An autonomic PCN based admission control mechanism for video services in access networks

The introduction of new added value services such as IPTV has introduced great challenges for today's broadband DSL access networks as these services have stringent quality demands. In an attempt to protect the quality delivery of existing sessions, operators employ admission control mechanisms that limit the amount of sessions transmitted in the network. Current admission control mechanisms require a traffic specification of each stream, in order to know beforehand how many resources need to be reserved. For variable bit rate videos, which are bursty of nature, resources are reserved using the peak rate of the video. This leads to under-utilisation of the network as the amount of resources needed is over-dimensioned. We propose an autonomic measurement based admission control algorithm, optimised for the protection of video services in multimedia access networks. The algorithm is based on the IETF precongestion notification (PCN) mechanism and autonomically adjusts its parameters to the traffic characterisation of the video. The performance of this mechanism has been extensively evaluated in a packet based network simulation environment. Tests show that the autonomic nature of the algorithm leads to a better utilisation of the network while still avoiding any congestion in the network

Discovering Indicators for Congestion in DBMSs

Abstract-In today's data server environments, multiple types of workloads can be present in a system simultaneously. Workloads may have different levels of business importance and unique performance goals. An autonomic workload management system controls the flow of the workloads to help the database management system (DBMS) meet the performance goals. A task of the autonomic workload management system is to prevent congestion in the DBMS, which can result in severe degradation in overall system performance. Autonomic workload management should detect that a system is becoming congested and then act to restore normal system operation. In this paper, we describe an approach to identify a set of database monitor metrics that can serve as indicators for potential congestion in a specific scenario. We present experiments to illustrate two cases of congestion in a DB2 ® DBMS and use our approach to derive the indicators

Protecting video service quality in multimedia access networks through PCN

The growing popularity of video-based services and their corresponding unpredictable bursty behavior makes the design of an admission control system an important research challenge. The pre-congestion notification (PCN) mechanism is a measurement-based approach, recently standardized by the IETF, optimized toward the admission of inelastic flows, where the number of flows is sufficiently large that individual bursts of flows can be compensated by silence periods of others. In this article, we discuss the implications of applying PCN to protect video services, which have less predictable behavior. Several algorithms for protecting video services in multimedia access networks are described. Through performance evaluation, we show the impact of these algorithms on the network utilization and video quality, and present guidelines on how to configure a PCN system

Cross-layer signalling and middleware: a survey for inelastic soft real-time applications in MANETs

This paper provides a review of the different cross-layer design and protocol tuning approaches that may be used to meet a growing need to support inelastic soft real-time streams in MANETs. These streams are characterised by critical timing and throughput requirements and low packet loss tolerance levels. Many cross-layer approaches exist either for provision of QoS to soft real-time streams in static wireless networks or to improve the performance of real and non-real-time transmissions in MANETs. The common ground and lessons learned from these approaches, with a view to the potential provision of much needed support to real-time applications in MANETs, is therefore discussed

PCN based admission control for autonomic video quality differentiation: design and evaluation

The popularity of multimedia services has introduced important new challenges for broadband access network management. As these services are very prone to network anomalies such as packet loss and jitter, accurate admission control mechanisms are needed to avoid congestion. Traditionally, centralized admission control mechanisms often underperform in combination with multimedia services, as they fail to effectively characterize the amount of needed resources. Recently, measurement based admission control mechanisms have been proposed such as the IETF Pre-Congestion Notification (PCN) mechanism, where the network load is measured at each intermediate node and signaled to the edge, where the admittance decision takes place. In this article, we design a PCN based admission control mechanism, optimized for protecting bursty traffic such as video services, which is currently not studied in the PCN working group. We evaluated and identified the effect of PCN's configuration in protecting bursty traffic. The proposed admission control mechanism features three main improvements to the original PCN mechanism: first, it uses a new measurement algorithm, which is easier to configure for bursty traffic. Second, it allows to automatically adapt PCN's configuration based on the traffic characteristics of the current sessions. Third, it introduces the differentiation between video quality levels to achieve an admission decision per video quality level of each request. The mechanism has been extensively evaluated in a packet switched simulation environment, which shows that the novel admission control mechanism is able to protec

Policy-based QoS management framework for software-defined networks

With the emerging trends of virtualization of cloud computing and big data applications, network management has become a challenging problem for optimizing the network state while satisfying the applications’ Quality of Service (QoS) requirements. This paper proposes a policy-based management framework over Software-Defined Networks (SDN) for QoS provisioning. The proposed approach monitors the QoS parameters of the active flows and dynamically enforces new decisions on the underlying SDN switches to adapt the network state to the current demanded high-level policies. Moreover, the proposed solution makes use of Neural Networks to identify the violating flows causing the network congestion. Upon detection of a policy violation two route management techniques are implemented, such as: rerouting and rate limiting. The proposed framework was implemented and evaluated within an experimental test bed setup. The results indicate that the proposed PBNM-based SDN framework enables QoS provisioning and outperforms the default SDN in terms of throughput, packet loss rate and latency

Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

Increasing efficiency and quality demands of modern Internet technologies drive today’s network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature

Policy-based QoS management framework for software-defined networks

With the emerging trends of virtualization of cloud computing and big data applications, network management has become a challenging problem for optimizing the network state while satisfying the applications’ Quality of Service (QoS) requirements. This paper proposes a policy-based management framework over Software-Defined Networks (SDN) for QoS provisioning. The proposed approach monitors the QoS parameters of the active flows and dynamically enforces new decisions on the underlying SDN switches to adapt the network state to the current demanded high-level policies. Moreover, the proposed solution makes use of Neural Networks to identify the violating flows causing the network congestion. Upon detection of a policy violation two route management techniques are implemented, such as: rerouting and rate limiting. The proposed framework was implemented and evaluated within an experimental test bed setup. The results indicate that the proposed PBNM-based SDN framework enables QoS provisioning and outperforms the default SDN in terms of throughput, packet loss rate and latency