Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

An Emergency Plan Selection Method for Emergency Latency

Drawing upon a characteristic analysis of the latency period in emergencies,this paper proposes an emergency plan selection method based on interval language variables and information entropy to address the challenge of acquiring critical information during this crucial stage.Initially,decision-makers employ interval language variables to express the preference information regarding emergency plans,while also introducing an enhanced information entropy theory to derive the weight coefficients of key indicators.Subsequently,the weighted arithmetic average operator of interval language is applied twice to aggregate the preference information alongside the relative importance of decision-makers and the weight coefficients of key indicators.Finally,the ranking coefficients of each emergency plan are sorted to determine the optimal scheme.The feasibility and effectiveness of this method are demonstrated through a case study involving the selection of an emergency plan for a flood disaster in a specific location.

Latency Minimization Using an Adaptive Load Balancing Technique in Microservices Applications

Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex systems.Microservices Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed independently.This methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,etc.and the advantages;Microservices bring some challenges too.Multiple microservices need to be invoked one by one as a chain.In most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s request.It results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of requests.The communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting time.Experiments were done for both interactive as well as non interactive workloads to test the effectiveness of the solution.The approach has been proved to be very effective in reducing latency in the case of long service chains.

Latency arbitrage and the synchronized placement of orders

We argue that owing to traders’inability to fully express their preferences over the execution times of their orders,contemporary stock market designs are prone to latency arbitrage.In turn,we propose a new order type,which allows traders to specify the time at which their orders are executed after reaching the exchange.Using recent latency data,we demonstrate that the order type proposed here allows traders to synchronize order executions across different exchanges,such that high-frequency traders,even if they operate at the speed of light,can no-longer engage in latency arbitrage.

Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic,native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered,or lightweight solutions adapted to ultrareliable low-latency communications(URLLC)but whose security properties remain under discussion.Although different 5G network slices may have different requirements,in general,both visions seem to fall short at provisioning secure URLLC in the future.In this work we address this challenge,by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks.We categorize those new security components into different groups according to their purpose and deployment scope.We propose to analyze them in the context of existing 5G architectures using two different approaches.First,using model checking techniques,we will evaluate the probability of an attacker to be successful against each security solution.Second,using analytical models,we will analyze the impact of these security mechanisms in terms of delay,throughput consumption,and reliability.Finally,we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture.Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced,dedicated non-native mechanisms could only guarantee secure URLLC with a probability of∼55%.

Optimal edge-cloud collaboration based strategies for minimizing valid latency of railway environment monitoring system

Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.

Mobile Edge Computing and Field Trial Results for 5G Low Latency Scenario

Through enabling the IT and cloud computation capacities at Radio Access Network(RAN),Mobile Edge Computing(MEC) makes it possible to deploy and provide services locally.Therefore,MEC becomes the potential technology to satisfy the requirements of 5G network to a certain extent,due to its functions of services localization,local breakout,caching,computation offloading,network context information exposure,etc.Especially,MEC can decrease the end-to-end latency dramatically through service localization and caching,which is key requirement of 5G low latency scenario.However,the performance of MEC still needs to be evaluated and verified for future deployment.Thus,the concept of MEC is introduced into5 G architecture and analyzed for different 5G scenarios in this paper.Secondly,the evaluation of MEC performance is conducted and analyzed in detail,especially for network end-to-end latency.In addition,some challenges of the MEC are also discussed for future deployment.

Hierarchical Content Caching in Fog Radio Access Networks:Ergodic Rate and Transmit Latency

In order to alleviate capacity constraints on the fronthaul and decrease the transmit latency, a hierarchical content caching paradigm is applied in the fog radio access networks(F-RANs). In particular, a specific cluster of remote radio heads is formed through a common centralized cloud at the baseband unit pool, while the local content is directly delivered at fog access points with edge cache and distributed radio signal processing capability. Focusing on a downlink F-RAN, the explicit expressions of ergodic rate for the hierarchical paradigm is derived. Meanwhile, both the waiting delay and latency ratio for users requiring a single content are exploited. According to the evaluation results of ergodic rate on waiting delay, the transmit latency can be effectively reduced through improving the capacity of both fronthaul and radio access links. Moreover, to fully explore the potential of hierarchical content caching, the transmit latency for users requiring multiple content objects is optimized as well in three content transmission cases with different radio access links. The simulation results verify the accuracy of the analysis, further show the latency decreases significantly due to the hierarchical paradigm.

Subtle role of latency for information diffusion in online social networks

Information diffusion in online social networks is induced by the event of forwarding information for users, and latency exists widely in user spreading behaviors. Little work has been done to reveal the effect of latency on the diffusion process. In this paper, we propose a propagation model in which nodes may suspend their spreading actions for a waiting period of stochastic length. These latent nodes may recover their activity again. Meanwhile, the mechanism of forwarding information is also introduced into the diffusion model. Mean-field analysis and numerical simulations indicate that our model has three nontrivial results. First, the spreading threshold does not correlate with latency in neither homogeneous nor heterogeneous networks, but depends on the spreading and refractory parameter. Furthermore, latency affects the diffusion process and changes the infection scale. A large or small latency parameter leads to a larger final diffusion extent, but the intrinsic dynamics is different. Large latency implies forwarding information rapidly, while small latency prevents nodes from dropping out of interactions. In addition, the betweenness is a better descriptor to identify influential nodes in the model with latency, compared with the coreness and degree. These results are helpful in understanding some collective phenomena of the diffusion process and taking measures to restrain a rumor in social networks.

Specificity and sensitivity of visual evoked potentials P100 latency to different events exercise

Visual evoked potentials (VEPs) are a series of signals about visual occipital cortex in response to visual stimuli and can be used as one of ob-jective non-invasive neuro-physiological pa-rameters to reflect the visual organs and central visual pathway’s functional integrity. Previous studies have shown that acute and chronic ex-ercise could affect VEPs independent from body temperature and other physiological parameters. VEPs may well be used as neuro-physiological criteria in defining the performances of the ath-letes. Different sports training have different effects on VEPs, but the results are not consis-tent. P100 latency is the representative compo-nent of VEPs and it is of high, steady amplitude and of slight intra- and inter-individual variabil-ity so that the index is most commonly used. The purpose of this study was to investigate the specificity and sensitivity of P100 latency to dif-ferent physical activities. The neural electricity device of NDI-200 was used to measure the pattern reversal VEPs of all subjects, including the values of the resting state before and after different events exercise. Different events exer-cise contained an aerobic cycloergometric ex-ercise (7 subjects were conducted to a Bruce Graded Exercise Test on the Monark Ergomedic 839E cycloergometer, THR (target heart rate) = 85% HRmax, 3 times/week, about 10 minutes once time, 6 weeks), tennis training (16 volun-teers, 2 hours/day, 3 days/week, 8 weeks), aerobic Latin exercise (7 subjects, 1 hour/day, 3 days/week, 6 weeks) and the Baduanjin of Health Qigong training (6 subjects, 1 hour/day, 3 days/week, 6 weeks). The VEPs recordings of the control groups obtained synchronized with the experimental groups. SPSS 11.5 for win-dows was used for statistical analysis. A level of P﹤0.05 was accepted as statistically significant. The VEPs P100 latency of post-exercise of all experimental groups except Baduanjin group became shorter significantly compared with those of pre-exercise (P﹤0.05). No significant difference was found between pre-and post- exercise for the control groups. This study showed that exercise could shorten the P100 la-tency significantly. Moreover, it also indicated that VEPs were sensitive to exercise to a certain extent. We concluded that VEPs might well be used as neuro-physiological criteria in defining the performances of the athletes. It was found that the VEPs P100 latency became shorter after most training programs;furthermore, it demon-strated that P100 latency of VEPs had little specificity to different events.

The 5-HT2c receptor gene Cys23Ser polymorphism influences the intravaginal ejaculation latency time in Dutch Caucasian men with lifelong premature ejaculation

It has been postulated that the persistent short intravaginal ejaculation latency time （IELT） of men with lifelong premature ejaculation （LPE） is related to 5-hydroxytryptamine （HT）2c receptor functioning. The aim of this study was to investigate the relationship of Cys23Ser 5-HT2c receptor gene polymorphism and the duration of IELT in men with LPE. Therefore, a prospective study was conducted in 64 Dutch Caucasian men with LPE. Baseline IELT during coitus was assessed by stopwatch over a 1-month period. All men were genotyped for Cys23Ser 5-HT2c receptor gene polymorphism. Allele frequencies and genotypes of Cys and Ser variants of 5-HT2c receptor gene polymorphism were determined. Association between Cys/Cys and Ser/Ser genotypes and the natural logarithm of the IELT in men with LPE were.investigated. As a result, the geometric mean, median and natural mean IELT were 25.2, 27.0, 33.9s, respectively. Of all men, 20.0%, 10.8%, 23.1% and 41.5% ejaculated within 10, 10-20, 20-30 and 30-60s after vaginal penetration. Of the 64 men, the Cys/Cys and Ser/Ser genotype frequency for the Cys23Ser polymorphism of the 5-HT2c receptor gene was 81% and 19%, respectively. The geometric mean IELT of the wildtypes （Cys/Cys） is significantly lower （22.6s; 95% CI 18.3-27.8s） than in male homozygous mutants （Ser/Ser） （40.4s; 95% CI 20.3-80.4s） （P = 0.03）. It is concluded that Cys23Ser 5-HT2c receptor gene polymorphism is associated with the IELT in men with LPE. Men with Cys/Cys genotype have shorter IELTs than men with Ser/Ser genotypes.

A New Scheduling Algorithm for Reducing Data Aggregation Latency in Wireless Sensor Networks

Existing works on data aggregation in wireless sensor networks (WSNs) usually use a single channel which results in a long latency due to high interference, especially in high-density networks. Therefore, data aggre- gation is a fundamental yet time-consuming task in WSNs. We present an improved algorithm to reduce data aggregation latency. Our algorithm has a latency bound of 16R + Δ – 11, where Δ is the maximum degree and R is the network radius. We prove that our algorithm has smaller latency than the algorithm in [1]. The simulation results show that our algorithm has much better performance in practice than previous works.

Data Aggregation Scheduling with Guaranteed Lifetime and Efficient Latency in Wireless Sensor Networks

In scenarios of real-time data collection of long-term deployed Wireless Sensor Networks （WSNs）, low-latency data collection with long net- work lifetime becomes a key issue. In this paper, we present a data aggregation scheduling with guaran- teed lifetime and efficient latency in WSNs. We first Construct a Guaranteed Lifetime Mininmm Ra- dius Data Aggregation Tree （GLMRDAT） which is conducive to reduce scheduling latency while pro- viding a guaranteed network lifetime, and then de-sign a Greedy Scheduling algorithM （GSM） based on finding the nmzximum independent set in conflict graph to schedule he transmission of nodes in the aggregation tree. Finally, simulations show that our proposed approach not only outperfonm the state-of-the-art solutions in terms of schedule latency, but also provides longer and guaranteed network lifetilre.

The determination of the link with the smallest end-to-end network latency in ethernet architecture

Ethernet fundamental and its data transmission model are introduced in brief and end-to-end network latency was analyzed in this paper. On the premise of not considering transmission quality and transmission cost, latency was the function of the rest of network resource parameter (NRP). The relation between the number of nodes and that of end-to-end links was presented. In ethernet architecture, the algorithm to determine the link with the smallest latency is a polynomial issue when the number of network nodes is limited, so it can be solved by way of polynomial equations. Latency measuring is the key issue to determine the link with the smallest network latency. 3-node brigade (regiment) level network centric warfare (NCW) demonstration platform was studied and the latency between the detectors and weapon control stations was taken as an example. The algorithm of end-to-end network latency and link information in NCW was presented. The algorithm program based on Server/Client architecture was developed. The data transmission optimal link is one whose end-to-end latency is the smallest. This paper solves the key issue to determine the link whose end-to-end latency is the smallest in ethernet architecture. The study can be widely applied to determine the optimal link which is in the complex network environment of multiple service provision points.

Method for Latency Measurement of Visual Feedback-Based Master–Slave Minimally Invasive Surgical Robot

To measure the latency between human motion stimulation and stereo image display response in a visual feedback-based minimally invasive surgical(MIS) robotic system,a method was proposed by comparing the orientations of input and output events through image-processing technology. This method used a black bar to keep pace with the measured joint rotating at a number of speeds. During tests,an external camera was placed in front of the apparatus with a proper visual field,so that it can simultaneously view orientations of both bars fixed on the corresponding joints. After quantitatively analyzing the accuracy of the proposed measurement method,the method was applied to a visual feedback-based master–slave robotic system with two-degrees-of-freedom. Experimental results show that the latency of the overall system was approximately 250 ms,and the opposite clearance of the measured joint was in the range of 1.7°–1.9°.

New Latency Model for Dynamic Frequency Scaling on Network-on-Chip

Modulating both the clock frequency and supply voltage of the network-on-chip （NoC） during runtime can reduce the power consumption and heat flux, but will lead to the increase of the latency of NoC. It is necessary to find a tradeoff between power consumption and communication latency. So we propose an analytical latency model which can show us the relationship of them. The proposed model to analyze latency is based on the M/G/1 queuing model, which is suitable for dynamic frequency scaling. The experiment results show that the accuracy of this model is more than 90%.

End-to-End Latency Evaluation of the Sat5G Network Based on Stochastic Network Calculus

Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time,reliability and capacity is an inherent feature of satellite-5G integrated network(Sat5G).However,there is still a lack of theoretical characterization of whether the network can satisfy the end-to-end transmission performance for latency-sensitive service.To this end,we build a tandem model considering the connection relationship between the various components in Sat5G network architecture,and give an end-to-end latency calculation function based on this model.By introducing stochastic network calculus,we derive the relationship between the end-to-end latency bound and the violation probability considering the traffic characteristics of multimedia.Numerical results demonstrate the impact of different burst states and different service rates on this relationship,which means the higher the burst of arrival traffic and the higher the average rate of arrival traffic,the greater the probability of end-to-end latency violation.The results will provide valuable guidelines for the traffic control and cache management in Sat5G network.

Design of Latency-Aware IoT Modules in Heterogeneous Fog-Cloud Computing Networks

The modern paradigm of the Internet of Things(IoT)has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud computing.However,such applications cannot meet strict quality of service(QoS)requirements.The large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big data.Generally,cloud-centric IoT application deployment involves different modules running on terminal devices and cloud servers.Fog devices with different computing capabilities must process the data generated by the end device,so deploying latency-sensitive applications in a heterogeneous fog computing environment is a difficult task.In addition,when there is an inconsistent connection delay between the fog and the terminal device,the deployment of such applications becomes more complicated.In this article,we propose an algorithm that can effectively place application modules on network nodes while considering connection delay,processing power,and sensing data volume.Compared with traditional cloud computing deployment,we conducted simulations in iFogSim to confirm the effectiveness of the algorithm.The simulation results verify the effectiveness of the proposed algorithm in terms of end-to-end delay and network consumption.Therein,latency and execution time is insensitive to the number of sensors.

Benefits of combination of electroencephalography, short latency somatosensory evoked potentials, and transcranial Doppler techniques for confirming brain death

Objective: Optimization of combining electroencephalography (EEG), short latency somatosensory evoked potentials (SLSEP) and transcranial Doppler (TCD) techniques to diagnose brain death. Methods: One hundred and eleven patients (69 males, 42 females) from the major hospitals of Zhejiang Province were examined with portable EEG, SLSEP and TCD devices. Re-examinations occurred ≤12 h later. Results: The first examination revealed that the combination of SLSEP and EEG led to more sensitive diagnoses than the combination of SLSEP and TCD. Re-examination confirmed this and also revealed that the combination of TCD and EEG was the most sensitive. Conclusion: The results show that using multiple techniques to diagnose brain death is superior to using single method, and that the combination of SLSEP and EEG is better than other combinations.

Investigating and Modelling of Task Offloading Latency in Edge-Cloud Environment

Recently,the number of Internet of Things(IoT)devices connected to the Internet has increased dramatically as well as the data produced by these devices.This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing.However,different service architecture and offloading strategies have a different impact on the service time performance of IoT applications.Therefore,this paper presents an Edge-Cloud system architecture that supports scheduling offloading tasks of IoT applications in order to minimize the enormous amount of transmitting data in the network.Also,it introduces the offloading latency models to investigate the delay of different offloading scenarios/schemes and explores the effect of computational and communication demand on each one.A series of experiments conducted on an EdgeCloudSim show that different offloading decisions within the Edge-Cloud system can lead to various service times due to the computational resources and communications types.Finally,this paper presents a comprehensive review of the current state-of-the-art research on task offloading issues in the Edge-Cloud environment.