Number Of Concurrent Requests Research Articles

Research on Detection and Early Warning Mechanism of Emergency Public Health Medical Education System Based on Internet of Things Technology.

Sudden public health and medical education events have tested the stability of society to a great extent. The government need to strengthen capacity building, make use of system dynamic supervision, warn public health events in advance, and minimize the impact scope and related harmfulness of events. This not only facilitates the rapid mobilization of resources by the later government but also facilitates the comprehensive and detailed deployment and arrangement of decision-makers. As we all know, the Internet of Things is used by all walks of life because of its outstanding advantages of low power consumption, low cost, and wide range. Therefore, this article takes the Internet of Things as the technical basis of the system. According to the actual demand and resource design, it includes two system functions: detection and early warning. The results show that: (1) considering the practical principle, the evaluation system interface found that the scores of font size and color style are all below 80%, which need to be optimized and adjusted; the overall interface basically meets the needs of users. (2) The throughput of the three methods is different. The CoAP-E has superior throughput. (3) With the increase in packet loss rate, the request success rate of the CoAP method decreases in a “drop” manner. The CoAP-E method in this article has the best performance. (4) When the packet loss rate is 25%, the network adaptability of this method is the strongest, and the retransmission rate is less than 18%; the CoAP method is as high as 35%. (5) When the number of concurrent requests is less than 2500, there is no obvious difference between the three methods; the optimal performance of the dynamic load balancing method is 10.1 s. (6) The system comprehensively considers various factors of five site selections. The highest comprehensive score of Final Site, 5 is 8.7, which can be used as the resettlement place of emergency rescue facilities. This article starts from the characteristics and needs of public emergencies, and the final set of the system runs well. It can quickly reflect public health emergencies and medical education events. Use the most effective system functions for risk control, and maximize the analysis, organization, and coordination of events. The follow-up optimization of system details needs to be studied.

Design and Implementation of REST API for Academic Information System

With the increased number of information systems used in an organization, there is also an increased importance of data exchange between these systems. This research deals with prototype development and performance analysis of Rest API for academic information system. Rest API was developed using two different server technologies, NodeJS and PHP. The prototype was developed on top of a database server using one sample table that represents employee in a higher education institution. For each of the Rest API developed, there were 2 types of endpoint created. Experiment was set with one database containing a single table and utilized Apache Jmeter to simulate up to 1000 concurrent requests. The results of the experiment show NodeJS implementation of REST API consistently has better performance compared to PHP based REST API implementation. NodeJS implementation reached 100% throughput for up to 1000 concurrent requests, while PHP reached 48.70% throughput when serving the same number of concurrent requests.

Virtual Replication of IoT Hubs in the Cloud: A Flexible Approach to Smart Object Management

In future years, the Internet of Things is expected to interconnect billions of highly heterogeneous devices, denoted as “smart objects”, enabling the development of innovative distributed applications. Smart objects are constrained sensor/actuator-equipped devices, in terms of computational power and available memory. In order to cope with the diverse physical connectivity technologies of smart objects, the Internet Protocol is foreseen as the common “language” for full interoperability and as a unifying factor for integration with the Internet. Large-scale platforms for interconnected devices are required to effectively manage resources provided by smart objects. In this work, we present a novel architecture for the management of large numbers of resources in a scalable, seamless, and secure way. The proposed architecture is based on a network element, denoted as IoT Hub, placed at the border of the constrained network, which implements the following functions: service discovery; border router; HTTP/Constrained Application Protocol (CoAP) and CoAP/CoAP proxy; cache; and resource directory. In order to protect smart objects (which cannot, because of their constrained nature, serve a large number of concurrent requests) and the IoT Hub (which serves as a gateway to the constrained network), we introduce the concept of virtual IoT Hub replica: a Cloud-based “entity” replicating all the functions of a physical IoT Hub, which external clients will query to access resources. IoT Hub replicas are constantly synchronized with the physical IoT Hub through a low-overhead protocol based on Message Queue Telemetry Transport (MQTT). An experimental evaluation, proving the feasibility and advantages of the proposed architecture, is presented.

QoS Based Cloud Service Selection to Handle Large Volume of Concurrent Requests

Background/Objectives: With the exponential growth of cloud providers and users, the possibility of arrival of large number of concurrent requests within a small interval, may reduce the performance of broker. This paper presents a cloud service selection mechanism with service grouping. The main objective of this paper to show the performance difference between the selection mechanism with grouping and without grouping. Methods/Statistical Analysis: For the concurrent services groups and sub groups are created using functional and QoS parameters. Analytical hierarchy based selection algorithm is proposed. Performance of selection algorithm with grouping is evaluated. Performance of selection algorithm with grouping is compared with algorithm without grouping and the sufficient reduction in execution time is noted. Findings: AHP based selection algorithm with grouping improves the performance by reducing the computation time and reducing the repetitive repository access. Applications/Improvements: The limitation of AHP based algorithm is the rank reversal problem. The improved AHP based algorithm can be used to eliminate the rank reversal problem.

Research on Virtual Machine Response Time Prediction Method Based on GA-BP Neural Network

Cloud application provides access to large pool of virtual machines for building high-quality applications to satisfy customers’ requirements. A difficult issue is how to predict virtual machine response time because it determines when we could adjust dynamic scalable virtual machines. To address the critical issue, this paper proposes a prediction virtual machine response time method which is based on genetic algorithm-back propagation (GA-BP) neural network. First of all, we predict component response time by the past virtual machine component usage experience data: the number of concurrent requests and response time. Then, we could predict virtual machines service response time. The results of large-scale experiments show the effectiveness and feasibility of our method.

Enhancing Scalability in On-Demand Video Streaming Services for P2P Systems

Recently, many video applications like video telephony, video conferencing, Video-on-Demand (VoD), and so forth have produced heterogeneous consumers in the Internet. In such a scenario, media servers play vital role when a large number of concurrent requests are sent by heterogeneous users. Moreover, the server and distributed client systems participating in the Internet communication have to provide suitable resources to heterogeneous users to meet their requirements satisfactorily. The challenges in providing suitable resources are to analyze the user service pattern, bandwidth and buffer availability, nature of applications used, and Quality of Service (QoS) requirements for the heterogeneous users. Therefore, it is necessary to provide suitable techniques to handle these challenges. In this paper, we propose a framework for peer-to-peer- (P2P-) based VoD service in order to provide effective video streaming. It consists of four functional modules, namely, Quality Preserving Multivariate Video Model (QPMVM) for efficient server management, tracker for efficient peer management, heuristic-based content distribution, and light weight incentivized sharing mechanism. The first two of these modules are confined to a single entity of the framework while the other two are distributed across entities. Experimental results show that the proposed framework avoids overloading the server, increases the number of clients served, and does not compromise on QoS, irrespective of the fact that the expected framework is slightly reduced.

A Fast Job Scheduling System for a Wide Range of Bioinformatic Applications

Bioinformatic tools are often used by researchers through interactive Web interfaces, resulting in a strong demand for computational resources. The tools are of different kind and range from simple, quick tasks, to complex analyses requiring minutes to hours of processing time and often longer than that. Batteries of computational nodes, such as those found in parallel clusters, provide a platform of choice for this application, especially when a relatively large number of concurrent requests is expected. Here, we describe a scheduling architecture operating at the application level, able to distribute jobs over a large number of hierarchically organized nodes. While not contrasting and peacefully living together with low-level scheduling software, the system takes advantage of tools, such as SQL servers, commonly used in Web applications, to produce low latency and performance which compares well and often surpasses that of more traditional, dedicated schedulers. The system provides the basic functionality necessary to node selection, task execution and service management and monitoring, and may combine loosely linked computational resources, such as those located in geographically distinct sites.

Pinned demand paging based on the access frequency of video files in video servers

In this paper, we present an ameliorative demand-paging algorithm called PDPAF (i.e., pinned demand paging based on the access frequency of video files), to efficiently utilize the limited buffer space in a VOD (video-on-demand) server. It excludes the limitation of the disk bandwidth, and raises the hit ratio of video pages in the buffer, thereby increasing the total number of concurrent clients. Furthermore, we also propose an admission control algorithm to decide whether a new request can be admitted. Finally, we conduct extensive experiments to compare PDPAF with other algorithms on the average waiting time and the maximal number of concurrent requests, and the simulation results validate the superiority of our approach.

QoS issues in Web services

Quality of service (QoS) is a combination of several qualities or properties of a service, such as: availability is the percentage of time that a service is operating; security properties include the existence and type of authentication mechanisms the service offers, confidentiality and data integrity of messages exchanged, nonrepudiation of requests or messages, and resilience to denial-of-service attacks; response time is the time a service takes to respond to various types of requests; Response time is a function of load intensity, which can be measured in terms of arrival rates (such as requests per second) or number of concurrent requests. QoS takes into account not only the average response time, but also the percentile of the response time; and throughput is the rate at which a service can process requests. QoS measures can include the maximum throughput or a function that describes how throughput varies with load intensity. The QoS measure is observed by Web services users. These users are not human beings but programs that send requests for services to Web service providers. QoS issues in Web services have to be evaluated from the perspective of the providers of Web services and from the perspective of the users of these services.