Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

Finite element（FE） is a powerful tool and has been applied by investigators to real-time hybrid simulations（RTHSs）. This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time（TET） decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method（CDM）, the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ（λ = 4） method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

A Novel Time-aware Frame Adjustment Strategy for RFID Anti-collision

Recently,object identification with radio frequency identification(RFID)technology is becoming increasingly popular.Identification time is a key performance metric to evaluate the RFID system.The present paper analyzes the deficiencies of the state-of-the-arts algorithms and proposes a novel sub-frame-based algorithm with adaptive frame breaking policy to lower the tag identification time for EPC global C1 Gen2 UHF RFID standard.Through the observation of slot statistics in a sub-frame,the reader estimates the tag quantity and efficiently calculates an optimal frame size to fit the unread tags.Only when the expected average identification time in the calculated frame size is less than that in the previous frame size,the reader starts the new frame.Moreover,the estimation of the proposed algorithm is implemented by the look-up tables,which allows dramatically reduction in the computational complexity.Simulation results show noticeable throughput and time efficiency improvements of the proposed solution over the existing approaches.

A High Spectral Efficiency System Enabled by Free Window with Full Duplex

This paper studies the capacity issues of a wireless communication system that implements single channel full duplex(SCFD) communication at the base station(BS), thereby the mobile stations share the channel via time division duplex(TDD). The system makes use of the same setup as has been used in previous studies of SCFD, but unlike these previous systems, the new system uses water-filling to maximize the spectral efficiency of the uplink channel. The concept of a free window is introduced to the duplex model for measuring, intuitively, the effective bandwidth of the bi-directional communication. The capacity gain is calculated and numerical results show the advantage of the proposed system over that of conventional TDD.

Space- and time-efficient approach for virtual machine provisioning

As a new promising paradigm, cloud computing can make good use of economics of scale and elastically deliver almost any IT related services on demand. Nevertheless, one of the key problems remaining in cloud computing is related to virtual machine images, which require a great amount of space/time to reposit/provision, especially with diverse requests from thousands of users simultaneously. In this paper, by using the splitting and eliminating redundant data techniques, a space and time efficient approach for virtual machines is proposed. The experiments demonstrate that, compared with existing solutions, our approach can conserve more disk space and speed up the provisioning of virtual machines.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Energy Efficient Unequal Fault Tolerance Clustering Approach

For achieving Energy-Efficiency in wireless sensor networks(WSNs),different schemes have been proposed which focuses only on reducing the energy consumption.A shortest path determines for the Base Station(BS),but fault tolerance and energy balancing gives equal importance for improving the network lifetime.For saving energy in WSNs,clustering is considered as one of the effective methods for Wireless Sensor Networks.Because of the excessive overload,more energy consumed by cluster heads(CHs)in a cluster based WSN to receive and aggregate the information from member sensor nodes and it leads to failure.For increasing the WSNs’lifetime,the CHs selection has played a key role in energy consumption for sensor nodes.An Energy Efficient Unequal Fault Tolerant Clustering Approach(EEUFTC)is proposed for reducing the energy utilization through the intelligent methods like Particle Swarm Optimization(PSO).In this approach,an optimal Master Cluster Head(MCH)-Master data Aggregator(MDA),selection method is proposed which uses the fitness values and they evaluate based on the PSO for two optimal nodes in each cluster to act as Master Data Aggregator(MDA),and Master Cluster Head.The data from the cluster members collected by the chosen MCH exclusively and the MDA is used for collected data reception from MCH transmits to the BS.Thus,the MCH overhead reduces.During the heavy communication of data,overhead controls using the scheduling of Energy-Efficient Time Division Multiple Access(EE-TDMA).To describe the proposed method superiority based on various performance metrics,simulation and results are compared to the existing methods.

Statistics and Analysis on Reliability of HVDC Transmission Systems of SGCC

Reliability level of HVDC power transmission systems becomes an important factor impacting the entire power grid.The author analyzes the reliability of HVDC power transmission systems owned by SGCC since 2003 in respect of forced outage times,forced energy unavailability,scheduled energy unavailability and energy utilization eff iciency.The results show that the reliability level of HVDC power transmission systems owned by SGCC is improving.By analyzing different reliability indices of HVDC power transmission system,the maximum asset benef its of power grid can be achieved through building a scientif ic and reasonable reliability evaluation system.

Minimum Time Extrema Estimation for Large-Scale Radio-Frequency Identification Systems

We consider the extrema estimation problem in large-scale radio-frequency identification(RFID)systems,where there are thousands of tags and each tag contains a finite value.The objective is to design an extrema estimation protocol with the minimum execution time.Because the standard binary search protocol wastes much time due to inter-frame overhead,we propose a parameterized protocol and treat the number of slots in a frame as an unknown parameter.We formulate the problem and show how to find the best parameter to minimize the worst-case execution time.Finally,we propose two rules to further reduce the execution time.The first is to find and remove redundant frames.The second is to concatenate a frame from minimum value estimation with a frame from maximum value estimation to reduce the total number of frames.Simulations show that,in a typical scenario,the proposed protocol reduces execution time by 79%compared with the standard binary search protocol.

A position-sensitive detector with lithium glass and MaPMT

A position-sensitive detector is designed for neutron detection. It uses a single continuous screen of a self-made lithium glass scintillator, rather than discrete crystal implementations, coupling with a multi-anode PMT （MaPMT）. The scintillator is fast and efficient; with a decay time of 34 ns and thermal neutron detection efficiency of around 95.8% for the 3 mm thick screen, and its light yield is around 5670 photons per neutron and 3768 photons per MeV γ rays deposition. The spatial resolution is around 1.6 mm （FWHM） with the energy resolution around 34.7% by using α （5.2 MeV） rays test.