Constrained Bayesian Optimization of VANET Safety Messaging Using Deep Learning Neural Networks

Enforcing QoS in scientific workflow systems enacted over Cloud infrastructures

Edge computing is a new computing paradigm after cloud computing. Edge service scheduling and composition (ESC) has been well recognized as a convenient and flexible way of services sharing and integrating in industrial application fields. The ESC aims at selecting a set of existing edge service candidates with different Quality of Service (QoS) attributes (e.g., price), then compositing them to accomplish a complex task to meet users' QoS requirements, where each edge service may have multiple functionally equivalent, but different QoS metrics. A grand research challenge of the ESC based on QoS is to select proper service candidates to maximize QoS of the composited edge service and meanwhile meet the global QoS requirements. In this article, we focus on this challenge and propose a hierarchical solution for ESC. Specifically, we classify service candidates into specified grades based on their QoS attributes, and use hierarchical model to address service selection problem. Furthermore, in order to expand the flexibility of our approach, we design a near-optimal solution by decomposing the global end-to-end QoS constraints into local QoS constraints and adopting local service selecting and updating strategy based on the hierarchical model. The results of simulation-based experiments are conducted to show our approach is more efficient and valid compared to other existing approaches.

The growing emergence of a variety of network applications have stringent Quality of Service (QoS) requirements which cannot be always met by the best-effort Internet. To provide QoS, several QoS frameworks have been explored over last two decades, but none of them has been truly successful and globally implemented. This paper proposes QOF, a novel QoS framework based on the OpenFlow. It uses the superior control capabilities of OpenFlow network to transmit business having QoS requirements. On receiving QoS requirements of an application, QOF employs network status information provided by the measurement system (bandwidth, delay, packet loss), then uses QoS routing algorithm implemented by path computation module to guarantee QoS. Finally, QOF is simulated and verified, simulation results show that QOF can find a path satisfying QoS requirements of application according to network status information, and can improve resource usage.

Wireless Body Area Network (WBAN) represents one of the most promising networks to provide health applications for improving the quality of life, such as ubiquitous e-Health services and real-time health monitoring. The resource allocation of an energy-constrained, heterogeneous WBAN is a critical issue that should consider both energy efficiency and Quality of Service (QoS) requirements with the dynamic link characteristics, especially when the limited resource cannot satisfy the expected QoS requirements. In this paper, a buffer aware Energy-efficient and QoS-effective resource allocation scheme is proposed in which the sensor queue buffer states, constraints of QoS metrics and the characteristics of dynamic links are considered. Specifically, a buffer aware sensor evaluation method is designed to dynamically evaluate the sensor state with considering the sensor buffer states for improving the system performance. We then formulate the resource allocation problem for optimizing the transmission power, the transmission rate and the allocated time slots for each sensor to minimize the sum mix-cost, which is defined to characterize the energy cost and QoS cost between attainable QoS support and QoS requirements. Simulation results demonstrate the effectiveness of the buffer aware sensor evaluation method and the proposed energy-efficient and QoS-effective resource allocation scheme.

Vehicular ad hoc network (VANET) applications become increasingly popular. Particular characteristics of VANETs profoundly impede the deployment of the VANET applications. Therefore, the merits of routing significantly affect the accomplishments of the VANETs. Though myriads of efforts have been made, the problems are partially solved. Quality of Service (QoS) requirements should be satisfied for various applications. Existing routing protocols are incapable of well satisfying distinct QoS needs. To remedy this problem, a next-hop selection scheme is proposed in this paper; which is able to select the next-hop node for various applications with diverse QoS requirements. Aspects including QoS type classification, link lifetime prediction, bandwidth evaluation, and next-hop node selection; are elaborately addressed in the proposed scheme. The simulation results show that the proposed next-hop selection scheme promotes packet delivery rate, shortens end-to-end delay, and decreases signaling overhead in VANETs.

With the rapid development of e-commerce over Internet, web services have attracted much attention in recent years. Nowadays, enterprises are able to outsource their internal business processes as services and make them accessible via the Web. Then they can dynamically combine individual services to provide new value-added services. With the increasing number of web services having equivalent functionality, the binding procedure is driven by some non-functional, Quality of Service (QoS) criteria, such as the money cost, response time, reputation, reliability or a trade-off between them. Thus, an important problem is, given QoS constraints, how to aggregate and leverage individual service’s QoS information to derive the optimal QoS of the composite service. In this paper, we propose a novel QoS model for performing flexible service selection. The key idea of the model is to relax users’ QoS constraints and try to find the most possible services satisfying users’ QoS requirements. Based on the proposed QoS framework, we develop various algorithms for making service selection on individual and composite services. We also introduce a top-k ranking strategy to reflect a user’s personalized requirements. Experimental evaluation shows the proposed QoS model is efficient and practical.

End-to-end network slicing in unmanned aerial vehicle (UAV) networks has attracted significant attention for delivering differentiated services tailored to the quality of service (QoS) requirements of user terminals (UTs). In a sliced UAV network, the dual mobility of both UTs and UAVs, combined with the three-layer association of UT-UAV-network slice (NS), makes handoff a critical and challenging problem for maintaining the communication performance of UTs. This paper proposes a sequential handoff process where a central controller makes handoff decisions for each UT sequentially according to the UT queue. This process is modeled as a Markov decision process (MDP). In the MDP, the state space includes NS available resources, UTs' QoS requirements, and UT queue information. Additionally, the reward function accounts for UTs' QoS and handoff overhead. The double deep Q-network (DDQN) technique is then employed to design a handoff algorithm. This algorithm achieves the optimization goal of ensuring UTs' QoS requirements while avoiding frequent handoffs by maximizing the total reward of the MDP. Additionally, a state-dependent exploration technique with adaptive intensity adjustment, called noisy network (NoisyNet), is utilized to drive the DDQN for effective exploration, thereby enhancing the performance of the handoff algorithm. Finally, the runtime complexity of the proposed NoisyNet-DDQN-based sequential handoff (NoisyNet-DDQN-SH) algorithm is analyzed. The simulation results show that the NoisyNet-DDQN-SH algorithm converges well. Moreover, it exhibits strong robustness. Additionally, the NoisyNet technique effectively enhances the algorithm's performance, making the NoisyNet-DDQN-SH algorithm superior to the vanilla DDQN (with an ϵ-greedy strategy), greedy, maximum signal-to-interference-plus-noise ratio (MaxSINR), and random algorithms.

Component-based development (CBD) techniques have been widely used to enhance the productivity and reduce the cost for software systems development. However, applying CBD techniques to embedded software development faces additional challenges. For embedded systems, it is crucial to consider the quality of service (QoS) attributes, such as timeliness, memory limitations, output precision, battery constraints. Frequently, multiple components implementing the same functionality with different QoS properties can be used to compose a system. Also, software components may have parameters that can be configured to satisfy different QoS requirements. Composition analysis, which is used to determine the most suitable component selections and parameter settings to best satisfy the system QoS requirement, is very important in embedded software development process. In this paper, we present a model and the methodologies to facilitate composition analysis. We define QoS requirements as constraints and objectives. Composition analysis is performed based on the QoS properties and requirements to find solutions (component selections and parameter settings) that can optimize the QoS objectives while satisfying the QoS constraints. We use a multiobjective concept to model the composition analysis problem and use an evolutionary algorithm to determine the Pareto-optimal solutions efficiently.

Wireless mobile radio systems have to serve users with different quality of service (QoS) requirements. Scheduling algorithms like weighted proportional fair (WPF) have been proposed considering channel gains to improve the system capacity in terms of sector throughput as well as user priorities to fulfill QoS requirements. These scheduling algorithms allow assigning different priority factors to users and services so that different QoS requirements can be fulfilled. This paper provides an analysis of the influence of users with different priorities on the sector and user throughput. It is shown analytically and by system level simulations that the average user throughput can be adjusted by choosing a specific priority factor. Furthermore, it is shown that the sector throughput decreases if WPF scheduling for users with different priorities and full buffer model are considered compared to a scenario with users having equal priority. If QoS requirements for realistic traffic models, e.g. FTP, have to be fulfilled, for each high priority user low priority users have to be removed from the system in order not to exceed an acceptable number of unsatisfied users. It is shown that the decrease in sector throughput with a realistic traffic model and QoS requirements is higher than for the full buffer model.

Effective support of real‐time multimedia applications in wireless access networks, viz. cellular networks and wireless LANs, requires a dynamic bandwidth adaptation framework where the bandwidth of an ongoing call is continuously monitored and adjusted. Since bandwidth is a scarce resource in wireless networking, it needs to be carefully allocated amidst competing connections with different Quality of Service (QoS) requirements. In this paper, we propose a new framework called QoS‐adaptive multimedia wireless access (QoS‐AMWA) for supporting heterogeneous traffic with different QoS requirements in wireless cellular networks. The QoS‐AMWA framework combines the following components: (i) a threshold‐based bandwidth allocation policy that gives priority to handoff calls over new calls and prioritizes between different classes of handoff calls by assigning a threshold to each class, (ii) an efficient threshold‐type connection admission control algorithm, and (iii) a bandwidth adaptation algorithm that dynamically adjusts the bandwidth of an ongoing multimedia call to minimize the number of calls receiving lower bandwidth than the requested. The framework can be modeled as a multi‐dimensional Markov chain, and therefore, a product‐form solution is provided. The QoS metrics—new call blocking probability (NCBP), handoff call dropping probability (HCDB), and degradation probability (DP)—are derived. The analytical results are supported by simulation and show that this work improves the service quality by minimizing the handoff call dropping probability and maintaining the bandwidth utilization efficiently. Copyright © 2006 John Wiley & Sons, Ltd.

Although cloud storage service (CSS) is convenient to access data, the cost, security, and performance are the issues to users who consider to adopt CSS. For example, CSS could be unavailable due to technical issues or natural disaster. In order to avoid single point of failure, many users duplicate data into multiple CSS providers (CSPs). However, this will increase cost; decrease security; and is difficult to maintain data consistency. In this paper, we propose a QoS-aware Distributed Cloud Storage Service (QDCSS) which aims to provide users with the appropriate CSS according to their quality of service (QoS) requirements. In QDCSS, the data will be encoded into code words by applying erasure code and then the code words will be smartly distributed to multiple CSPs to meet users' QoS requirements. Compared with data duplication, the numerical analysis show that QdCSS can reduce cost by 73% and improve security by 63%. Moreover, the simulation results show that QDCSS can adapt to different users' QoS requirements.

Objectives: To explored the highlighted obliged QoS routing issue in Vehicular Ad hoc Networks (VANETs). Methods/ Statistical Analysis: The issues are tended to firstly by working up an association faithful quality model considering the topological and numerical properties of vehicular advancements and speeds. The VANET correspondence diagram in advancing chart hypothesis is used to model and organize the formed association trustworthiness shown into it. In light of the consequent intensified chart diagram illustrate, the most tried and true course in the framework is picked. However course assurance does not ensure awesome transmission as well. Findings: Vehicular extraordinarily designated Systems (VANETs) are a particular sort of remote framework made by vehicles giving among themselves and with roadside base stations. A broad assortment of organizations has been made for VANETs going from security to infotainment applications. A key need for such organizations is that they are offered with Nature of Administration Quality of Service (QoS) guarantees similar to organization unfaltering quality and availability. QoS routing expect an essential part in recognizing courses that meet the QoS necessities of the offered organization over VANETs. For filtering the achievable courses it subject to various QoS goals is with everything taken into account a NP-difficult issue. Furthermore, the reliability of the routing ought to be given unprecedented thought as correspondence associations, as frequently as conceivable in VANETs. In present situation, the most existing QoS routing calculations are been PSO algorithm for stable VANET system without considering the security and wellbeing of the routing procedure. Along these lines, they are not appropriate for applications in VANETs. Application/Improvements: Low complexity nature advanced administration dependable routing calculation is made to ensure to lessen transmission redundancy with use of Subterranean insect State estimation with better eventual outcomes of course decision and transmission considering better request and sorting calculations in the Particle Swam Optimization (PSO) algorithm work calculation for extremely powerful VANET system with less preferred quality in evaluation with favoured data transmission over interchange QoS counts as shown by the results and satisfy QoS requirements of specific traffic using PSO in the VANET routing protocol environments. Meanwhile, an optimized function with PSO is also proposed to make scheduling decisions so that the dropped packet rates are reduced. The results of PSO algorithm simulations are better and feasible as compared to the previous techniques. Keywords: Graph Theory, Optimised Service Reliable Routing Algorithm, Particle Swam Optimization, Quality of Service, Roadside Base Stations, VANET

Vehicular ad-hoc networks (VANETs) are a significant field in the intelligent transportation system (ITS) for improving road security. The interaction among the vehicles is enclosed under VANETs. Many experiments have been performed in the region of VANET improvement. A familiar challenge that occurs is obtaining various constrained quality of service (QoS) metrics. For resolving this issue, this study obtains a cost design for the vehicle routing issue by focusing on the QoS metrics such as collision, travel cost, awareness, and congestion. The awareness of QoS is fuzzified into a price design that comprises the entire cost of routing. As the genetic algorithm (GA) endures from the most significant challenges such as complexity, unassisted issues in mutation, detecting slow convergence, global maxima, multifaceted features under genetic coding, and better fitting, the currently established lion algorithm (LA) is employed. The computation is analyzed by deploying three well-known studies such as cost analysis, convergence analysis, and complexity investigations. A numerical analysis with quantitative outcome has also been studied based on the obtained correlation analysis among various cost functions. It is found that LA performs better than GA with a reduction in complexity and routing cost.

IEEE 802.16 is a standardisation for a broadband wireless access in metropolitan area networks (MAN). Since the IEEE 802.16 standard defines the concrete quality of service (QoS) requirement, a scheduling scheme is necessary to achieve the QoS requirement. Many scheduling schemes are proposed with the purpose of throughput optimisation and fairness enhancement, however, few scheduling schemes support the delay requirement. In this study, the authors propose a new scheduling scheme reflecting the delay requirement. Specifically, the authors add the delay requirement term in the proportional fair scheduling scheme and the scheduling parameters are optimised with respect to the QoS requirement. Therefore the QoS requirement is achieved without the excessive resource consumption.

A 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) system uses the concept of two-tier heterogeneous networks (HetNets), where low-power and short-range femtocells are laid under macrocells to fulfill the quality of service (QoS) requirements of users and to boost overall network capacity. However, co-channel interference is one of the major issues that need to be resolved for the successful deployment of HetNets. To overcome this problem, fractional frequency reuse (FFR) schemes have been proposed that can efficiently utilize the available spectrum. Nevertheless, these schemes waste limited frequency resources owing to their static allocation and lack of following QoS requirements, network loading conditions, and service priority of users. In this paper, a QoS-based dynamic FFR (QoS-DFFR) scheme is proposed that efficiently allocates the non-occupied center-zone frequency bands, i.e., bonus bandwidth (BBW), to cell-edge users by considering their QoS requirements. Consequently, the proposed QoS-DFFR scheme can optimize cell-edge user throughput and sector throughput and reduce co-channel interference by dynamically allocating the BBW to the most demanding cell-edge users. The proposed QoS-DFFR scheme improves performance because of its ability to dynamically allocate the limited portion of the frequency bands based on the service priorities of users. The system-level simulation results show that the proposed QoS-DFFR scheme performs remarkably well in a HetNet environment. Compared with the usual FFR schemes, the proposed scheme almost doubles the cell-edge user's throughput and reduces the user's packet loss rate.