Skyline queries on sensor networks have attracted much attention from the database research community due to their wide applications related to multi-criteria decision making. The existing methods use filters that are based on the data locality of sensor nodes and routing paths. However, they have two serious problems: i) unnecessary data transmission is still to frequent. ii) the processing cost of a continuous skyline query on high-dimensional data is very high. In this paper, we propose a new method that uses competitive mechanisms for processing continuous skyline queries. The proposed method dramatically reduces the data transmissions of sensors and quickly processes a continuous skyline query on high-dimensional data. An extensive performance study verifies the merits of our new method.

“Internet of Things” (IoT) requires information to be collected from “anything”, “anytime”, and “anywhere”. In order to achieve this, wireless devices are required that have (1) automatic data acquisition capability, (2) small size, (3) long life, and (4) long range communication capability. One way to meet these requirements is to adopt active Radio Frequency Identification (RFID) systems. Active RFID is more advantageous than passive RFID and enables higher data reading performance over longer distances. This paper surveys active RFID systems, the services they currently promise to provide, technical problems common to these services, and the direction in which research should head in the future. It also reports the results of EPCglobal (EPC: Electronic Product Code) pilot tests conducted on global logistics for tracking ocean/air container transportation using active RFID systems for which we developed several new types of active RFID tags. The test results confirm that our active RFID tags have sufficient capability and low power consumption to well support ocean/air transportation and logistics service.

In this letter, we introduce two different resource allocation and Tx power management schemes, called resource control and fixed power (RCFP) and fixed resource and power control (FRPC), in an LTE-Advanced femtocell network. We analyze and compare the two schemes in terms of the system throughput for downlink and energy consumption of home evolved NodeB (HeNB) Tx power according to the number of HeNBs and home user equipment (HUE)'s user traffic density (C). The simulation results show that the FRPC scheme has better performance in terms of system throughput for macro user equipments (MUEs) and energy consumption in low C.

Cooperative diversity using space-time codes offers effective space diversity with low complexity, but the scheme needs the space-time coding process in the relay nodes. We propose a simple cooperative relay scheme that uses space-time coding. In the scheme, the source node transmits the Alamouti coded signal sequences and the sink node receives the signal sequence via the two coordinated relay nodes. At the relay nodes, the operation procedure is just permutation and forwarding of the signal sequence. In the proposed scheme, none of the relay nodes need quadrature detection and space-time coding and the simple relay process offers effective space diversity. Moreover, simulations show the effectiveness of the proposed relay process by some simulations.

This letter proposes an adaptive scheme that switches between cooperative and non-cooperative transmission for multicell downlink systems in Kronecker spatially correlated channels, which exploits statistical channel state information (CSI). Based on the received signal-to-noise ratios (SNRs) and a cooperation metric, we propose a simple base station (BS) association method and then derive low-SNR capacity approximations for both cooperative and non-cooperative systems. Using the results, we provide a low-complexity efficient cooperation switching method to enhance the system capacity. Results show that the proposed method is more efficient than the conventional method to search the switching point.

This letter considers a multiple-channel cognitive radio network (CRN) which can simultaneously sense multiple narrowband channels at a time. Taking the maximization of the CRN's overall throughput as the design objective, the optimization problem of jointly designing sensing time, sensing thresholds and transmission power allocation is formulated under the total power constraint of the CRN and the average interference constraint of the primary network. An iterative algorithm is proposed to obtain the locally optimal values for these parameters. Finally, numerical results show that significant overall throughput gain is achieved through the joint design.

This paper proposes a novel sub-architecture to optimize the data flow of REMUS-II (REconfigurable MUltimedia System 2), a dynamically coarse grain reconfigurable architecture. REMUS-II consists of a µPU (Micro-Processor Unit) and two RPUs (Reconfigurable Processor Unit), which are used to speeds up control-intensive tasks and data-intensive tasks respectively. The parallel computing capability and flexibility of REMUS-II makes itself an excellent candidate to process multimedia applications, which require a large amount of memory accesses. In this paper, we specifically optimize the data flow to deal with those performance-hazard and energy-hungry memory accessing in order to meet the bandwidth requirement of parallel computing. The RPU internal memory could work in multiple modes, like 2D-access mode and transformation mode, according to different multimedia access patterns. This novel design can improve the performance up to 26% compared to traditional on-chip memory. Meanwhile, the block buffer is implemented to optimize the off-chip data flow through reducing off-chip memory accesses, which reducing up to 43% compared to direct DDR access. Based on RTL simulation, REMUS-II can achieve 1080p@30 fps of H.264 High Profile@ Level 4 and High Level MPEG2 at 200 MHz clock frequency. The REMUS-II is implemented into 23.7 mm2 silicon on TSMC 65 nm logic process with a 400 MHz maximum working frequency.

The hierarchical multi-function matrix operation (MFMO) circuit modules are designed using coordinate rotations digital computer (CORDIC) algorithm for realizing the intensive computation of matrix operations. The paper emphasizes that the designed hierarchical MFMO circuit modules can be used to develop a power-efficient software-defined radio (SDR) digital beamformer (DBF). The formulas of the processing time for the scalable MFMO circuit modules implemented in field programmable gate array (FPGA) are derived to allocate the proper logic resources for the hardware reconfiguration. The hierarchical MFMO circuit modules are scalable to the changing number of array branches employed for the SDR DBF to achieve the purpose of power saving. The efficient reuse of the common MFMO circuit modules in the SDR DBF can also lead to energy reduction. Finally, the power dissipation and reconfiguration function in the different modes of the SDR DBF are observed from the experiment results.

Service providers should monitor the quality of experience of a communication service in real time to confirm its status. To do this, we previously proposed a packet-layer model that can be used for monitoring the average video quality of typical Internet protocol television content using parameters derived from transmitted packet headers. However, it is difficult to monitor the video quality per user using the average video quality because video quality depends on the video content. To accurately monitor the video quality per user, a model that can be used for estimating the video quality per video content rather than the average video quality should be developed. Therefore, to take into account the impact of video content on video quality, we propose a model that calculates the difference in video quality between the video quality of the estimation-target video and the average video quality estimated using a packet-layer model. We first conducted extensive subjective quality assessments for different codecs and video sequences. We then model their characteristics based on parameters related to compression and packet loss. Finally, we verify the performance of the proposed model by applying it to unknown data sets different from the training data sets used for developing the model.

This paper proposes a diversity scheme for Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on Radio Frequency (RF) signal processing. Although a 22 MIMO-OFDM system can double the capacity without expanding the occupied frequency bandwidth, we cannot get additional diversity gain using the linear MIMO decomposition method. The proposed method improves the bit error rate (BER) performance by making efficient use of RF signal processing. Computer simulation results show that the proposed scheme gives additional diversity gain.

This paper analyzes a pseudo-differential dynamic comparator with a dynamic pre-amplifier. The transient gain of a dynamic pre-amplifier is derived and applied to equations of the thermal noise and the regeneration time of a comparator. This analysis enhances understanding of the roles of transistor's parameters in pre-amplifier's gain. Based on the calculated gain, two calibration methods are also analyzed. One is calibration of a load capacitance and the other is calibration of a bypass current. The analysis helps designers' estimation for the accuracy of calibration, dead-zone of a comparator with a calibration circuit, and the influence of PVT variation. The analyzed comparator uses 90-nm CMOS technology as an example and each estimation is compared with simulation results.

In deep-submicron era, wire delay is becoming a bottleneck while pursuing higher system clock speed. Several distributed register (DR) architectures are proposed to cope with this problem by keeping most wires local. In this article, we propose the distributed register-file microarchitecture with inter-island delay (DRFM-IID). Though DRFM-IID is also one of the DR-based architectures, it is considered more practical than the previously proposed DRFM, in terms of delay model. With such delay consideration, the synthesis task is inherently more complicated than the one without inter-island delay concern since uncertain interconnect latency is very likely to seriously impact on the whole system performance. Therefore we also develop a performance-driven architectural synthesis framework targeting DRFM-IID. Several factors for evaluating the quality of results, such as number of inter-island transfers, timing-criticality of transfer, and resource utilization balancing, are adopted as the guidance while performing architectural synthesis for better optimization outcomes. The experimental results show that the latency and the number of inter-cluster transfers can be reduced by 26.9% and 37.5% on average; and the latter is commonly regarded as an indicator for power consumption of on-chip communication.

Vehicular ad hoc networks have been attracting the interest of both academic and industrial communities on account of their potential role in Intelligent Transportation Systems (ITS). However, due to vehicle movement and fading in wireless communications, providing a reliable and efficient multi-hop broadcast service in vehicular ad hoc networks is still an open research topic. In this paper, we propose FUZZBR (FUZZy BRoadcast), a fuzzy logic based multi-hop broadcast protocol for information dissemination in vehicular ad hoc networks. FUZZBR has low message overhead since it uses only a subset of neighbor nodes to relay data messages. In the relay node selection, FUZZBR jointly considers multiple metrics of inter-vehicle distance, node mobility and signal strength by employing the fuzzy logic. FUZZBR also uses a lightweight retransmission mechanism to retransmit a packet when a relay fails. We use computer simulations to evaluate the performance of FUZZBR.

Future wireless communication systems aim at very high data rates. As the medium access control (MAC) protocol plays the central role in determining the overall performance of the wireless system, designing a suitable MAC protocol is critical to fully exploit the benefit of high speed transmission that the physical layer (PHY) offers. In the latest 802.11n standard [2], the problem of long overhead has been addressed adequately but the issue of excessive colliding transmissions, especially in congested situation, remains untouched. The procedure of setting the backoff value is the heart of the 802.11 distributed coordination function (DCF) to avoid collision in which each station makes its own decision on how to avoid collision in the next transmission. However, collision avoidance is a problem that can not be solved by a single station. In this paper, we introduce a new MAC protocol called Intelligent Local Avoided Collision (iLAC) that redefines individual rationality in choosing the backoff counter value to avoid a colliding transmission. The distinguishing feature of iLAC is that it fundamentally changes this decision making process from collision avoidance to collaborative collision prevention. As a result, stations can avoid colliding transmissions with much greater precision. Analytical solution confirms the validity of this proposal and simulation results show that the proposed algorithm outperforms the conventional algorithms by a large margin.

We propose a motion detection model, which is suitable for higher speed operation than the video rate, inspired by the neuronal propagation in the hippocampus in the brain. The model detects motion of edges, which are extracted from monocular image sequences, on specified 2D maps without image matching. We introduce gating units into a CA3-CA1 model, where CA3 and CA1 are the names of hippocampal regions. We use the function of gating units to reduce mismatching for applying our model in complicated situations. We also propose a map-division method to achieve accurate detection. We have evaluated the performance of the proposed model by using artificial and real image sequences. The results show that the proposed model can run up to 1.0 ms/frame if using a resolution of 6460 units division of 320240 pixels image. The detection rate of moving edges is achieved about 99% under a complicated situation. We have also verified that the proposed model can achieve accurate detection of approaching objects at high frame rate (>100 fps), which is better than conventional models, provided we can obtain accurate positions of image features and filter out the origins of false positive results in the post-processing.

This paper examines the robust performance of a load torque observer for the position control of a surface-mounted permanent magnet synchronous motor (PMSM) under parameter uncertainties. The load torque observer has been widely employed to compensate for unknown slow-varying disturbances without explicit analysis on the robustness against parameter uncertainties. By using the singular perturbation theory this paper presents an analysis on the robust performance of the load torque observer based on the reduced-order estimator. As the observer poles are placed sufficiently left of the complex plane, the feedforward compensation with estimation can recover nominal system performance without parameter uncertainties and load torque disturbance. An example shows the performance of the load torque observer.

In this paper, a sepic-type single-stage electronic ballast (STSSEB) is proposed, which is derived from the combination of a sepic converter and a half-bridge inverter. The ballast can not only step down input voltage directly but achieve high power factor, reduce voltage stress, improve efficiency and lower cost. Since component stress is reduced significantly, the presented ballast can be applied to high voltage mains. Derivation of the STSSEB is first presented. Then, analysis, design and practical consideration for the STSSEB are discussed. A 347 Vac 60 W prototype has been simulated and implemented. Simulations and experimental results have verified the feasibility of the proposed STSSEB.

We introduce the distributed estimation of a random vector signal in wireless sensor networks that follow coherent multiple access channel model. We adopt the linear minimum mean squared error fusion rule. The problem of interest is to design linear coding matrices for those sensors in the network so as to minimize mean squared error of the estimated vector signal under a total power constraint. We show that the problem can be formulated as a convex optimization problem and we obtain closed form expressions of the coding matrices. Numerical results are used to illustrate the performance of the proposed method.

In this paper, we analyze the best relay selection scheme for the soft-decision-and-forward (SDF) cooperative networks with multiple relays. The term `best relay selection' implies that the relay having the largest end-to-end signal-to-noise ratio is selected to transmit in the second phase transmission. The approximate performances in terms of pairwise error probability (PEP) and bit error rate (BER) are analyzed and compared with the conventional multiple-relay transmission scheme where all the relays participate in the second phase transmission. Using the asymptotics of the Fox's H-function, the diversity orders of the best relay selection and conventional relay scheme for the SDF cooperative networks are derived. It is shown that both have the same full diversity order. The numerical results show that the best relay selection scheme outperforms the conventional one in terms of bit error rate.