Minimum Response Time Research Articles

Hybrid load balance based on genetic algorithm in cloud environment

Load balancing is an efficient mechanism to distribute loads over cloud resources in a way that maximizes resource utilization and minimizes response time. Metaheuristic techniques are powerful techniques for solving the load balancing problems. However, these techniques suffer from efficiency degradation in large scale problems. This paper proposes three main contributions to solve this load balancing problem. First, it proposes a heterogeneous initialized load balancing (HILB) algorithm to perform a good task scheduling process that improves the makespan in the case of homogeneous or heterogeneous resources and provides a direction to reach optimal load deviation. Second, it proposes a hybrid load balance based on genetic algorithm (HLBGA) as a combination of HILB and genetic algorithm (GA). Third, a newly formulated fitness function that minimizes the load deviation is used for GA. The simulation of the proposed algorithm is implemented in the cases of homogeneous and heterogeneous resources in cloud resources. The simulation results show that the proposed hybrid algorithm outperforms other competitor algorithms in terms of makespan, resource utilization, and load deviation.

Traffic-aware adaptive server load balancing for software defined networks

Servers in data center networks handle heterogenous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TA-ASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.

Internet of Things-Based Energy Efficiency Optimization Model in Fog Smart Cities

In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.

Police Presence, Rapid Response Rates, and Crime Prevention

AbstractThis paper estimates the impact of police presence on crime using a unique database that tracks the exact location of Dallas Police Department patrol cars throughout 2009. To address the concern that officer location is often driven by crime, my instrument exploits police responses to calls outside their allocated coverage beat. This variable provides a plausible shift in police presence within the abandoned beat that is driven by the police goal of minimizing response times. I find that a 10% decrease in police presence at that location results in a 7% increase in crime. This result sheds light on the black box of policing and crime and suggests that routine changes in police patrol can have a significant impact on criminal behavior.

101 Measurement of Tapping During the Interstimulus Interval as a Validation Metric for the 3-Minute Psychomotor Vigilance Test

Abstract Introduction The Psychomotor Vigilance Test is a well-validated measure of sustained attention used to assess daytime alertness in sleep research studies.1 It is commonly used in a variety of research settings due to its high sensitivity to sleep loss and absence of learning effects,2 making it an ideal tool to assess objective alertness. As some types of sleep research transition out of controlled laboratory environments, tools like the PVT require modification to maximize their reliability. The validation of the 3-minute version (PVT-B) against the 10-minute PVT is an example of this modification.3 However, considerable work is needed to improve trust in the utility of the PVT-B in and outside of traditional laboratory settings. Methods We carefully analyzed data from a mobile-based version of the PVT-B, noting responses that occurred during the interstimulus interval which were termed “wrong taps.” Wrong taps indicated that participants were not performing the task as instructed. In some cases, wrong taps occurred across multiple trials of the same PVT block, indicative of participants repeatedly tapping the screen throughout the task to minimize response times. A comprehensive examination of wrong taps was carried out in order to identify instances where this pattern emerged. Results A total of 1,338,538 PVT-B trials from 7,028 participants were examined to determine the number of wrong taps present across all trials. While 91.7% of PVT-B trials were free of wrong taps, 8.3% of PVT-B trials contained 1 or more wrong taps and 5.2% contained 2 or more wrong taps. It appears that a maximum of one wrong tap per trial is acceptable and trials containing 2 or more should be excluded to maximize PVT data quality. Conclusion Utilizing a metric like wrong taps can help identify individuals taking the PVT-B who are tapping the screen multiple times prior to stimulus display. Closely examining this metric can help to ensure the validity of PVT-B administrations. Two possible uses of the metric could be to provide feedback during training trials and to remove trials where this strategy was employed. Support (if any) This analysis was supported by the VA San Diego Healthcare System Research Service.

Software Defined Network: Load Balancing Algorithm Design and Analysis

Software Defined Network (SDN) cut down the monopolies of producing network devices and their applications. It allows the use of an omniscient controller that manages the overall network and promises for simplifying the configuration and management burden of the traditional Internet Protocol (IP) network. The use of hardware load balancer is a critical issue in conventional IP networks that creates many negative impacts such as the cost affordability, features customization, and availability. Also, the existing load balancing algorithm does not consider the flow size generated by the client nodes. Further, flows are not classified based on the threshold value of the dynamic flow size. The paper proposes to compare the performance of two load balancing algorithms such as flow-based load balancing algorithm and traffic pattern-based load balancing algorithm with distributed controllers' architecture. The result shows that the flow-based load balancing algorithm minimizes response time by 94%, enhances transaction rate by 14% and Traffic pattern-based load balancing algorithm has improved availability by 2.69%.

Design and fabrication of quick responsive and highly sensitive LPG sensor using ZnO/SnO2 heterostructured film

Highly efficient LPG sensor working at room temperature was developed using a simple and cost-effective route. For this purpose, ZnO/SnO2 heterostructure was synthesized using the hydrothermal route and thin films of the material were prepared. X-ray Diffraction revealed all the crystal parameters including grain size, texture coefficient, dislocation densities, surface area which are necessary for a sensor. Also, particle size, zeta potential, and conductivity were observed using nanozetasizer. Heterojunctions at the surface of the film were viewed by Scanning electron microscopy. An optical band-gap of ∼3.85 eV was measured using UV–vis absorption spectrum. Further, the film was used as room ambient sensor for different concentrations of LPG. Among them, the best sensor response and sensitivity of 276.51 and 3.78 respectively were obtained for 2.0 vol% of LPG whereas minimum response and recovery time of 10 s and 15 s were obtained for 0.5 vol% of LPG.

Cooperative agents-based approach for workflow scheduling on fog-cloud computing

Connected objects in the Internet of Things (IoT) domain are widespread everywhere. They interact with each other and cooperate with their neighbors to achieve a common goal. Most of these objects generate a huge amount of data, often requiring a process under strict time constraints. Being motivated by the question of optimizing the execution time of these IoT tasks, we remain aware of the sensitivity to latency and the volume of data generated. In this article, we propose a hybrid Cloud-Fog multi-agent approach to schedule a set of dependent IoT tasks modeled as a workflow. The major advantage of our approach is to allow to model IoT workflow planning as a multi-objetif optimization problem in order to create a compromise planning solution in terms of response time, cost and makespan. In addition to taking into account data communications between workflow tasks, during the planning process, our approach has two other advantages: (1) maximizing the use of Fog Computing in order to minimize response time, and (2) the use of elastic cloud computing resources at minimum cost. The implementation of the MAS-GA (Multi-Agent System based Genetic Algorithm), which we have proposed in this context; the series of experiments carried out on different corpora, as well as the analysis of the found results confirm the feasibility of our approach and its performance in terms of cost which represents an average gain of 21.38% compared to Fog and 25.49% compared to Cloud, makespan which represents a gain of 14.13% compared to Fog and a slight increase of 5.24% compared to Cloud and in response time which represents an average gain of 46.66% compared to Cloud with a slight increase of 6.66% compared to Fog, while strengthening the collaboration between Fog computing and Cloud computing.

Light-induced pyroelectric property of self-powered photodetectors based on all-inorganic perovskite quantum dots

All-inorganic cesium lead bromine (CsPbBr3) perovskites quantum dots (QDs) are one of the most photoelectric materials due to their high absorption coefficient, pronounced quantum-size effect, tunable optical property. Here, a self-powered PD based on all-inorganic CsPbBr3 perovskites QDs is fabricated and demonstrated. The light-induced pyroelectric effect is utilized to modulate the optoelectronic processes without the external power supply. The working mechanism of the PD is carefully investigated upon 532 nm laser illumination and the minimum recognizable response time of the self-powered PD is 1.5 μs, which are faster than those of most previously reported wurtzite nanostructure PDs. Meanwhile, the frequency and temperature independence of the self-powered PD are experimented and summarized. The self-powered PD with high performance is expected to have extensive applications in solar cell, energy harvesting, resistive random access memory.

A Strategic Review on Gallium Oxide Based Deep‐Ultraviolet Photodetectors: Recent Progress and Future Prospects

AbstractWith the use of UV‐C radiation sterilizers on the rise in the wake of the recent pandemic, it has become imperative to have health safety systems in place to curb the ill‐effects on humans. This requires detection systems with suitable spectral response to the “invisible to the naked eye” radiation leaks with utmost sensitivity and swiftness. State of the art deep‐UV photodetectors based on the wide bandgap material gallium oxide have achieved responsivities up to few hundred A W−1 while the minimum response time achieved is few hundred nanoseconds. However, due to the trade‐off between these two key parameters, the ultimate performance of the photodetectors remains inadequate. The focus here is to give a thorough review of the gallium oxide based photodetectors, their recent progress and future prospects. This review highlights the fundamental physics and the key parameters such as dark current, responsivity, and response time with their dependence on the material properties. Exploration of the reasons behind current scenario in the field of gallium oxide is comprehensively and critically analyzed. The key challenges which limit device performance and inhibit the realization of real‐world practical detectors are also described. The lacunae currently plaguing the field is also discussed with possible remedial solutions.

Exploitation whale optimization based optimal offloading approach and topology optimization in a mobile ad hoc cloud environment

Widespread availability of network technologies, mobile user request is increased day by day. The larger amount of energy utilization and resource sufficiency of cloud computing is to create the maximum capacity of exploration and exploitation as troublesome. In this paper, we proposed the formation of mobile user behavior based topology and its optimization. During the offloading process, the minimization of response time and the energy consumption is the major goal of this paper. The topology node formations are performed via improved text rank algorithm (ITRA) and neural network (NN) classifiers with Euclidian distance. In this paper, we introduced an effective optimization algorithm of the exploitation whale optimization algorithm (EWOA) and it is the combination of differential evaluation (DE) and whale optimization algorithms (WOA). The offloading process of proposed EWOA produces an optimal outcome of minimized energy consumption and response time. The implementation works of the proposed EWOA are carried out in the VMware platform. The performance of the proposed method is evaluated using different size puzzles, face detection applications, and state-of-art methods. Ultimately, our proposed method produces optimal accuracy and convergence speed with the minimized offloading process.

Effect of Molecular Weight on Electro – Optic Switching Times of Liquid Crystal Polymer Doped with Ceo2 Nanoparticles

Nonlinearity liquid crystal cell which doped with Ferroelectric nanoparticles characters studied in this paper according to their eclectic absorption. Polysiloxin series with side chain liquid polymers used with side chain polymers and molecular weight ran This study consternate on polymers electro. optic characteristic with various molecular weights by using the mesogenic units and a stable polysiloxane. Suspension sensitivity or Electro-visual response to the mark of the used electric field, a real character to electric liquid crystals. The addition of CeO2, nanoparticles to polymer rise dielectric anisotropy and minimize response times. It observed that the voltages raised with molecular weight rising, and when intensity value rise, we gain voltage operating. Spectrometer used infrared measurements to locate the orientational order parameters, for liquid crystals with a side series. The orientational order parameters rely on temperature with various molecular weights and the threshold voltage.

Development of an algorithm to protect user communication devices against data leaks

In order to identify ways used to collect data from user communication devices, an analysis of the interaction between DNS customers and the Internet name domain space has been carried out. It has been established that the communication device's DNS traffic is logged by the DNS servers of the provider, which poses a threat to the privacy of users. A comprehensive algorithm of protection against the collection of user data, consisting of two modules, has been developed and tested. The first module makes it possible to redirect the communication device's DNS traffic through DNS proxy servers with a predefined anonymity class based on the proposed multitest. To ensure a smooth and sustainable connection, the module automatically connects to a DNS proxy server that has minimal response time from those available in the compiled list. The second module blocks the acquisition of data collected by the developers of the software installed on the user's communication device, as well as by specialized Internet services owned by IT companies. The proposed algorithm makes it possible for users to choose their preferred level of privacy when communicating with the Internet space, thereby providing them with a choice of privacy level and, as a result, limiting the possibility of information manipulation over their owners. The DNS traffic of various fixed and mobile communication devices has been audited. The analysis of DNS traffic has enabled to identify and structure the DNS requests responsible for collecting data from users by the Internet services owned by IT companies. The identified DNS queries have been blocked; it has been experimentally confirmed that the performance of the basic and application software on communication devices was not compromised.

Energy Efficient Resource Migration Based Load Balance Mechanism for High Traffic Applications IoT

The biggest challenge for the network service providers is the day to day advancement of technologies which makes them difficult to manage the traditional networks. This day to day advancement has worked as a motivation to vendors for developing, deploying and migrating their services, installments of new hardware, trained people and up gradation of infrastructure which involves a huge cost and time. These frequent changes demand a new network architecture which supports future technologies and solves all these issues named as the proposal of networks defined by software. A large amount of data is being generated and through the internet, we interact with the world using our smart devices such as tablets, sensors, and smartphones using the concepts of Internet of Things (IoT). Along with continuous growth and development, there is a continuous heterogenous and ever-increasing demands of services. This leads to a cause of emerging challenge of load balancing of networks for meeting up with highly demanding requirements (e.g., high performance, lower latency, high throughput, and high availability) of IoT and 5G network applications. For meeting up highly increasing demands, various proposal of load balancing techniques comes forward, in which highly dedicated balancers of loads are being required for ever service in some of them, or for every new service, manual recognition of device is required. In the conventional network, on the basis of the local information in the network, load balancing is being established. However, the production of more optimized load balancers and a global view for the network is being contained by SDN controllers. So, these well-known techniques are quite time-consuming, expensive and impractical as well as service types aren’t being considered by various existing load balancing schemes. Through this paper, researchers focus on an SDN based load balancing (SBLB) service, in which minimized response time and maximized resource utilization are being considered for the user on cloud servers. The proposed scheme is being constituted by an application module which runs along with a SDN controller and server pools that connect to the controller through SDN enabled switches. The application module contains a dynamic load balancing module, a monitoring module and a service classification module. All messages are being handled in real time and host pool are being maintained by the Controller. The performance of the proposed scheme has been validated by experimental results. Through various experiments, results are being concluded that usage of SBLB results in significant decrease in average response and reply time.

A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware

The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive Ubiquitous Middleware for context-aware IoT ecosystems, which considers the situational context of the applications, devices, or people and the contexts of the network formed and accordingly adapts the behavior of the ecosystem. Adaptive Ubiquitous Middleware is a multi-agent, multi-communication protocol-facilitated middleware that acts as an integration point for applications to access relevant context, share it with other applications, and have relevant services made available via a multi-communication protocol bridge. We also present an optimal service allocation model for a single service class that utilizes available computing resources and achieves a minimum average response time. The system implementation has been evaluated with two use cases to demonstrate its applicability, effectiveness, and generality. The evaluation of optimal service allocation demonstrates the service response is much faster in the proposed model.

A proposed framework for cloud-aware multimodal multimedia big data analysis toward optimal resource allocation

Abstract The main goal of this paper is to demonstrate the structural design of Multimodal Multimedia Services in Cloud Platform (MMSCP). Thus, our proposed MMSCP architecture is built of three levels such as, Service Platform, Execution Platform and Structural platform. The functionality of service platform is to gather different forms of video files generated by the media creators and to store these files on the local platform. The second execution platform integrates both the Hadoop and Mapreduce functionalities. Finally, QoS based cloud computing functionalities (i.e. load balancing, security, resource allocation and network traffic management) is employed at the third structural platform. Likely, we introduced the Crow Search Algorithm (CSA) in structural platform for optimal allocation of resources. We adapt a Hadoop cluster to perform the experiment. Also, to conduct the resource allocation experiment we used some of the conventional optimization algorithms such as, ABC, GA and PSO for comparison with our proposed CSA algorithm imposed on the structural platform. However, to evaluate the performance of the algorithms we configured the CloudAnalyst tool. The simulation results illustrate that the proposed algorithm can allocate the virtual machine (VM) optimally to attain a minimal response time.

A Heuristic Load Balancing Algorithm for Cloud Computing in Heterogeneous Resource Environment

Cloud computing is an alternative technology to develop web-based services. The continuous increase of internet users causes high web service traffic that leads to the requirement of good infrastructure in managing servers in cloud computing. Load balancing between servers is one of the main challenges in cloud computing across multiple nodes. The objective is to ensure that no single resource is overwhelmed nor underused. Load balancing is optimal when maximizing throughput, minimizing response times, and avoiding overloading on one of the connection lines. To solve problems in cloud computing infrastructure, we propose the utilization of two well-known heuristic algorithms to distribute loads on cloud computing. Experimental results indicated that the heuristic algorithm could distribute task loads proportionally to cloud computing resources. Our heuristic algorithm can also distribute tasks to resources with different computing resource specifications and different tasks weights.

Fabrication and characterization of cellulose acetate-based nanofibers and nanofilms for H2S gas sensing application

Electrospun nanofibers and solution-casting nanofilms were produced from an environmentally friendly cellulose acetate (CA) blended with glycerol (as an ionic liquid (IL)), mixed with polypyrrole (PPy, a conducting polymer) and doped with tungsten oxide (WO3) nanoparticles. The sensing membranes fabricated were used to detect H2S gas at room temperature and shown to exhibit high performance. The results revealed that the lowest operating temperature of both nanofiber and nanofilm sensors was 20 °C, with a minimum gas detection limit of 1 ppm. Moreover, the sensor exhibits a reasonably fast response, with a minimum average response time of 22.8 and 31.7 s for the proposed nanofiber and nanofilm based sensors, respectively. Furthermore, the results obtained indicated an excellent reproducibility, long-term stability, and low humidity dependence. Such distinctive properties coupled with an easy fabrication technique provide a promising potential to achieve a precise monitoring of harmful H2S gas in both indoor and outdoor atmospheres.

A novel low-cost gas sensor for CO2 detection using polymer-coated fiber Bragg grating

The realization of detection of carbon dioxide (CO2) is important for environmental protection. A critical challenge is how to fabricate low-cost fiber Bragg grating (FBG) sensor. Here, a new type of polyether sulfone (PES)-coated FBG sensor for CO2 detection is reported to address this challenge. The PES coating exhibits volume dilation in CO2 exposure and can transfer the stress to the grating, causing changes of the period and the refractive index of the grating. The uniform and smooth PES coating is critical for the repeatability and reliability of the sensor, which is realized through the low-temperature spin coating and high-temperature curing. The influence factors and the performance of the FBG sensor were investigated. The maximum Bragg wavelength shift is positively related to coating thickness and negatively related to temperature. The PES-coated FBG sensor possesses good selectivity to CO2 and the minimum response time is 3.27 min. The limit of detection (LOD) can be down to 0.78 % for CO2 detection. Finally, an over-concentration alarm system for on-line CO2 monitoring was developed. The outstanding features of the PES-coated FBG sensor with low-cost and simple fabrication process provide widely prospect in applications.

A fair and efficient resource sharing scheme using modified grey wolf optimizer

With the rapid upsurge in large-scale computing, resource sharing in heterogeneous distributed systems where users’ goals are conflicting has become a paramount research issue. The resource sharing or resource allocation problem is attributed to allocating users’ tasks across multiple computing resources so that the utility of the resources is improved while ensuring the quality of services. In this paper, the resource allocation problem is considered as a bi-objective optimization problem, including minimizing response time and the utilization imbalance between resources. To optimize both the objectives simultaneously, the contributions of this paper are manifolds. First, the problem is modeled as an optimization problem by considering both the objectives in an integrated manner. Second, the resource allocation problem is formulated as a non-cooperative game. Finally, to derive the game’s solution in a distributed manner, a Best Response dynamics based Modified Grey Wolf Optimizer BR-MGWO is proposed. Further, to assess the efficacy of BR-MGWO, it is compared with two other approaches, i.e., GOS and NCOP on problem instances of various settings. The experimental results show that BR-MGWO not only provides less response time while provides better improvements in utilization imbalance, which is reduced by 50% and 71%, respectively, in comparison to the GOS and NCOP.