Quality Of Service Conditions Research Articles

A cost‐efficient and QoS‐aware adaptive placement of applications in fog computing

SummaryWith the rapid development of the Internet of Things (IoT), fog computing has emerged as a complementary solution to address the issues faced in cloud computing. However, it is a challenging issue to ensure both of the high Quality of Service (QoS) and low cost for different requests when dealing with computing resources. In this article, we propose a new approach on adaptive cost‐efficient and QoS‐aware application placement for fog computing called DATSS. Specifically, this approach consists of a QoS state driven strategy and a credibility rating mechanism. The algorithm divides the QoS into three different states by calculating the QoS violation rate and adaptively selects the best scheduling strategy. Then evaluates the stability of the node based on the task history, and prioritize the task on the node with a higher rating. Performance results show that the cost, delay and energy consumption of the proposed algorithm can be reduced by 20.9%, 15.7%, and 12.6% respectively compared with other algorithms at most. The proposed algorithm can effectively improve cost efficiency and stability under QoS constraints in fog computing environments.

Quality-based Video Bitrate Control for WebRTC-based Teleconference Services

In this article, we propose a quality-based video bitrate control method for web real-time communication (WebRTC)-based teleconferences. Video bitrate is controlled on the basis of quality of service (QoS) parameters such as delay and packet-loss rate in WebRTC. Therefore, the amount of transferred data may increase because media streams are transmitted at excessive quality levels depending on QoS conditions (e.g., the jitter and packet-loss rate are low). An increase in transferred data leads to higher operational cost (i.e., data transferred cost) and affects profitable growth. In the proposed method, quality desired by a service provider is set as TargetQuality, and the video bitrate of each stream is controlled aiming at TargetQuality, thereby suppressing the amount of transferred data while maintaining sufficient quality. The proposed method is implemented to an actual teleconference system and is evaluated in terms of its effect at reducing the amount of transferred data. The results show that the amount of transferred data can be reduced by more than 40% by setting the value of TargetQuality appropriately.

Nature inspired chaotic squirrel search algorithm (CSSA) for multi objective task scheduling in an IAAS cloud computing atmosphere

Task scheduling in the cloud platform seems to be the most significant issue to guarantee that cloud connectivity adequately and efficiently meets the requirements of customers. Schedulingis basically the method of mapping or assigning tasks after taking into account job features to accessible funds. An effective scheduling protocol should comply with user needs and aids a service provider perform excellent quality of service(QoS) in order to boost general application efficiency. Cloud computing is an evolving computational paradigm with a broad range of self-reliant and economically diverse computational structures. Task scheduling is a significant move to enhance cloud computing general efficiency. Task scheduling is also important in order to decrease power utilization and enhance service providers ' profitability through a reduction in handling moment. In this paper we suggest a chaotic squirrel search algorithm (CSSA) to optimally multitask scheduling in an Infrastructure as a Service (IaaS) cloud atmosphere. The methods continuously generate job plans that render the current approaches more cost-effective. In order to guarantee greater global convergence, the early eco system was produced with messy optimisation for the efficient eco-system. The suggested chaotic squirrel search algorithm was ultimately synthesised with the messy local search to enable the exploring authority to complement Squirrel search algorithm (SSA) algorithms. Other QoS conditions such as compatibility and safety for very big cases can be expanded to cover the suggested technique. A cloud simulator toolkit takes into consideration the strategy and compares the outcomes with scheduling algorithms so that ideal outcomes for several goals are achieved.

On Human-in-the-Loop CPS in Healthcare: A Cloud-Enabled Mobility Assistance Service

SummaryDespite recent advancements on cloud-enabled and human-in-the-loop cyber-physical systems, there is still a lack of understanding of how infrastructure-related quality of service (QoS) issues affect user-perceived quality of experience (QoE). This work presents a pilot experiment over a cloud-enabled mobility assistive device providing a guidance service and investigates the relationship between QoS and QoE in such a system. In our pilot experiment, we employed the CloudWalker, a system linking smart walkers and cloud platforms, to physically interact with users. Different QoS conditions were emulated to represent an architecture in which control algorithms are performed remotely. Results point out that users report satisfactory interaction with the system even under unfavorable QoS conditions. We also found statistically significant data linking QoE degradation to poor QoS conditions. We finalize discussing the interplay between QoS requirements, the human-in-the-loop effect, and the perceived QoE in healthcare applications.

Energy and Bursty Packet Loss Tradeoff Over Fading Channels: A System-Level Model

Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience (QoE) for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross-layer design framework when channel state information (CSI) is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance tradeoff numerically and show the effect of channel uncertainty on the packet scheduler design.

Workload Consolidation for Cloud Data Centers with Guaranteed QoS Using Request Reneging

Cloud data centers are widely employed to offer reliable cloud services. However, low resource utilization and high power consumption have been great challenges for cloud providers. Moreover, the rapid increase in demand for affordable cloud services magnifies the obstacles for proficient resource management policies. In this paper, we investigate how to improve resource utilization and power consumption in cloud data centers when delivering services with statistically guaranteed Quality of Service (QoS). We assume that the service provider hosts different types of services, each of which has request classes with different QoS requirements. Different from the traditional approaches that distribute workloads with different QoS levels on different Virtual Machines (VMs), we introduce an approach to pack requests of the same service type, even with different QoS requirements, into the same VM, and to remove potential failure requests in time to improve resource usage and energy cost. We formally prove that our algorithm can statistically guarantee QoS conditions in terms of deadline miss ratios. We develop a cloud prototype to empirically validate our proposed methods and algorithm. Our experimental results demonstrate that our approach can significantly outperform other traditional approaches in terms of QoS guarantees, power consumption, resource demand and electricity cost.

IJARCCE - Computer and Communication Engineering

QoS (Quality of Service) aware spectrum sensing and channel allocation in cognitive radio wireless mesh networks is a continuous practice due to the divergent scope of communication in wireless mesh networks. Henceforth the current research is moving in a direction to find effective solutions towards QoS aware spectrum sensing and channel allocation. But all of these solutions are specific to one or two QoS factors. According to the real-time practices the QoS assessment by one or two factors is impractical. Moreover majority of current approaches are delivering the computational complexity as O(n2), which due to the magnification of number evolution against the increment in number of channel availability in cognitive radio wireless mesh networks. In this context here we devised a Neighbor Conduct Sensitive QoS variance assessment strategy for cooperative spectrum sensing and channel allocation strategy, which enables to assess the QoS state of a spectrum under possible malicious cooperation that is based on multiple number of QoS factors and also should stabilize the computational complexity to O(n*log(n)). The experiment results are indicating the significance of the proposed model towards scalable and robust QoS variance aware spectrum sensing and channel allocation strategy for cognitive radio wireless mesh networks.

An IPv6 Based QoS Unicast Routing Mechanism

IPv6 is the core protocol of Future Internet. Thus, IPv6 based QoS (Quality of Service) routing mechanisms need to be developed to support diverse QoS requirements of new network applications. In this paper, an IPv6 based QoS unicast routing mechanism is proposed based on OSPFv3 and BGP4 +. By introducing QoS state message and extending the link state database and link state advertisement, the collection, storage and release of intra-domain QoS information are realized. By introducing NLRI (Network Layer Reachability Information) which supports QoS, the release and revocation of inter-domain QoS routing information are realized. The mechanism not only provides QoS support, but also is compatible with the existing routing protocols. It can be quickly and effectively deployed in networks. A prototype implementation of the proposed mechanism is completed, which is tested under a video conference application over the CERNET2 topology. The results indicate that it is feasible and effective with good performance.

Performance Evaluation of Real Time Traffic over MPLS Networks under Different QoS Conditions

One of the most crucial problems in the Internet has been the quality of service (QoS) provisioning. Multiprotocol Label Switching (MPLS) technology guarantees real time and multimedia applications QoS using different resource allocation techniques. Also MPLS contributes high scalability in data network. This paper aims to evaluate MPLS performance based on multimedia service average throughput, total number of packets received, end to end delay, jitter, and packet loss ratio using OPNET simulator. It also compares MPLS network performance to that provided by IP networks. This study shows the scalability of MPLS by simulating small and large networks under different loading conditions. The simulation alsoshows the performance of different MPLS QoS configurations.

QoS and channel state aware load balancing in 3GPP LTE multi-cell networks

In this paper, we investigate the load balancing problem with the consideration of different qualityof- service (QoS) and channel state in 3GPP long term evolution (LTE) multi-cell networks. Load imbalance among nearby cells often causes inefficient utilization of the system resources. Then in overloaded cells, users cannot get satisfied services for short resources, while in idle cells, there is plenty of unoccupied resources. However, switching users only for load balancing with no consideration of channel state often results in aggressive handover of users, which may occupy too many resources in their target cells and deteriorate the network efficiency. Thus, how to efficiently perform load balancing with the consideration of channel state becomes an important issue. Meanwhile, LTE network aims to serve users with different QoS requirements, which should be taken into account when performing load balancing. Thus we propose a multi-objective optimization problem, whose objectives are load balancing index and network average load for users with QoS requirements and a unified utility function for users without QoS requirements. The constraints are physical resource limits and users’ QoS demands. Then we analyze its complexity and propose a practical algorithm, load balancing, with the consideration of different QoS requirements and channel state services (LBQC). Extensive simulations are conducted. The results show that the proposed algorithm can approximate the optimal algorithm efficiently, and leads to significantly better performances than load balancing with no consideration of channel state, e.g. a lower new call blocking rate with a fewer system resources occupation for users with QoS requirements, a higher cell edge throughput and total throughput for users without QoS requirements.

A Dynamic Physical Rate Adaptation for Multimedia Quality-Based Communications in IEEE_802.11 Wireless Networks

Abstract Assuming that the IEEE802.11 Wireless Local Area Networks (WLANs) are based on a radio/infrared link, they are more sensitive to the channel variations and connection ruptures. Therefore the support for multimedia applications over WLANs becomes non-convenient due to the compliance failure in term of link rate and transmission delay performance. We studied link adaptation facets and the Quality of Service (QoS) requirements essential for successful multimedia transmissions. In fact, the efficiency of rate control diagrams is linked to the fast response for channel variation. The 802.11 physical layers provide multiple transmission rates (different modulation and coding schemes). The last 802.11g-version maintains 12 physical rates up to 54 Mbps at the 2.4 GHz band. As a result, Mobile Stations (MSs) are able to select the appropriate link rate depending on the required QoS and instantaneous channel conditions to enhance the overall system performance. Hence, the implemented link adaptation algorithm symbolizes a vital fraction to achieve highest transmission capability in WLANs. “When to decrease and when to increase the transmission rate?” Are the two fundamental matters that we will be faced when designing a new physical-rate control mechanism? Many research works focus on tuning channel estimation schemes to better detect when the channel condition was improved enough to accommodate a higher rate, and then adapts its transmission rate accordingly. However, those techniques usually entail modifications on the current 802.11 standard. Another way to perform link control is based on local Acknowledgment (Ack) information for the transmitter station. Consequently, two techniques where accepted by the standard due to their efficiency and implementation simplicity. We propose a new dynamic time-based link adaptation mechanism, called MAARF (Modified Adaptive Auto Rate Fallback). Beside the transmission frame results, the new model implements a Round Trip Time (RTT) technique to select adequately an instantaneous link rate. This proposed model is evaluated with most recent techniques adopted by the IEEE 802.11 standard: ARF (Auto Rate Fallback) and AARF (Adaptive ARF) schemes. Simulation results will be given to illustrate the link quality improvement of multimedia transmissions over Wi-Fi networks and to compare its performance with previous published results.

A Cost-Optimal QoS Aggregation Policy for Network Mobility: Analysis and Performance Comparisons

The potentially large population density and high handover rates of mobile users aboard a public transport vehicle underpin the need for robust and scalable quality-of-service (QoS) provisioning mechanisms designed for such environments. Traditional QoS approaches fall short of such criteria and have led to the proposal of a number of aggregation-based QoS mechanisms that maintain a single QoS state in the access network for the entire moving network subnet. Although such proposals can increase handover scalability, the dynamic connectivity and population of users within public transport vehicles can lead to bursts of requests being made due to passengers embarking on a vehicle in groups, intermittently increasing the control signaling density in the network and consequently increasing the cost to the operator. QoS aggregation policies alleviate this problem by buffering QoS requests at the mobile router installed on the vehicle for a period of time and then aggregating these into a single request to alter the resources reserved in the access network for the moving network. A number of such policies have previously been proposed in the literature to control and manage the buffering duration at the mobile router. However, since the aggregation decision of these policies is based on a static request-rate-dependent parameter, cost inefficiency can occur when the request rate is variable, as is typical of public transport vehicles due to passengers embarking and disembarking. This paper therefore provides a full mathematical and simulation-based analysis of a novel cost-driven aggregation policy and compares its performance with that of other policies previously proposed in the literature. Our results show that our cost-driven policy can reduce operator costs due to signaling by up to 21% compared with other policies while, at the same time, not putting the user at a disadvantage with long and unpredictable waiting times to establish a session.

Multi-Area QoS Provisioning Using Hierarchical Bandwidth Brokers Architecture

In this paper, an intra-domain, multi-area Quality of Service (QoS) provisioning mechanism, namely the QoS-HBB architecture is proposed to alleviate the scalability problem in the intra-domain bandwidth broker design. By exploiting the inherent hierarchical nature of OSPF and the fact that an OSPF domain can be subdivided into multiple areas, QoS-HBB introduces two levels (i.e. intra-area and inter-area) of QoS provisioning within a domain. The proposed architecture allows the deployment of multiple bandwidth brokers in the backbone area and non-backbone areas. At the intra-area level, a child bandwidth broker is deployed in every non-backbone area to handle intra-area QoS provisioning; whereas, at the inter-area level, QoS control functions are delegated from the child bandwidth broker to the parent bandwidth broker situated at the backbone area. With the hierarchical design and efficient QoS state information maintenance, QoS-HBB is capable of providing service assurance to end-user applications. Furthermore, Multi-Protocol Label Switching (MPLS) and path caching are incorporated to improve the performance. Simulation results show that, compared to ordinary OSPF, QoS-HBB significantly improves QoS provisioning in terms of packet loss ratio, link utilization, end-to-end delay, packet commit percentage, and throughput.

Policy mechanism and evaluation algorithm for connectivity management adaptability

Purpose – An infrastructure based on multiple heterogeneous access networks is one of the leading enablers for the emerging paradigm of pervasive computing. The optimal management of diverse networking resources is a challenging problem. This paper aims to present a context‐aware policy mechanism with related end‐to‐end (E2E) evaluation algorithm for adaptive connectivity management in multi‐access wireless networks.Design/methodology/approach – A policy is used to express the criteria for adaptive selection of the best local and remote network interfaces. The best connection can then be used for the establishment of a channel as well as for the maintenance of on‐going data transmission. Rich context information is considered in the policy representation with respect to user profile and preference, application characteristics, device capability, and network quality of service conditions. The decision of the best access networks to be used is made on the basis of an E2E evaluation process. The decision can...

Extending the Lifetime of Sensor Networks through Adaptive Reclustering

We analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality-of-service (QoS) constraint, given by the maximum tolerable probability of decision error at the access point (AP). In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal) for the lifetime of a single sensor. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. We also derive an analytical framework for the computation of the network lifetime and the penalty, in terms of time delay and energy consumption, brought by adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime. Moreover, the observation of the phenomenon should be frequent in order to limit the penalties associated with the reclustering procedure. We also apply the developed framework to analyze the energy consumption associated with the proposed reclustering protocol, obtaining results in good agreement with the performance of realistic wireless sensor networks. Finally, we present simulation results on the lifetime of IEEE 802.15.4 wireless sensor networks, which enrich the proposed analytical framework and show that typical networking performance metrics (such as throughput and delay) are influenced by the sensor network lifetime.

Localized Route Selection for Traffic with Bandwidth Guarantees

Localized Quality of Service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localized view of the network QoS state. One of the most important QoS metrics is bandwidth and in this paper we introduce a localized routing scheme for providing bandwidth guarantees, based on a crediting scheme that uses an estimate of flow blocking probability to adjust credits and select routes. We compare its performance against the localized proportional sticky routing (PSR) algorithm using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that our algorithm outperforms the PSR scheme while maintaining the same level of adaptivity and stability. We also compare performance against the well known widest-shortest path (WSP) algorithm that uses the global network QoS state and show that our algorithm gives a comparable performance with better time complexity and very much lower communication overhead. The simulations were implemented using OMNET ++, a discrete-event simulator that provides a rich set of functions and tools for simulating the elements of a communication network, such as nodes, links and packets.

Localised credit based QoS routing

Localised quality of service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localised view of the network QoS state. A credit based routing algorithm (CBR) which is a simple yet effective localised QoS routing algorithm is introduced. Its performance is compared against the localised proportional sticky routing (PSR) algorithm using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that the algorithm outperforms the PSR scheme while maintaining the same level of adaptivity and stability. Its performance is also compared against the global widest-shortest path algorithm (WSP) and it is shown that CBR gives a comparable performance with better time complexity and very low communication overhead.

Class Mapping for End-to-End Guaranteed Service with Minimum Price over DiffServ Networks

Differentiated-services model has been prevailed as a scalable solution to provide quality of service over the Internet. Many researches have been focused on per hop behavior or a single domain behavior to enhance quality of service. Thus, there are still difficulties in providing the end-to-end guaranteed service when the path between sender and receiver includes multiple domains. Furthermore differentiated-services model mainly considers quality of service for traffic aggregates due to the scalability, and the quality of service state may be time varying according to the network conditions in the case of relative service model, which make the problem more challenging to guarantee the end-to-end quality-of-service. In this paper, we study class mapping mechanisms along the path to provide the end-to-end guaranteed quality of service with the minimum networking price over multiple differentiated-services domains. The proposed mechanism includes an effective implementation of relative differentiated-services model, quality of service advertising mechanism and class selecting mechanisms. Finally, the experimental results are provided to show the performance of the proposed algorithm.

A survey of internet QoS signaling

The need for real-time services support over the Internet drives research efforts toward the provisioning of quality of service (QoS) guarantees in IP networks. Among the various aspects of QoS provisioning, QoS state establishment and maintenance in intermediate routers is a major factor, responsible for dynamic resource allocation. The dynamic manipulation of QoS state is possible through the utilization of appropriate QoS signaling that triggers the respective resource allocation in QoS-capable network elements. At first, protocol design assumed a homogeneous underlying network and resulted in end-to-end QoS protocols that applied a specific QoS configuration in all routers along the path. However, the need for accommodating network heterogeneity and flexibility led to a two-tier resource management model that utilizes separate signaling for intra- and inter-domain reservations and requires different signaling processing in domain interior and border routers. This article gives an overview of the QoS signaling protocols designed for the Internet and describes their characteristics. Moreover, the identified protocols are classified depending on their applicability for intra- or inter-domain usage. A comparison of the various protocols based on some common signaling elements is also provided, and future trends in the Internet QoS signaling area are identified.

QMBF: a QoS-aware multicast routing protocol

Many multicast applications, such as video-on-demand and tele-education, desire quality of service (QoS) support from the underlying network. Recently, many QoS-based multicast protocols have been proposed to meet this requirement. However, few of them can achieve high success ratios while maintaining good scalability. In this paper, we propose a new QoS-aware multicast protocol based on a bounded flooding technique (QMBF). In this protocol, every network node maintains the knowledge of a local network cell (LNC) topology as well as QoS state information (collected from the bounded flooding messages). QMBF utilizes this knowledge to increase the probability and accuracy of finding a feasible branch which connects a new member to an existing multicast tree. The protocol exploits two approaches to find feasible branches: repeatedly computing partial feasible branches using the LNC information and searching multiple paths. The design of QMBF allows it to operate on top of any unicast routing protocol or cooperate with a QoS-based unicast routing protocol. Results obtained using NS-2 simulator demonstrate high success ratio for locating feasible branches for multicast paths.