Distributed Weighted Data Aggregation Algorithm in End-to-Edge Communication Networks Based on Multi-armed Bandit

As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when learning agents are deployed on the edge side,the data aggregation from the end side to the designated edge devices is an important research topic.Considering the various importance of end devices,this paper studies the weighted data aggregation problem in a single hop end-to-edge communication network.Firstly,to make sure all the end devices with various weights are fairly treated in data aggregation,a distributed end-to-edge cooperative scheme is proposed.Then,to handle the massive contention on the wireless channel caused by end devices,a multi-armed bandit(MAB)algorithm is designed to help the end devices find their most appropriate update rates.Diffe-rent from the traditional data aggregation works,combining the MAB enables our algorithm a higher efficiency in data aggregation.With a theoretical analysis,we show that the efficiency of our algorithm is asymptotically optimal.Comparative experiments with previous works are also conducted to show the strength of our algorithm.

Optimizing Parallel Kinetic Monte Carlo Simulation by Communication Aggregation and Scheduling

Kinetic Monte Carlo(KMC)algorithm has been widely applied for simulation of radiation damage,grain growth and chemical reactions.To simulate at a large temporal and spatial scale,domain decomposition is commonly used to parallelize the KMC algorithm.However,through experimental analysis,we find that the communication overhead is the main bottleneck which affects the overall performance and limits the scalability of parallel KMC algorithm on large-scale clusters.To alleviate the above problems,we present a communication aggregation approach to reduce the total number of messages and eliminate the communication redundancy,and further utilize neighborhood collective operations to optimize the communication scheduling.Experimental results show that the optimized KMC algorithm exhibits better performance and scalability compared with the well-known open-source library—SPPARKS.On 32-node Xeon E5-2680 cluster(total 640 cores),the optimized algorithm reduces the total execution time by 16%,reduces the communication time by 50%on average,and achieves 24 times speedup over the single node(20 cores)execution.

Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

Data Aggregation-based Transmission Method in Ultra-Dense Wireless Networks

As the Internet of Things(IoT)advances,machine-type devices are densely deployed and massive networks such as ultra-dense networks(UDNs)are formed.Various devices attend to the network to transmit data using machine-type communication(MTC),whereby numerous,various are generated.MTC devices generally have resource constraints and use wireless communication.In this kind of network,data aggregation is a key function to provide transmission efficiency.It can reduce the number of transmitted data in the network,and this leads to energy saving and reducing transmission delays.In order to effectively operate data aggregation in UDNs,it is important to select an aggregation point well.The total number of transmitted data may vary,depending on the aggregation point to which the data are delivered.Therefore,in this paper,we propose a novel data aggregation scheme to select the appropriate aggregation point and describe the data transmission method applying the proposed aggregation scheme.In addition,we evaluate the proposed scheme with extensive computer simulations.Better performances in the proposed scheme are achieved compared to the conventional approach.

Investigation of Cross-Correlation Characteristics for Multi-Link Channels in High-Speed Railway Scenarios

This paper investigates the cross-correlation characteristics of large-scale parameters(LSPs) and small-scale fading(SSF) for high-speed railway(HSR) multilink propagation scenarios, based on realistic measurements conducted on Beijing to Tianjin HSR line in China. A long-term evolution-based channel sounding system is utilized in the measurements to obtain the channel data. By applying a proposed time-delay based dynamic partition method, multi-link channel impulse responses are extracted from the raw channel data. Then, the statistical results of LSPs, including shadow fading, K-factor, and root-mean-square delay spread are derived and the cross-correlation coefficients of these LPSs are calculated. Moreover, the SSF spatial correlation and cross-correlation of SSF are analyzed. These results can be used to exploit multi-link channel model and to optimize the next-generation HSR communication system.

MULTI-AGENT AGGREGATION BEHAVIOR ANALYSIS: THE DYNAMIC COMMUNICATION TOPOLOGY

The authors extend the Gazi＇s swarm model with local neighbor rules and the dynamic communication topology, and study its aggregation properties. Results of analysis show that all agents in the models aggregate and eventually form a cohesive cluster of finite size around the swarm center or the appointed point. Finally, simulations are provided to testify some of the results. Models in the paper are more applicable to the reality for the advantage that each agent only needs the partial information of the entire dynamic system when making motion decision.

Impact of Electric Vehicle Aggregator with Communication Time Delay on Stability Regions and Stability Delay Margins in Load Frequency Control System

This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphical method characterizing stability boundary locus is implemented.For a given time delay,the method computes all the stabilizing proportional-integral(PI)controller gains,which constitutes a stability region in the parameter space of PI controller.Secondly,in order to complement the stability regions,a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains.The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder(QPmR)algorithm.

Use of wireless system in healthcare for developing countries

Healthcare is one of the major applications of wireless systems that possess crucial issues. Specifically developing countries require a tow cost and reliable network with efficient protocols. The most challenging concern of Body Area Network （BAN） is heterogeneity, which requires fairness with reliability among all the network nodes. Solutions proposed for these networks either do not provide fair packet transmission or consume high energy and introduce delays. In this paper, we propose a cross layer protocol for healthcare applications meeting the requirements and challenges of the heterogeneous BAN. The protocol is also feasible for developing countries as it can be implemented over existing wireless infrastructure and provides high network reliability with energy efficiency through cooperation and adaptability. Results show that the proposed scheme improves reliability, throughput, Packet Delivery Ratio （PDR）, and energy consumption for scalable and mobile networks over conventional BAN protocols.

Flexible空间扫描统计量在传染病聚集性探测的应用研究

目的探索空间扫描统计量在乙型脑炎聚集性探测及其早期预警中的应用。方法采用Flexible空间扫描统计量对2007年四川省乙脑发病进行空间聚集性分析。结果空间聚集性探测结果显示,在乙脑具有聚集性的时间段内其空间聚集区域存在明显差异。7月共探测到发生乙脑聚集的区县19个,8月共探测到发生乙脑聚集的区县14个。结论 Flexible空间扫描统计量与地理信息系统相结合可有效对乙脑的空间聚集性做出早期预警。

2016—2020年深圳市传染病类突发公共卫生事件流行特征分析

目的分析2016—2020年深圳市传染病类突发公共卫生事件监测结果的流行病学特征。方法在国家突发公共卫生事件报告管理信息系统中导出2016—2020年深圳市突发公共卫生事件数据,按病种、地区和机构类型描述性分析暴发疫情的发生特点,用SPSS 22.0统计分析。结果排除2020年报告的新冠肺炎事件,2016—2020年深圳市共报告233起传染病突发公共卫生事件相关信息,发病6271例,死亡2例,罹患率3.87%,病死率0.03%。其中2018年罹患率最高,为5.20%。聚集性疫情事件164起,占突发公共卫生事件相关信息总数的70.39%,涉及7种传染病,病例数与发生事件起数最多的病种为水痘(100起,3565例)和感染性腹泻(41起,1491例),分别占聚集性疫情事件总数的60.98%和25.00%。78.45%呼吸道传染病聚集性疫情事件发生在小学,58.33%肠道传染病聚集性疫情事件发生在幼儿园,两种传染病事件在幼儿园、小学、初中、高中和大专院校及其他场所的构成比存在显著性差异。结论应采取综合防控策略,针对不同人群中发生风险较高的传染病病种,从降低人群易感性、落实及早报告与停课措施、监测流行株,以及加强培养个人卫生防护习惯等多方面制定防控策略。

Gregariousness in lepidopteran larvae

The gregarious lifestyle of lepidopteran larvae is diverse and shaped by a com-plex interplay of ecological and evolutionary factors.Our review showed that the larval-aggregation behavior has been reported in 23 lepidopteran families,indicating multiple evolution of this behavior.Some larvae live in sibling groups throughout all larval in-stars and even pupation stages,which may result from the kin-selection.In contrast,group fusion may occur among different sibling or foraging groups of larvae and form larger ag-gregates,and the gregariousness of these species might be driven by the group-selection.While group size and foraging patterns vary greatly across species,it is generally associ-ated with improved larval survivorship and accelerated development.However,the advan-tages of group living,such as facilitating feeding activities,adjusting the temperature,and defending natural enemies,may diminish along with development,with strong intraspe-cific competition occurring at later instars,even when food is abundant.Therefore,the group sizes and fission-fusion dynamics of certain gregarious lepidopteran larvae may be a consequence of their cost-benefit balance depending on various biotic and abiotic fac-tors.Trail and aggregation pheromones,silk trails,or body contact contribute to collective movement and group cohesion of gregarious lepidopteran larvae.However,frequent con-tact among group members may cause the horizontal transmission of pathogens and pes-ticides,which may bring an integrated pest management strategy controlling gregarious lepidopteran pests.