much larger capacity than conventional scheduling algorithms. In particular, our proposal improves up to 70% capacity compared with the conventional methods in situations where the proportion of one- and two-hop links is small.

There have been several recent reports that botnet communication between bot-infected computers and Command and Control servers (C&C servers) using the Domain Name System (DNS) protocol has been used by many cyber attackers. In particular, botnet communication based on the DNS TXT record type has been observed in several kinds of botnet attack. Unfortunately, the DNS TXT record type has many forms of legitimate usage, such as hostname description. In this paper, in order to detect and block out botnet communication based on the DNS TXT record type, we first differentiate between legitimate and suspicious usages of the DNS TXT record type and then analyze real DNS TXT query data obtained from our campus network. We divide DNS queries sent out from an organization into three types — via-resolver, and indirect and direct outbound queries — and analyze the DNS TXT query data separately. We use a 99-day dataset for via-resolver DNS TXT queries and an 87-day dataset for indirect and direct outbound DNS TXT queries. The results of our analysis show that about 30%, 8% and 19% of DNS TXT queries in via-resolver, indirect and direct outbound queries, respectively, could be identified as suspicious DNS traffic. Based on our analysis, we also consider a comprehensive botnet detection system and have designed a prototype system.

The remaining issues in optical transmission technology are the degradation of optical signal to noise power ratio due to amplifier noise and the distortions due to optical nonlinear effects in a fiber. Therefore in addition to the Shannon limit, practical channel capacity is believed to be restricted by the nonlinear Shannon limit. The nonlinear Shannon limit has been derived under the assumption that the received signal points on the constellation map deviated by optical amplifier noise and nonlinear interference noise are symmetrically distributed around the ideal signal point and the sum of the noises are regarded as white Gaussian noise. The nonlinear Shannon limit is considered as a kind of theoretical limitation. However it is doubtful that its derivation process and applicable range have been understood well. In this paper, some fundamental papers on the nonlinear Shannon limit are reviewed to better understanding its meaning and applicable range.

Today's enterprise, data-center, and internet-service-provider networks deploy different types of network devices, including switches, routers, and middleboxes such as network address translation and firewalls. These devices are vertically integrated monolithic systems. Software-defined networking (SDN) and network function virtualization (NFV) are promising technologies for dis-aggregating vertically integrated systems into components by using “softwarization”. Software-defined networking separates the control plane from the data plane of switch and router, while NFV decouples high-layer service functions (SFs) or Network Functions (NFs) implemented in the data plane of a middlebox and enables the innovation of policy implementation by using SF chaining. Even though there have been several survey studies in this area, this area is continuing to grow rapidly. In this paper, we present a recent survey of this area. In particular, we survey research activities in the areas of re-architecting middleboxes, state management, high-performance platforms, service chaining, resource management, and trouble shooting. Efforts in these research areas will enable the development of future virtual-network-function platforms and innovation in service management while maintaining acceptable capital and operational expenditure.

This paper proposes an oscillation model for analyzing the dynamics of activity propagation across social media networks. In order to analyze such dynamics, we generally need to model asymmetric interactions between nodes. In matrix-based network models, asymmetric interaction is frequently modeled by a directed graph expressed as an asymmetric matrix. Unfortunately, the dynamics of an asymmetric matrix-based model is difficult to analyze. This paper, first of all, discusses a symmetric matrix-based model that can describe some types of link asymmetry, and then proposes an oscillation model on networks. Next, the proposed oscillation model is generalized to arbitrary link asymmetry. We describe the outlines of four important research topics derived from the proposed oscillation model. First, we show that the oscillation energy of each node gives a generalized notion of node centrality. Second, we introduce a framework that uses resonance to estimate the natural frequency of networks. Natural frequency is important information for recognizing network structure. Third, by generalizing the oscillation model on directed networks, we create a dynamical model that can describe flaming on social media networks. Finally, we show the fundamental equation of oscillation on networks, which provides an important breakthrough for generalizing the spectral graph theory applicable to directed graphs.

To support the rapid increase of mobile traffic, the LTE-based air interface is expected to be employed in the unlicensed spectrum known as “Licensed-Assisted Access (LAA).” The LAA terminal, which employs an LTE-based air interface, suffers from interference from WiFi access points as well as the LAA base station. The interference rejection combining (IRC) receiver, which employs a linear minimum mean square error (MMSE) filter, can suppress this interference from WiFi access points in addition to that of the LAA base station. The IRC receiver is effective, since it requires no knowledge of the interference, which is generally difficult to obtain for different systems. In this paper, we use a link-level simulation to evaluate the performance of the IRC receiver in suppressing the interference from WiFi access points, and show that the IRC receiver can effectively cancel the interference from WiFi systems as well as LTE systems, although we observed a slight performance degradation due to the covariance matrix estimation error caused by the WiFi interference fluctuation in the frequency-domain.

In this paper, a spectrum efficient spatial polarized quadrature amplitude modulation (SPQM) scheme for physical layer security in dual-polarized satellite systems is proposed, which uses the carrier's polarization state, amplitude, phase and the polarization characteristics of the transmitting beams as information bearing parameters, which can improve the transmission efficiency and enhance the transmission security at the same time. As we know, the depolarization effect is the main drawback that affects the symbol error rate performance when polarization states are used to carry information. To solve the problem, we exploit an additional degree of freedom, time, in the proposed scheme, which means that two components of the polarized signal are transmitted in turn in two symbol periods, thus they can be recovered without mutual interference. Furthermore, orthogonal polarizations of the transmitting beam are used as spatial modulation for further increasing the throughput. In addition, in order to improve the transmission security, two transmitting beams are designed to transmit the two components of the polarized signal respectively. In this way, a secure transmission link is formed from the transmitter to the receiver to prevent eavesdropping. Finally, superiorities of SPQM are validated by the theoretical analysis and simulation results in dual-polarized satellite systems.

The demand for wireless traffic is increasing rapidly, which has posed huge challenges to mobile network operators (MNOs). A heterogeneous network (HetNet) framework, composed of a marcocell and femtocells, has been proved to be an effective way to cope with the fast-growing traffic demand. In this paper, we assume that both the macrocell and femtocells are owned by the same MNO, with revenue optimization as its ultimate goal. We aim to propose a pricing strategy for macro-femto HetNets with a user centric vision, namely, mobile users would have their own interest to make rational decisions on selecting between the macrocell and femtocells to maximize their individual benefit. We formulate a Stackelberg game to analyze the interactions between the MNO and users, and obtain the equilibrium solution for the Stackelberg game. Via extensive simulations, we evaluate the proposed pricing strategy in terms of its efficiency with respect to the revenue optimization.

In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.

We propose a wideband antenna that has both vertical and horizontal polarization to create access points with enhanced connectivity. The antenna is composed of a rectangular plate and a ground plate, and the rectangular plate is fed sideways from the ground plate. Its -10dB fractional bandwidth is approximately 162%. It is shown that the offset feed of the rectangular plate is important to attain wideband impedance matching and vertical polarized wave. The results of a parametric study to characterize the first- and second-lowest resonant frequencies are presented. Moreover, the behavior of the impedance matching and polarization is interpreted by dividing the current distribution around the feed port on the rectangular plate into the same direction current mode and the opposite direction current mode. The measured results for the return loss and the radiation pattern of a prototype antenna agree well with the simulation results, therefore the wideband property was experimentally confirmed.

In this paper, we propose a low-complexity widely-linear minimum mean square error (WL-MMSE) signal detection based on the Chebyshev polynomials accelerated symmetric successive over relaxation (SSORcheb) algorithm for uplink (UL) over-loaded large-scale multiple-input multiple-output (MIMO) systems. The technique of utilizing Chebyshev acceleration not only speeds up the convergence rate significantly, and maximizes the data throughput, but also reduces the cost. By utilizing the random matrix theory, we present good estimates for the Chebyshev acceleration parameters of the proposed signal detection in real large-scale MIMO systems. Simulation results demonstrate that the new WL-SSORcheb-MMSE detection not only outperforms the recently proposed linear iterative detection, and the optimal polynomial expansion (PE) WL-MMSE detection, but also achieves a performance close to the exact WL-MMSE detection. Additionally, the proposed detection offers superior sum rate and bit error rate (BER) performance compared to the precision MMSE detection with substantially fewer arithmetic operations in a short coherence time. Therefore, the proposed detection can satisfy the high-density and high-mobility requirements of some of the emerging wireless networks, such as, the high-mobility Internet of Things (IoT) networks.

The radio wave shadowing by a two-dimensional human body is examined numerically as the scattering problem by using the Method of Moments (MoM) in order to verify the equivalent human body diameter. Three human body models are examined: (1) a circular cylinder, (2) an elliptical cylinder, and (3) an elliptical cylinder with two circular cylinders are examined. The scattered fields yields by the circular cylinder are compared with measured data. Since the angle of the model to an incident wave affects scattered fields in models other than a circular cylinder, the models of an elliptical cylinder and an elliptical cylinder with two circular cylinders are converted into a circular cylinder of equivalent diameter. The frequency characteristics for the models are calculated by using the equivalent diameter.

Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.

In Cognitive Radio Networks (CRNs), spectrum sensing is performed by secondary (unlicensed) users to utilize transmission opportunities, so-called white spaces or spectrum holes, in the primary (licensed) frequency bands. Secondary users (SUs) perform sensing upon arrival to find an idle channel for transmission as well as during transmission to avoid interfering with primary users (PUs). In practice, spectrum sensing is not perfect and sensing errors including false alarms and misdetections are inevitable. In this paper, we develop a continuous-time Markov chain model to study the effect of false alarms and misdetections of SUs on several performance measures including the collision rate between PUs and SUs, the throughput of SUs and the SU delay in a CRN. Numerical results indicate that sensing errors can have a high impact on the performance measures.

The generalized spatial modulation (GSM) is a new transmission technique that can realize high-performance multiple-input multiple-output (MIMO) communication systems with a low RF complexity. This paper presents an efficient sphere decoding method used to perform the symbol detection for the generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems. In the proposed method, the cost metric is modified so that it does not include the cancellation of the nonexistent interference. The modified cost metric can be computed by formulating a detection tree that has a regular structure representing the transmit antenna combinations as well as the symbol vectors, both of which are detected efficiently by finding the shortest path on the basis of an efficient tree search algorithm. As the tree search algorithm is performed for the regular detection tree to compute the modified but mathematically-equivalent cost metric, the efficiency of the sphere decoding is improved while the bit-error rate performance is not degraded. The simulation results show that the proposed method reduces the complexity significantly when compared with the previous method: for the 6×6 64QAM GSM-MIMO system with two active antennas, the average reduction rate of the complexity is as high as 45.8% in the count of the numerical operations.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

In cellular network environments, where users are not evenly distributed across cells, overloaded base stations handling many users have difficulties in providing effective and fair services with their limited resources. Additionally, users at the cell edge may suffer from the potential problems resulting from low signal-to-interference ratio owing to the incessant interference from adjacent cells. In this paper, we propose a relay-assisted load balancing scheme to resolve these traffic imbalance. The proposed scheme can improve the performance of the overall network by utilizing relay stations to divert heavy traffic to other cells, and by adopting a partial frequency-reuse scheme to mitigate inter-cell interference. Each user and relay station calculates its own utility influence in the neighboring candidates for reassociation and decides whether to stay or move to another cell presenting the maximum total network utility increment. Simulation results show that the proposed scheme improves the overall network fairness to users by improving the performance of cell boundary users without degrading the total network throughput. We achieve a system performance gain of 16 ∼ 35% when compared with conventional schemes, while ensuring fairness among users.

The smart grid is expected to be the next generation electricity grid. It is beneficial for communication systems to improve energy efficiency and reduce carbon emissions. In this paper, we propose a distributed game theoretical framework for decode-and-forward (DF) cooperative relay networks with smart grid. A relay selection and power allocation strategy based on the buyer-seller game is proposed that processes the statistic channel-state information (CSI) available. The user is modeled as a buyer who selects the optimal relay and determines the optimal amount of power to be bought from the relay by the maximum utility criterion. The relay powered by the smart grid is modeled as a seller who determines the price of the power to achieve the maximum profit with its own cost. The equilibrium conditions of the game between the two sides are analyzed. The simulation results verify the existence of a Nash equilibrium point and illustrate that the proposed strategy may guarantee the utility of the source, the relay and the network and increase the energy efficiency.