Optimal Resource Allocation and Quality of Service Prediction in Cloud

In the present scenario,cloud computing service provides on-request access to a collection of resources available in remote system that can be shared by numerous clients.Resources are in self-administration;consequently,clients can adjust their usage according to their requirements.Resource usage is estimated and clients can pay according to their utilization.In literature,the existing method describes the usage of various hardware assets.Quality of Service(QoS)needs to be considered for ascertaining the schedule and the access of resources.Adhering with the security arrangement,any additional code is forbidden to ensure the usage of resources complying with QoS.Thus,all monitoring must be done from the hypervisor.To overcome the issues,Robust Resource Allocation and Utilization(RRAU)approach is developed for optimizing the management of its cloud resources.The work hosts a numerous virtual assets which could be expected under the circumstances and it enforces a controlled degree of QoS.The asset assignment calculation is heuristic,which is based on experimental evaluations,RRAU approach with J48 prediction model reduces Job Completion Time(JCT)by 4.75 s,Make Span(MS)6.25,and Monetary Cost(MC)4.25 for 15,25,35 and 45 resources are compared to the conventional methodologies in cloud environment.

Efficient Energy and Delay Reduction Model for Wireless Sensor Networks

In every network,delay and energy are crucial for communication and network life.In wireless sensor networks,many tiny nodes create networks with high energy consumption and compute routes for better communication.Wireless Sensor Networks(WSN)is a very complex scenario to compute minimal delay with data aggregation and energy efficiency.In this research,we compute minimal delay and energy efficiency for improving the quality of service of any WSN.The proposed work is based on energy and distance parameters as taken dependent variables with data aggregation.Data aggregation performs on different models,namely Hybrid-Low Energy Adaptive Clustering Hierarchy(H-LEACH),Low Energy Adaptive Clustering Hierarchy(LEACH),and Multi-Aggregator-based Multi-Cast(MAMC).The main contribution of this research is to a reduction in delay and optimized energy solution,a novel hybrid model design in this research that ensures the quality of service in WSN.This model includes a whale optimization technique that involves heterogeneous functions and performs optimization to reach optimized results.For cluster head selection,Stable Election Protocol(SEP)protocol is used and Power-Efficient Gathering in Sensor Information Systems(PEGASIS)is used for driven-path in routing.Simulation results evaluate that H-LEACH provides minimal delay and energy consumption by sensor nodes.In the comparison of existing theories and our proposed method,HLEACH is providing energy and delay reduction and improvement in quality of service.MATLAB 2019 is used for simulation work.

Centralized QoS Routing Model for Delay/Loss Sensitive Flows at the SDN-IoT Infrastructure

The rapidly increasing number of Internet of Things(IoT)devices and Quality of Service(QoS)requirements have made the provisioning of network solutions to meet this demand a major research topic.Providing fast and reliable routing paths based on the QoS requirements of IoT devices is very important task for Industry 4.0.The software-defined network is one of the most current interesting research developments,offering an efficient and effective solution for centralized control and network intelligence.A new SDN-IoT paradigm has been proposed to improve network QoS,taking advantage of SDN architecture in IoT networks.At the present time,most publish-subscribe IoT platforms assume the same QoS requirements for all customers.However,in many real-world scenarios of IoT applications,different subscribers may have different E2E delay requirements.Providing reliable differentiated services has become a relevant problem.For this we developed a technique for classifying IoT flows with the individual subscriber recommendation on the importance of certain parameters for particular classes of traffic taken into account.To improve the QoS for mission-critical IoT applications in large-scale SDN-IoT infrastructure,we focused on optimizing routing in the SDN.For this purpose,a centralized routing model based on QoS parameters and IoT priority flow for the SDN was proposed and implemented.We have compared the proposed routing model with the state-of-art deterministic multiconstrained centralized QoS routing model(DMCQR).The developed centralized routing model in comparison with the known DMCQR flow routing achieved better balance of channel resources load due to rational choice of transmission paths for different traffic.And it was possible to reduce up to 3 times the average delay of real time flows service from end to end,for which with the existing DMCQR routing model the permissible delay rates were not met.

Dynamic resource management using bandwidth brokers

The admission control issue in the design of a centralized bandwidth broker model for dynamic control and management of QoS provisioning is studied. A two-phase differentiated flow treatment based dynamic admission control scheme under the centralized bandwidth broker model is proposed. In the proposed scheme, the flow requests are classified into two classes and get differentiated treatment according to their QoS demands. We demonstrate that this admission control scheme can not only improve the resource utilization but also guarantee the flows＇ QoS. Furthermore, the admission control is divided into two phases： edge admission control and interior admission control. During the interior phase, the PoQ scheme is adopted, which enhances the call processing capability of the bandwidth broker. The simulation results show that the proposed scheme can result in lower flow blocking probability and higher resource utilization. And it also reduces the number of QoS state accesses/updates, thereby increasing the overall call processing capability of the bandwidth broker.

QoS in FANET Business and Swarm Data

This article shows the quality of services in a wireless swarm of drones that form an ad hoc network between them Fly Ad Hoc Networks(FANET).Each drone has the ability to send and receive information(like a router);and can behave as a hierarchical node whit the intregration of three protocols:Multiprotocol Label Switch(MPLS),Fast Hierarchical AD Hoc Mobile(FHAM)and Internet Protocol version 6(IPv6),in conclusion MPLS+FHAM+IPv6.The metrics analyzed in the FANET are:delay,jitter,throughput,lost and sent packets/received.Testing process was carried out with swarms composed of 10,20,30 and 40 units;In this work,the stage with 40 droneswas analyzed showing registration processes,and sentmessages sequences between different drones that were part of the same swarm.A special analysis about the traffic between drones(end-to-end)was carried out,as well as the possible security flaws in each drone and the current status and future trends in real services.Regarding future trends,in a real environment,we took as a starting point,metrics results obtained in the simulation(positive according to the obtained results).These results gave us a clear vision of how the network will behave in a real environment with the aim to carry out the experiment on a physical level in the near future.This work also shows the experience quality from the service quality metrics obtained through a mathematical model.This quality of experience model will allow us to use it objectively in the agricultural sector,which is a great interest area and is where we are working with drones.Finally in this article we show our advances for a business model applied to the aforementioned agricultural sector,as well as the data analysis and services available to the end customer.These services available to the end customer have been classified into a basic,medium,advanced and plus level.

A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to improve QoS in high-speed railway communication

Technological advancement in the field of trans- portation and communication has been happening at a faster pace in the past few decades. As the demand for high-speed transportation increases, the need for an improved seamless communication system to handle higher data traffic in a highly mobile environment becomes imperative. This paper proposes a novel scheme to enhance the quality of service in high-speed railway （HSR） communication environment using the concept of torch nodes （TNs） and adaptive measurement aggregation （AMA）. The system was modeled using an object-oriented discrete event sim- ulator, and the performance was analyzed against the existing single-antenna scheme. The simulation results show that the proposed scheme with its minimal imple- mentation overhead can efficiently perform seamless han- dover with reduced handover failure and communication interruption probability.

A Handover Strategy in the LEO Satellite-Based Constellation Networks with ISLs

A new handover strategy named minimal-hops handover(MHH) strategy for the lowearth orbit(LEO) satellite constellations networks equipped with inter-satellite links(ISLs) is proposed.MHH strategy,which is based on the hops of the end-to-end connection paths and makes good use of theregularity of the constellation network topology,can appropriately combine the handover procedure withrouting and efficiently solve the inter-satellite handover issue.Moreover,MHH strategy can providequality of services(QoS) guarantees to some extent.The system performances of the MHH strategy,suchas time propagation delay and handover frequency,are evaluated and compared with that of otherprevious strategies.The simulation results show that MHH strategy performs better than other previoushandover strategies.

QoS Requirement Generation and Algorithm Selection for Composite Service Based on Reference Vector

Under SOA （Service-Oriented Architecture）, composite service is formed by aggregating multiple component services together in a given workflow. One key criterion of this research topic is QoS composition. Most work on service composition mainly focuses on the algorithms about how to compose services according to assumed QoS, without considering where the required QoS comes from and the selection of user preferred composition algorithm among those with different computational cost and different selection results. In this paper, we propose to strengthen current service composition mechanism by generation of QoS requirement and its algorithm selection based on the QoS reference vectors which are calculated optimally from the existing individual services＇ QoS by registry to represent QoS overview about the best QoS, the worst （or most economical） QoS, or the average QoS of all composite services. To implement QoS requirement, which is determined according to QoS overview, this paper introduces two selection algorithms as two kinds of experiment examples, one aiming at the most accurate service selection and the other chasing for trade-off between selection cost and result. Experimental results show our mechanism can help the requester achieve his expected composite service with appropriate QoS requirement and customized selection algorithm.