Measurement-based Policy-driven QoS Management in Converged Next Generation Networks

Policy-based management is considered an effective approach to address the challenges of resource management in large complex networks. Within the IU-ATC QoS Frameworks project, a policy-based network management framework, CNQF (Converged Networks QoS Framework) is being developed aimed at providing context-aware, end-to-end QoS control and resource management in converged next generation networks. CNQF is designed to provide homogeneous, transparent QoS control over heterogeneous access technologies by means of distributed functional entities that co-ordinate the resources of the transport network through policy-driven decisions. In this paper, we present a measurement-based evaluation of policy-driven QoS management based on CNQF architecture, with real traffic flows on an experimental testbed. A Java based implementation of the CNQF Resource Management Subsystem is deployed on the testbed and results of the experiments validate the framework operation for policy-based QoS management of real traffic flows.

Performance analysis of an improved power-saving medium access protocol for IEEE 802.11 point coordination function WLAN

Wireless enabled portable devices must operate with the highest possible energy efficiency while still maintaining a minimum level and quality of service to meet the user's expectations. The authors analyse the performance of a new pointer-based medium access control protocol that was designed to significantly improve the energy efficiency of user terminals in wireless local area networks. The new protocol, pointer controlled slot allocation and resynchronisation protocol (PCSAR), is based on the existing IEEE 802.11 point coordination function (PCF) standard. PCSAR reduces energy consumption by removing the need for power saving stations to remain awake and listen to the channel. Using OPNET, simulations were performed under symmetric channel loading conditions to compare the performance of PCSAR with the infrastructure power saving mode of IEEE 802.11, PCF-PS. The simulation results demonstrate a significant improvement in energy efficiency without significant reduction in performance when using PCSAR. For a wireless network consisting of an access point and 8 stations in power saving mode, the energy saving was up to 31% while using PCSAR instead of PCF-PS, depending upon frame error rate and load. The results also show that PCSAR offers significantly reduced uplink access delay over PCF-PS while modestly improving uplink throughput.

Improved power-saving medium access protocol for IEEE 802.11e QoS-enabled wireless networks

The performance of a new pointer-based medium-access control protocol that was designed to significantly improve the energy efficiency of user terminals in quality-of-service-enabled wireless local area networks was analysed. The new protocol, pointer-controlled slot allocation and resynchronisation protocol (PCSARe), is based on the hybrid coordination function-controlled channel access mode of the IEEE 802.11e standard. PCSARe reduces energy consumption by removing the need for power-saving stations to remain awake for channel listening. Discrete event network simulations were performed to compare the performance of PCSARe with the non-automatic power save delivery (APSD) and scheduled-APSD power-saving modes of IEEE 802.11e. The simulation results show a demonstrable improvement in energy efficiency without significant reduction in performance when using PCSARe. For a wireless network consisting of an access point and eight stations in power-saving mode, the energy saving was up to 39% when using PCSARe instead of IEEE 802.11e non-APSD. The results also show that PCSARe offers significantly reduced uplink access delay over IEEE 802.11e non-APSD, while modestly improving the uplink throughput. Furthermore, although both had the same energy consumption, PCSARe gave a 25% reduction in downlink access delay compared with IEEE 802.11e S-APSD.

Linear quadratic and tumour control probability modelling in external beam radiotherapy

The standard linear-quadratic (LQ) survival model for external beam radiotherapy is reviewed with particular emphasis on studying how different schedules of radiation treatment planning may be affected by different tumour repopulation kinetics. The LQ model is further examined in the context of tumour control probability (TCP) models. The application of the Zaider and Minerbo non-Poissonian TCP model incorporating the effect of cellular repopulation is reviewed. In particular the recent development of a cell cycle model within the original Zaider and Minerbo TCP formalism is highlighted. Application of this TCP cell-cycle model in clinical treatment plans is explored and analysed.

Cross-layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems

Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence,purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44%.

Cross-layer Framework for Fine-grained Channel Access in Next Generation High-density WiFi Networks

Densely deployed WiFi networks will play a crucial role in providing the capacity for next generation mobile internet. However, due to increasing interference, overlapped channels in WiFi networks and throughput efficiency degradation, densely deployed WiFi networks is not a guarantee to obtain higher throughput. An emergent challenge is how to efficiently utilize scarce spectrum resources, by matching physical layer resources to traffic demand. In this aspect, access control allocation strategies play a pivotal role but remain too coarse-grained. As a solution, this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in WiFi networks. This approach, named SFCA (Sub-carrier Fine-grained Channel Access), adopts DOFDM (Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer. It allocates the frequency resource with a sub-carrier granularity, which facilitates the channel width adaptation for multi-channel access and thus brings more flexibility and higher frequency efficiency. The MAC layer uses a frequency-time domain backoff scheme, which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision, resulting in higher access probability for the contending nodes. SFCA is compared with FICA (an established access scheme) showing significant outperformance. Finally we present results for next generation 802.11ac WiFi networks.

WLAN Security Processor

A novel wireless local area network (WLAN) security processor is described in this paper. It is designed to offload security encapsulation processing from the host microprocessor in an IEEE 802.11i compliant medium access control layer to a programmable hardware accelerator. The unique design, which comprises dedicated cryptographic instructions and hardware coprocessors, is capable of performing wired equivalent privacy, temporal key integrity protocol, counter mode with cipher block chaining message authentication code protocol, and wireless robust authentication protocol. Existing solutions to wireless security have been implemented on hardware devices and target specific WLAN protocols whereas the programmable security processor proposed in this paper provides support for all WLAN protocols and thus, can offer backwards compatibility as well as future upgrade ability as standards evolve. It provides this additional functionality while still achieving equivalent throughput rates to existing architectures. © 2006 IEEE.

Performance analysis of a metro WDM ring networks with variable-length packets under symmetric and asymmetric traffic

In this paper, we discuss and evaluate two proposed metro wavelength division multiplexing (WDM) ring network architectures for variable-length packet traffic in storage area networks (SANs) settings. The paper begins with a brief review of the relevant architectures and protocols in the literature. Subsequently, the network architectures along with their medium access control (MAC) protocols are described. Performance of the two network architectures is studied by means of computer simulation in terms of their queuing delay, node throughput and proportion of packets dropped. The network performance is evaluated under symmetric and asymmetric traffic scenarios with Poisson and self-similar traffic. (C) 2011 Elsevier Inc. All rights reserved.

Detecting Anomalies in Graphs with Numeric Labels

This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-related examples and validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, Yagada detects twice as many anomalies as the best-performing numeric discretization algorithm. Qualitative evaluation shows that the detected anomalies are meaningful, representing a com- bination of structural irregularities and numerical outliers.

White matter fractional anisotrophy predicts balance performance in older adults

Aging is characterized by brain structural changes that may compromise motor functions. In the context of postural control, white matter integrity is crucial for the efficient transfer of visual, proprioceptive and vestibular feedback in the brain. To determine the role of age-related white matter decline as a function of the sensory feedback necessary to correct posture, we acquired diffusion weighted images in young and old subjects. A force platform was used to measure changes in body posture under conditions of compromised proprioceptive and/or visual feedback. In the young group, no significant brain structure-balance relations were found. In the elderly however, the integrity of a cluster in the frontal forceps explained 21% of the variance in postural control when proprioceptive information was compromised. Additionally, when only the vestibular system supplied reliable information, the occipital forceps was the best predictor of balance performance (42%). Age-related white matter decline may thus be predictive of balance performance in the elderly when sensory systems start to degrade.

The Impact of EU Privacy Legislation on Biometric System Deployment: Protecting citizens but constraining applications

Biometric systems provide a valuable service in helping to identify individuals from their stored personal details. Unfortunately, with the rapidly increasing use of such systems, there is a growing concern about the possible misuse of that information. To counteract the threat, the European Union (EU) has introduced comprehensive legislation that seeks to regulate data collection and help strengthen an individual’s right to privacy. This article looks at the implications of the legislation for biometric system deployment. After an initial consideration of current privacy concerns, it examines what is meant by ‘personal data’ and its protection, in legislation terms. Also covered are issues around the storage of biometric data, including its accuracy, its security, and justification for what is collected. Finally, the privacy issues are illustrated through three biometric use cases: border security, online bank access control and customer profiling in stores.

Contextual anomaly detection in crowded surveillance scenes

This work addresses the problem of detecting human behavioural anomalies in crowded surveillance environments. We focus in particular on the problem of detecting subtle anomalies in a behaviourally heterogeneous surveillance scene. To reach this goal we implement a novel unsupervised context-aware process. We propose and evaluate a method of utilising social context and scene context to improve behaviour analysis. We find that in a crowded scene the application of Mutual Information based social context permits the ability to prevent self-justifying groups and propagate anomalies in a social network, granting a greater anomaly detection capability. Scene context uniformly improves the detection of anomalies in both datasets. The strength of our contextual features is demonstrated by the detection of subtly abnormal behaviours, which otherwise remain indistinguishable from normal behaviour.

Multidimensional Intrusion Detection System for IEC 61850 based SCADA Networks

Emerging cybersecurity vulnerabilities in supervisory control and data acquisition (SCADA) systems are becoming urgent engineering issues for modern substations. This paper proposes a novel intrusion detection system (IDS) tailored for cybersecurity of IEC 61850 based substations. The proposed IDS integrates physical knowledge, protocol specifications and logical behaviours to provide a comprehensive and effective solution that is able to mitigate various cyberattacks. The proposed approach comprises access control detection, protocol whitelisting, model-based detection, and multi-parameter based detection. This SCADA-specific IDS is implemented and validated using a comprehensive and realistic cyber-physical test-bed and data from a real 500kV smart substation.

A Capabilities-Aware Framework for Using Computational Accelerators in Data-Intensive Computing

Multicore computational accelerators such as GPUs are now commodity components for highperformance computing at scale. While such accelerators have been studied in some detail as stand-alone computational engines, their integration in large-scale distributed systems raises new challenges and trade-offs. In this paper, we present an exploration of resource management alternatives for building asymmetric accelerator-based distributed systems. We present these alternatives in the context of a capabilities-aware framework for data-intensive computing, which uses an enhanced implementation of the MapReduce programming model for accelerator-based clusters, compared to the state of the art. The framework can transparently utilize heterogeneous accelerators for deriving high performance with low programming effort. Our work is the first to compare heterogeneous types of accelerators, GPUs and a Cell processors, in the same environment and the first to explore the trade-offs between compute-efficient and control-efficient accelerators on data-intensive systems. Our investigation shows that our framework scales well with the number of different compute nodes. Furthermore, it runs simultaneously on two different types of accelerators, successfully adapts to the resource capabilities, and performs 26.9% better on average than a static execution approach.