Cloud computing, which enables users to enjoy various Internet services provided by data centers (DCs) at anytime and anywhere, has attracted much attention. In cloud computing, however, service quality degrades with user distance from the DC, which is unfair. In this study, we propose a bandwidth allocation scheme based on collectable information to improve fairness and link utilization in DC networks. We have confirmed the effectiveness of this approach through simulation evaluations.

Clustering is known to be an effective means of reducing energy dissipation and prolonging network lifetime in wireless sensor networks (WSNs). Recently, game theory has been used to search for optimal solutions to clustering problems. The residual energy of each node is vital to balance a WSN, but was not used in the previous game-theory-based studies when calculating the final probability of being a cluster head. Furthermore, the node payoffs have also not been expressed in terms of energy consumption. To address these issues, the final probability of being a cluster head is determined by both the equilibrium probability in a game and a node residual energy-dependent exponential function. In the process of computing the equilibrium probability, new payoff definitions related to energy consumption are adopted. In order to further reduce the energy consumption, an assistant method is proposed, in which the candidate nodes with the most residual energy in the close point pairs completely covered by other neighboring sensors are firstly selected and then transmit same sensing data to the corresponding cluster heads. In this paper, we propose an efficient energy-aware clustering protocol based on game theory for WSNs. Although only game-based method can perform well in this paper, the protocol of the cooperation with both two methods exceeds previous by a big margin in terms of network lifetime in a series of experiments.

We propose a policy UCB-SC for budgeted multi-armed bandits. The policy is a variant of recently proposed KL-UCB-SC. Unlike KL-UCB-SC, which is computationally prohibitive, UCB-SC runs very fast while keeping KL-UCB-SC's asymptotical optimality when reward and cost distributions are Bernoulli with means around 0.5, which are verified both theoretically and empirically.

Irreversible thermal paints or temperature sensitive paints are a kind of special temperature sensor which can indicate the temperature grad by judging the color change and is widely used for off-line temperature measurement during aero engine test. Unfortunately, the hot gases flow within the engine during measuring always make the paint color degraded, which means a serious saturation reduction and contrast loss of the paint colors. This phenomenon makes it more difficult to interpret the thermal paint test results. Present contrast enhancement algorithms can significantly increase the image contrast but can't protect the hue feature of the paint images effectively, which always cause color shift. In this paper, we propose a color restoration method for thermal paint image. This method utilizes the atmospheric scattering model to restore the lost contrast and saturation information, so that the hue can be protected and the temperature can be precisely interpreted based on the image.

We present a design approach and analysis of a multimode stripline resonator (MSR). Furthermore, a bandpass filter (BPF) using a single MSR is presented. MSR has three fundamental modes, incorporating two transmission resonance modes and one quasi-lumped component (LC) resonance mode. The resonant frequencies and unloaded Q factors of those modes are theoretically derived by transmission modes and LC modes. By our equations, it is also explained that the resonant frequencies can be shown to be easily handled by an increase and decrease in the number of via holes. These frequencies calculated by our equations are in good agreement with those of 3-D simulations and measurements. Finally, design approach of a narrow bandpass filter using our resonator is introduced. Good agreement between measured and computed result is obtained.

As the emergence and the thriving development of social networks, a huge number of short texts are accumulated and need to be processed. Inferring latent topics of collected short texts is an essential task for understanding its hidden structure and predicting new contents. A biterm topic model (BTM) was recently proposed for short texts to overcome the sparseness of document-level word co-occurrences by directly modeling the generation process of word pairs. Stochastic inference algorithms based on collapsed Gibbs sampling (CGS) and collapsed variational inference have been proposed for BTM. However, they either require large computational complexity, or rely on very crude estimation that does not preserve sufficient statistics. In this work, we develop a stochastic divergence minimization (SDM) inference algorithm for BTM to achieve better predictive likelihood in a scalable way. Experiments show that SDM-BTM trained by 30% data outperforms the best existing algorithm trained by full data.

In this letter, a novel on-orbit estimation and calibration method of GPS antenna geometry offsets for attitude determination of LEO satellites is proposed. Both baseline vectors in the NED coordinate system are achieved epoch-by-epoch firstly. Then multiple epochs' baseline vectors are united to compute all the offsets via an UKF for a certain long time. After on-orbit estimation and calibration, instantaneous and accurate attitude can be achieved. Numerical results show that the proposed method can obtain the offsets of each baseline in all directions with high accuracy estimation and small STDs, and effective attitudes can be achieved after antenna geometry calibration using the estimated offsets. The high accuracy give the proposed scheme a strong practical-oriented ability.

To reduce the backbone video traffic generated by video surveillance, we propose an intelligent video surveillance system that offers multi-modal sensor-based event detection and event-driven video rate adaptation. Our proposed system can detect pedestrian existence and movements in the monitoring area by using multi-modal sensors (camera, laser scanner and infrared distance sensor) and control surveillance video quality according to the detected events. We evaluate event detection accuracy and video traffic volume in the experiment scenarios where up to six pedestrians pass through and/or stop at the monitoring area. Evaluation results conclude that our system can significantly reduce video traffic while ensuring high-quality surveillance.

This paper presents an approximated log-likelihood ratio calculation scheme with bit shifts and summations. Our previous work yielded a metric calculation scheme that replaces multiplications with bit shifts and summations in the selection of candidate signal points for joint maximum likelihood detection (MLD). Log-likelihood ratio calculation for turbo decoding generally uses multiplications and by replacing them with bit shifts and summations it is possible to reduce the numbers of logic operations under specific transmission parameters. In this paper, an approximated log-likelihood ratio calculation scheme that substitutes bit shifts and summations for multiplications is proposed. In the proposed scheme, additions are used only for higher-order bits. Numerical results obtained through computer simulation show that this scheme can eliminate multiplications in turbo decoding at the cost of just 0.2dB performance degradation at a BER of 10-4.

Network-listening-based synchronization is recently attracting attention as an effective timing synchronization method for indoor small-cell base stations as they cannot utilize GPS-based synchronization. It uses only the macro-cell downlink signal to establish synchronization with the overlaying macro cell. However, the loop-back signal from the small-cell base station itself interferes with the reception of the macro-cell downlink signal in the deployment of co-channel heterogeneous networks. In this paper, we investigate a synchronization method that avoids loop-back interference by muting small-cell data transmission and shifting small-cell transmission timing. Our proposal enables to reduce the processing burden of the network listening and mitigate the throughput degradation of the small cell caused by the data-transmission mutation. In addition to this, the network-listening system enables the network listening in dense small cell deployments where a large number of neighboring small cells exist. We clarify the performance of our proposal by computer simulations and laboratory experiments on actual equipment.

Software-defined networking (SDN) has emerged as a promising approach to enable network innovation, which can provide network virtualization through a hypervisor plane to share the same cloud datacenter network among multiple virtual networks. While, this attractive approach may bring some new problem that leads to more susceptible to the failure of network component because of the separated control and forwarding planes. The centralized control and virtual network sharing the same physical network are becoming fragile and prone to failure if the topology of virtual network and the control path is not properly designed. Thus, how to map virtual network into physical datacenter network in virtualized SDN while guaranteeing the survivability against the failure of physical component is extremely important and should fully consider more influence factors on the survivability of virtual network. In this paper, combining VN with SDN, a topology-aware survivable virtual network embedding approach is proposed to improve the survivability of virtual network by an enhanced virtual controller embedding strategy to optimize the placement selection of virtual network without using any backup resources. The strategy explicitly takes account of the network delay and the number of disjoint path between virtual controller and virtual switch to minimize the expected percentage of control path loss with survivable factor. Extensive experimental evaluations have been conducted and the results verify that the proposed technology has improved the survivability and network delay while keeping the other within reasonable bounds.

In this study, the reference pure metal-oxide semiconductor field-effect transistors (MOSFETs) and low-voltage (LV) and high-voltage (HV) MOSFETs with a super-junction (SJ) structure in the drain side were experimentally compared. The results show that the drain-side engineering of SJs exerts negative effects on the electrostatic discharge (ESD) and latch-up (LU) immunities of LV n-channel MOSFETs, whereas for LV p-channel MOSFETs and HV n-channel laterally diffused MOSFETs (nLDMOSs), the effects are positive. Compared with the pure MOSFET, electrostatic discharge (ESD) robustness (It2) decreased by approximately 30.25% for the LV nMOS-SJ, whereas It2 increased by approximately 2.42% and 46.63% for the LV pMOS-SJ and HV nLDMOS-SJ, respectively; furthermore, LU immunity (Vh) decreased by approximately 5.45% for the LV nMOS-SJ, whereas Vh increased by approximately 0.44% and 35.5% for the LV pMOS-SJ and HV nLDMOS-SJ, respectively. Thus, nMOS-SJ (pMOS-SJ and nLDMOS-SJ) has lower (higher) It2 and Vh, and this drain-side SJ structure of MOSFETs is an inferior (superior) choice for improving the ESD/LU reliability of LV nMOSs (LV pMOS and HV nLDMOS).

Phase locking with frequency tuning is demonstrated for a resonant-tunneling-diode terahertz oscillator integrated with a biased varactor diode. The tuning range of oscillation frequency is 606-613GHz. The phase noise in the output of the oscillator is transformed to amplitude noise, and fed back to the varactor diode together with bias voltage. The spectral linewidth at least <2Hz was obtained at the oscillation frequencies tuned by the bias voltage of the varactor diode.

A grammar compression is a restricted context-free grammar (CFG) that derives a single string deterministically. The goal of a grammar compression algorithm is to develop a smaller CFG by finding and removing duplicate patterns, which is simply a frequent pattern discovery process. Any frequent pattern can be obtained in linear time; however, a huge working space is required for longer patterns, and the entire string must be preloaded into memory. We propose an online algorithm to address this problem approximately within compressed space. For an input sequence of symbols, a1,a2,..., let Gi be a grammar compression for the string a1a2…ai. In this study, an online algorithm is considered one that can compute Gi+1 from (Gi,ai+1) without explicitly decompressing Gi. Here, let G be a grammar compression for string S. We say that variable X approximates a substring P of S within approximation ratio δ iff for any interval [i,j] with P=S[i,j], the parse tree of G has a node labeled with X that derives S[l,r] for a subinterval [l,r] of [i,j] satisfying |[l,r]|≥δ|[i,j]|. Then, G solves the frequent pattern discovery problem approximately within δ iff for any frequent pattern P of S, there exists a variable that approximates P within δ. Here, δ is called the approximation ratio of G for S. Previously, the best approximation ratio obtained by a polynomial time algorithm was Ω(1/lg2|P|). The main contribution of this work is to present a new lower bound Ω(1/<*|S|lg|P|) that is smaller than the previous bound when lg*|S|

IEEE 802.11ah is a new wireless standard for large-scale wireless connectivity in IoT and M2M applications. One of the major requirements placed on IEEE 802.11ah is the energy-efficient communication of several thousand stations with a single access point. This is especially difficult to achieve during network initialization, because the several thousand stations must rely on the rudimentary approach of random channel access, and the inevitable increase in channel access contention yields a long association delay. IEEE 802.11ah has introduced an authentication control mechanism that classifies stations into groups, and only a small number of stations in a group are allowed to access the medium at a time. Although the grouping strategy provides fair channel access to a large number of stations, the presence of several thousand stations and limitation that only a group can use the channel at a time, causes the association time to remain excessive. In this paper, we propose a novel block association method that enables simultaneous association of all groups. Our experiments verify that our block association method decreases the total association time by many folds.

The conventional generalized spatial modulation (GSM) simultaneously activates multiple transmit antennas in order to improve the spectral efficiency of the original SM. In this letter, to lessen the hardware burden of the multiple RF chains, we provide a new scheme that is designed by combining the GSM scheme using only two active antennas with quaternary quasi-orthogonal sequences of a length of two. Compared with the other SM schemes, the proposed scheme has significant benefits in average error performances and/or their hardware complexities of the RF systems.

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.

Peer-to-peer overlay networks can easily achieve a large-scale content sharing system on the Internet. Although unstructured peer-to-peer networks are suitable for finding entire partial-match content, flooding-based search is an inefficient way to obtain target content. When the shared content is semantically specified by a great number of attributes, it is difficult to derive the semantic similarity of peers beforehand. This means that content search methods relying on interest-based locality are more advantageous than those based on the semantic similarity of peers. Existing search methods that exploit interest-based locality organize multiple peer groups, in each of which peers with common interests are densely connected using short-cut links. However, content searches among multiple peer groups are still inefficient when the number of incident links at each peer is limited due to the capacity of the peer. This paper proposes a novel content search method that exploits interest-based locality. The proposed method can organize an efficient peer-to-peer network similar to the semantic small-world random graph, which can be organized by the existing methods based on the semantic similarity of peers. In the proposed method, topology transformation based on local link replacement maintains the numbers of incident links at all the peers. Simulation results confirm that the proposed method can achieve a significantly higher ratio of obtainable partial-match content than existing methods that organize peer groups.

Codes over permutations and multipermutations have received considerable attention since the rank modulation scheme is presented for flash memories. Deletions in multipermutations often occur due to data synchronization errors. Based on the interleaving of several single-deletion-correcting multipermutation codes, we present a construction of multipermutation codes for correcting a burst of at most t deletions with shift magnitude one for t ≥2. The proposed construction is proved with including an efficient decoding method. A calculation example is provided to validate the construction and its decoding method.

A 2nd-order ΔΣAD modulator architecture is proposed to simplify the operation phase using ring amplifier and SAR quantizer. The proposed modulator architecture can guarantee the reset time for ring amplifier and relax the speed requirement on asynchronous SAR quantizer. The SPICE simulation results demonstrate the feasibility of the proposed 2nd-order ΔΣAD modulator in 90nm CMOS technology. Simulated SNDR of 95.70dB is achieved while a sinusoid -1dBFS input is sampled at 60MS/s for the bandwidth is BW=470kHz. The power consumption of the analog part in the modulator is 1.67mW while the supply voltage is 1.2V.