Crowdsensing-based spectrum detection (CSD) is promising to enable full-coverage radio resource availability for the increasingly connected machines in the Internet of Things (IoT) networks. The current CSD scheme consumes a lot of energy and network resources for local sensing, processing, and distributed data reporting for each crowdsensing device. Furthermore, when the amount of reported data is large, the data fusion implemented at the requestor can easily cause high latency. For improving efficiencies in both energy and network resources, this paper proposes a green CSD (GCSD) paradigm. The ambient backscatter (AmB) is used to enable a battery-free mode of operation in which the received spectrum data is reported directly through backscattering without local processing. The energy for backscattering can be provided by ambient radio frequency (RF) sources. Then, relying on air computation (AirComp), the data fusion can be implemented during the backscattering process and over the air by utilizing the summation property of wireless channel. This paper illustrates the model and the implementation process of the GCSD paradigm. Closed-form expressions of detection metrics are derived for the proposed GCSD. Simulation results verify the correctness of the theoretical derivation and demonstrate the green properties of the GCSD paradigm.

In this paper, we propose a Mobile Edge Internet of Things (MEIoT) architecture by leveraging the fiber-wireless access technology, the cloudlet concept, and the software defined networking framework. The MEIoT architecture brings computing and storage resources close to Internet of Things (IoT) devices in order to speed up IoT data sharing and analytics. Specifically, the IoT devices (belonging to the same user) are associated to a specific proxy Virtual Machine (VM) in the nearby cloudlet. The proxy VM stores and analyzes the IoT data (generated by its IoT devices) in real-time. Moreover, we introduce the semantic and social IoT technology in the context of MEIoT to solve the interoperability and inefficient access control problem in the IoT system. In addition, we propose two dynamic proxy VM migration methods to minimize the end-to-end delay between proxy VMs and their IoT devices and to minimize the total on-grid energy consumption of the cloudlets, respectively. Performance of the proposed methods is validated via extensive simulations.

This paper deals with the scattering of a cylindrical wave by a perfectly conductive periodic surface. This problem is equivalent to finding the Green's function G(x,z|xs,zs), where (x,z) and (xs,zs) are the observation and radiation source positions above the periodic surface, respectively. It is widely known that the Green's function satisfies the reciprocity: G(x,z|xs,zs)=G(xs,zs|x,z), where G(xs,zs|x,z) is named the reversal Green's function in this paper. So far, there is no numerical method to synthesize the Green's function with the reciprocal property in the grating theory. By combining the shadow theory, the reciprocity theorem for scattering factors and the average filter introduced previously, this paper gives a new numerical method to synthesize the Green's function with reciprocal property. The reciprocity means that any properties of the Green's function can be obtained from the reversal Green's function. Taking this fact, this paper obtains several new formulae on the radiation and scattering from the reversal Green's function, such as a spectral representation of the Green's function, an asymptotic expression of the Green's function in the far region, the angular distribution of radiation power, the total power of radiation and the relative error of power balance. These formulae are simple and easy to use. Numerical examples are given for a very rough periodic surface. Several properties of the radiation and scattering are calculated for a transverse magnetic (TM) case and illustrated in figures.

This paper newly proposes a fast computation technique on the method of image Green's function for p-characteristic calculations, when a plane wave with the transverse wavenumber p is incident on a periodic rough surface having perfect conductivity. In the computation of p-characteristics, based on a spectral domain periodicity of the periodic image Green's function, the image integral equation for a given incidence p maintains the same form for other particular incidences except for the excitation term. By means of a quadrature method, such image integral equations lead to matrix equations. Once the first given matrix equation is performed by a solution procedure as calculations of its matrix elements and its inverse matrix, the other matrix equations for other particular incidences no longer need such a solution procedure. Thus, the total CPU time for the computation of p-characteristics is largely reduced in complex shaped surface cases, huge roughness cases or large period cases.

In this letter, we propose an improved timing offset estimation scheme without making use of pilot symbols in the HomePlug Green PHY (HomePlug GP) standard. In contrast to the conventional decision-directed timing estimation scheme, the proposed scheme exploits the inherent repetition information of the HomePlug GP signals, thus not only removing the need for the estimated data or pilot symbols but also improving the timing estimation performance.

As a research project supported jointly by the National Institute of Information and Communications Technology (NICT) in Japan and the European Commission under its 7th Framework Program, the GreenICN Project has been in operation from 2013 to 2016. The GreenICN project focused on two typical application scenarios, one a disaster scenario and the other a video delivery scenario. The disaster scenario assumed a situation of limited resources, and the video delivery scenario assumed a situation of large-scale content delivery. In both situations, the project challenged to provide “green”, i.e. energy-efficient, content delivery mechanism. For this goal, we designed an energy consumption model to lay out energy reduction policies. For the achievement of the policies, we improved ICN architecture, for example a name-based publish/subscribe mechanism, an effective cache management policy,energy-efficient security scheme and a new energy API. This paper provides a summary of our achievements and descriptions of some outcome.

In the conventional cellular macrocell implementation strategy, the main base station transmits the radio signals in the omnidirectional manner in order to provide a wide range of cellular transmission to the users. In reality, however, the users move from one place to another depending on their activities, hence, sometimes this creates areas where no user exists inside the macrocell. Nevertheless, the base station continues to transmit the radio signals to all the coverage areas due to its involuntary manner, thus causing waste of energy. In our previous work, an energy efficient LTE macrocell base station scheme based on hourly user location distribution, which utilized opportunistic beamforming, was proposed in order to provide the cellular transmission only to the area where the user density is high. The drawback of this scheme was that there were many users who cannot receive the cellular transmission because of the limitation of the beamforming shape. In this paper, to overcome this difficulty, a new energy efficient macrocell strategy will be proposed. Here, additional low power consumption femtocell access points are deployed inside the macrocell to support the energy efficient opportunistic beamforming based on the hourly user location distribution. Concretely, the femtocell access points are woken up only when the active calling users exist inside its range. The proposed new strategy will be evaluated in terms of the hourly successful calling user ratio, the total power consumption and the hourly average downlink throughput compared with the previously proposed beamforming transmission strategy and the conventional omnidirectional transmission. The results will show the effectiveness of the proposed strategy in providing an energy efficient cellular macrocell system with high quality cellular services.

This paper investigates the impact of hidden nodes (HNs) on on-demand access point (AP) wake-up that is employed to realize energy-efficient wireless LANs (WLANs). The considered wake-up signaling exploits IEEE 802.11 signals transmitted by a WLAN station (STA) to remotely activate a sleeping AP: a STA with communication demands transmits a series of WLAN frames with their length corresponding to the wake-up ID. A wake-up receiver attached to each AP detects the length of WLAN frames with the low-power operations of envelope detection and on-off-keying (OOK) demodulation. Since WLAN frames constituting a wake-up signal are transmitted by a STA following carrier sense multiple access (CSMA) protocol, they are vulnerable to the well-known hidden node (HN) problem. The impact of HNs on wake-up signaling is different from that on data communications since the wake-up receiver employs unconventional frame length detection to extract the information on the wake-up ID from the received signal. In this paper, we first investigate the impact of HNs on wake-up failure probability with theoretical and experimental evaluations. If the degradation of wake-up signalling due to HNs is observed for a STA, the corresponding STA may suffer from collisions due to the same HNs for its data communications even if it manages to succeed in the wake-up process. In this case, the wake-up operation itself may not be necessary. Therefore, we also compare the impact of HNs on wake-up signaling and that on data communications after the wake-up process. These results and discussions provide us with an insight on the impact of HNs on on-demand AP wake-up exploiting WLAN signals.

This paper proposes a novel image integral equation of the first type (IIE-1) for a TE plane wave scattering from periodic rough surfaces with perfect conductivity by means of the method of image Green's function. Since such an IIE-1 is valid for any incident wavenumbers including the critical wavenumbers, the analytical properties of the scattered wavefield can be generally and rigorously discussed. This paper firstly points out that the branch point singularity of the bare propagator inevitably appears on the incident wavenumber characteristics of the scattered wavefield and its related quantities just at the critical wavenumbers. By applying a quadrature method, the IIE-1 becomes a matrix equation to be numerically solved. For a periodic rough surface, several properties of the scattering are shown in figures as functions of the incident wavenumbers. It is then confirmed that the branch point singularity clearly appears in the numerical solution. Moreover, it is shown that the proposed IIE-1 gives a numerical solution satisfying sufficiently the optical theorem even for the critical wavenumbers.

In this paper, we propose a novel censor-based cooperative spectrum sensing strategy, called adaptive energy-efficient sensing (AES), in which both sequential sensing and censoring report mechanism are employed, aiming to reduce the sensing energy consumption of secondary user relays (SRs). In AES, an anchor secondary user (SU) requires cooperative sensing only when it does not detect the presence of PU by itself, and the cooperative SR adopts decision censoring report only if the sensing result differs from its previous one. We derive the generalized-form expressions false alarm and detection probabilities over Rayleigh fading channels for AES. The sensing energy consumption is also analyzed. Then, we study sensing energy overhead minimization problem and show that the sensing time allocation can be optimized to minimize the miss detection probability and sensing energy overhead. Finally, numerical results show that the proposed strategy can remarkably reduce the sensing energy consumption while only slightly degrading the detection performance compared with traditional scheme.

This paper proposes a new optimization problem and several implementation algorithms for energy-efficient clouds where energy efficiency is measured by the number of physical machines that can be removed from operation and turned off. The optimization problem is formulated is such a way that solutions are considered favorable not only when the number of migrations is minimized but also when the resulting layout has more free physical machines which can therefore be turned off to save electricity.

This paper deals with an integral equation method for analyzing the diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive periodic surface. In the region below the periodic surface, the extinction theorem holds, and the total field vanishes if the field solution is determined exactly. For an approximate solution, the extinction theorem does not hold but an extinction error field appears. By use of an image Green's function, new formulae are given for the extinction error field and the mean square extinction error (MSEE), which may be useful as a validity criterion. Numerical examples are given to demonstrate that the formulae work practically even at a critical angle of incidence.

The present paper introduces a prototype design and experimental results for a multi-user MIMO linear precoding system. A base station and two mobile stations are implemented by taking full advantage of the software-defined radio. The base station consists of general purpose signal analyzers and signal generators controlled by a personal computer. Universal software radio peripherals are used as mobile stations. Linear spatial precoding and a simple two-way channel estimation technique are adopted in this experimental system. In-lab and field transmission experiments are carried out, and the bit error rate performance is evaluated. The impact of the channel estimation error under average channel gain discrepancy between two mobile stations is analyzed through computer simulations. Channel estimation error is shown to have a greater influence on the mobile station with the greater average channel gain.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

This paper deals with an integral method analyzing the diffraction of a transverse electric (TE) wave by a perfectly conductive periodic surface. The conventional integral method fails to work for a critical angle of incidence. To overcome such a drawback, this paper applies the method of image Green's function. We newly obtain an image integral equation for the basic surface current in the TE case. The integral equation is solved numerically for a very rough sinusoidal surface. Then, it is found that a reliable solution can be obtained for any real angle of incidence including a critical angle.

Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

This paper deals with the diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive periodic surface by an integral method. However, it is known that a conventional integral method does not work for a critical angle of incidence, because of divergence of a periodic Green's function (integral kernel). To overcome such a divergence difficulty, we introduce an image Green's function which is physically defined as a field radiated from an infinite phased array of dipoles. By use of the image Green's function, it is newly shown that the diffracted field is represented as a sum of radiation from the periodic surface and its image surface. Then, this paper obtains a new image integral equation for the basic surface current, which is solved numerically. A numerical result is illustrated for a very rough sinusoidal surface. Then, it is concluded that the method of image Green's function works practically even at a critical angle of incidence.

Well-crystallized Ba2SiO4:Eu2+ powders were grown on a substrate by the vapor phase reaction between a mixed powder (barium carbonate and europium oxide) and SiO gas. The vaporization of SiO occurs at 1400–1600 from the SiO2 source (or SiO powder) in a reducing atmosphere. The formed SiO gas was transported by 95 vol% Ar - 5 vol% H2 gas and reacted with the raw material powders. The emission intensity of the Ba2SiO4:Eu2 + phosphor synthesized by the new vapor phase technique is about 2.6 times higher than that of a conventional solid-state reaction sample.

With energy shortages and global climate change leading our concerns these days, the energy consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduler for reducing energy consumption of datacenters in Cloud computing platforms. It is composed of four algorithms: prediction, ON/OFF, task scheduling, and evaluation algorithms. The prediction algorithm employs a neural predictor to predict future load demand based on historical demand. According to the prediction, the ON/OFF algorithm dynamically adjusts server allocations to minimize the number of servers running, thus minimizing the energy use at the points of consumption to benefit all other levels. The task scheduling algorithm is responsible for directing request traffic away from powered-down servers and toward active servers. The performance is monitored by the evaluation algorithm to balance the system's adaptability against stability. For evaluation, we perform simulations with two load traces. The results show that the prediction mode, with a combination of dynamic training and dynamic provisioning of 20% additional servers, can reduce energy consumption by 49.8% with a drop rate of 0.02% on one load trace, and a drop rate of 0.16% with an energy consumption reduction of 55.4% on the other. Our method is also proven to have a distinct advantage over its counterparts.

The idea of using molecules and molecular structures as functional electronic device, promises to substantially decrease the size and improve the performance of electronic devices. In this paper, nonequilibrium Green's function formalism (NEGF) combined with extended Huckel theory (EHT), a semiempirical approach is used to study the electron transport phenomenon in single molecular junction systems. Benzene diamine molecule is studied to investigate the bonding of amine group to gold electrodes and the electron transport across the junction. The results are compared with that of benzene dithiol molecule with thiol end groups. Furthermore, the influence of charging and torsion angle on the transport characteristics is emphasized.