Approximate Continuous Aggregation via Time Window Based Compression and Sampling in WSNs

In many applications continuous aggregation of sensed data is usually required. The existing aggregation schemes usually compute every aggregation result in a continuous aggregation either by a complete aggregation procedure or by partial data update at each epoch. To further reduce the energy cost, we propose a sampling-based approach with time window based linear regression for approximate continuous aggregation. We analyze the approximation error of the aggregation results and discuss the determinations of parameters in our approach. Simulation results verify the effectiveness of our approach.

Computation Offloading Algorithms in Mobile Edge Computing System: A Survey

With the rapid development of the internet of things (IoT), the number of devices that can connect to the network has exploded. More computation intensive task appear on mobile terminals, and mobile edge computing has emerged. Computation offloading technology is a key technology in mobile edge computing. This survey reviews the state of the art of computation offloading algorithms. It was classified into three categories: computation offloading algorithms in MEC system with single user, computation offloading algorithms in MEC system with multiple users, computation offloading algorithms in MEC system with enhanced MEC server. For each category of algorithms, the advantages and disadvantages were elaborated, some challenges and unsolved problems were pointed out, and the research prospects were forecasted.

Efficient File Accessing Techniques on Hadoop Distributed File Systems

Hadoop framework emerged at the right moment when traditional tools were powerless in terms of handling big data. Hadoop Distributed File System (HDFS) which serves as a highly fault-tolerance distributed file system in Hadoop, can improve the throughput of data access effectively. It is very suitable for the application of handling large amounts of datasets. However, Hadoop has the disadvantage that the memory usage rate in NameNode is so high when processing large amounts of small files that it has become the limit of the whole system. In this paper, we propose an approach to optimize the performance of HDFS with small files. The basic idea is to merge small files into a large one whose size is suitable for a block. Furthermore, indexes are built to meet the requirements for fast access to all files in HDFS. Preliminary experiment results show that our approach achieves better performance.

Enhancing electromagnetic absorption performance of Molybdate@Carbon by metal ion substitution

Transition metal molybdate(RMoO4)has been extensively studied in optics,electricity and catalysis due to its low cost and multivalent Mo atoms,while its poor electrical conductivity limits its application in electromagnetic wave absorption(EMA).Compounding molybdate with conductive materials is an effective way to improve its electrical conductivity.In this work,a homogeneous coating on the molybdate surface was achieved by utilizing a pyrrole oxidation polymerization mechanism,and then stabilized composites of Molybdate@Carbon(RMoO4@C)were obtained by high-temperature pyrolysis.The EMA properties of the nanocomposites were tuned by substituting the species of transition metal elements(RMoO_(4)@C,R=Fe,Co,Cu).Among them,Fe_(2)(MoO_(4))_(3)@C has a minimum reflection loss of−60.62 dB at an ultra-low thickness of 1.7 mm,and the effective absorption bandwidth(EAB)can reach 4.75 GHz at 3.00 mm.This work expands the range of applications for molybdate and provides a new material basis for building high-performance EMA materials.

An Efficient EH-WSN Energy Management Mechanism

An Energy-Harvesting Wireless Sensor Network （EH-WSN） depends on harvesting energy from the environment to prolong network lifetime. Subjected to limited energy in complex environments, an EH-WSN encounters difficulty when applied to real environments as the network efficiency is reduced. Existing EH-WSN studies are usually conducted in assumed conditions in which nodes are synchronized and the energy profile is knowable or calculable. In real environments, nodes may lose their synchronization due to lack of energy. Furthermore, energy harvesting is significantly affected by multiple factors, whereas the ideal hypothesis is difficult to achieve in reality. In this paper, we introduce a general Intermittent Energy-Aware （lEA） EH-WSN platform. For the first time, we adopted a double-stage capacitor structure to ensure node synchronization in situations without energy harvesting, and we used an integrator to achieve ultra-low power measurement. With regard to hardware and software, we provided an optimized energy management mechanism for intermittent functioning. This paper describes the overall design of the lEA platform, and elaborates the energy management mechanism from the aspects of energy management, energy measurement, and energy prediction. In addition, we achieved node synchronization in different time and energy environments, measured the energy in reality, and proposed the light weight energy calculation method based on measured solar energy. In real environments, experiments are performed to verify the high performance of lEA in terms of validity and reliability. The lEA platform is shown to have ultra-low power consumption and high accuracy for energy measurement and prediction.

Microporous polythiophene(MPT)-guest complex derived magnetic metal sulfides/carbon nanocomposites for broadband electromagnetic wave absorption

Electrical and magnetic properties are two crucial factors for the designing of broadband electromagnetic wave absorption(EWA)materials.In this work,we synthesized various magnetic metal sulfides/carbon(M_(x)S_(y)/C)nanocomposites from the precursor complex of metal in microporous polythiophene(MPT),and systematically investigated their EWA properties and mechanism.The characterization results indicate that M_(x)S_(y) were determined to be Fe_(7)S_(8)/C,Co_(9)S_(8)/C and Ni_(4)S_(3)/C,respectively.It is observed that M_(x)S_(y)/C nanocomposites exhibit remarkable EWA performances,where the maximal absorption gets to-51.3 dB,and efficient absorption can be realized in 10.32-18 GHz(7.68 GHz),which is superior to most reported magnetic carbonaceous EWA composites.Beside,the efficient absorption can be tuned to cover Ku band X band,demonstrating their great potential in practical applications.Improved conductance loss,obvious polarization relaxation,and apparent eddy current loss are deemed to make the predominant contributions to the high-performance EWA.This research opens up the exploration of novel nanocomposite coupling dielectric loss and magnetic loss using MPT-metal complex precursor for EWA applications.

Carbon nanofilm stabilized twisty V_(2)O_(3)nanorods with enhanced multiple polarization behavior for electromagnetic wave absorption application

Vanadium(V)oxides exhibit low electrical conductivity and poor polarization properties,especially in that V_(2)O_(3)has low stability and is easily oxidized to higher valence V oxides.To solve this problem,we herein provide a two-step strategy for the synthesis of carbon nanofilm stabilized twisty V_(2)O_(3)nanorods(V_(2)O_(3)@C),including a hydrothermal reaction and a controlled pyrolysis process.Conductivity tests and electron-spin resonance(ESR)spectra indicate that the coating of carbon nanofilm not only enhances the electrical conductivity but also generates abundant defects.The electromagnetic waves absorption(EMA)results suggest that V_(2)O_(3)@C exhibits excellent EMA performance at ultra-low thickness,where the effective absorption bandwidth gets to 7.21 GHz at 1.7 mm and the maximal absorption reaches–56 d B.Enhanced conductivity loss and improved multiple polarization relaxation were used to illustrate the absorbing mechanism of V_(2)O_(3)@C.This work provides new insights into the design of advanced nanocomposites for EMA applications.