Automating Performance Diagnosis in Networked Systems

Diagnosing performance degradation in distributed systems is a complex and difficult task. Software that performs well in one environment may be unusably slow in another, and determining the root cause is time-consuming and error-prone, even in environments in which all the data may be available. End users have an even more difficult time trying to diagnose system performance, since both software and network problems have the same symptom: a stalled application. The central thesis of this dissertation is that the source of performance stalls in a distributed system can be automatically detected and diagnosed with very limited information: the dependency graph of data flows through the system, and a few counters common to almost all data processing systems. This dissertation presents FlowDiagnoser, an automated approach for diagnosing performance stalls in networked systems. FlowDiagnoser requires as little as two bits of information per module to make a diagnosis: one to indicate whether the module is actively processing data, and one to indicate whether the module is waiting on its dependents. To support this thesis, FlowDiagnoser is implemented in two distinct environments: an individual host's networking stack, and a distributed streams processing system. In controlled experiments using real applications, FlowDiagnoser correctly diagnoses 99% of networking-related stalls due to application, connection-specific, or network-wide performance problems, with a false positive rate under 3%. The prototype system for diagnosing messaging stalls in a commercial streams processing system correctly finds 93% of message-processing stalls, with a false positive rate of 2%

Infrared spectroscopy of hole doped ABA-stacked trilayer graphene

Using infrared spectroscopy, we investigate bottom gated ABA-stacked trilayer graphene subject to an additional environment-induced p-type doping. We find that the Slonczewski-Weiss-McClure tight-binding model and the Kubo formula reproduce the gate voltage-modulated reflectivity spectra very accurately. This allows us to determine the charge densities and the potentials of the {\pi}-band electrons on all graphene layers separately and to extract the interlayer permittivity due to higher energy bands.Comment: 6 pages, 6 figures Corrected sign of fig 3 and visibilty of fig

The doubling of the frame - Visual art and discourse

Natalie Edwards, Ben McCann and Peter Poian

Predicted long-term mortality reduction associated with the second round of breast screening in East Anglia

Randomized trials have demonstrated that mammographic screening can reduce breast cancer mortality. Our aim was to estimate the reduction in mortality expected from the East Anglian breast screening programme. Breast screening achieves benefit by improving cancer prognosis (reducing tumour size, nodal involvement and possibly grade) through earlier diagnosis. We compared cancer prognosis between women invited for screening and those not yet invited in East Anglia, UK, in order to predict the mortality reduction achievable by screening, independently of any reduction due to changes in treatment and underlying disease. Participants (both invited and not-yet invited) were women eligible for invitation to first and second screens and diagnosed with invasive breast cancer in 1989–96. Death rates were predicted based on the observed distribution of tumour grade, size and node status amongst 950 cancers diagnosed following first invitation, up to and including at second screen (excluding those detected at first screening), and 451 cancers presenting symptomatically in women awaiting first invitation during the staggered introduction of screening, after adjustment for lead time amongst screen detected cases. For all ages, the ratio of predicted breast cancer mortality in the invited compared with the uninvited group was 0.85 (95% CI 0.78, 0.93). It was 0.93 (0.80, 1.08) for women aged 50–54 at diagnosis and 0.81 (0.72, 0.91) for those aged 55–64. We conclude that, by 2004, the second round of screening in East Anglia should reduce mortality by around 7% in women below age 55 at diagnosis, and by around 19% in those aged 55–64. © 2001 Cancer Research Campaign http://www.bjcancer.co

A Secure Integrated Framework for Fog-Assisted Internet of Things Systems

Fog-Assisted Internet of Things (Fog-IoT) systems are deployed in remote and unprotected environments, making them vulnerable to security, privacy, and trust challenges. Existing studies propose security schemes and trust models for these systems. However, mitigation of insider attacks, namely blackhole, sinkhole, sybil, collusion, self-promotion, and privilege escalation, has always been a challenge and mostly carried out by the legitimate nodes. Compared to other studies, this paper proposes a framework featuring attribute-based access control and trust-based behavioural monitoring to address the challenges mentioned above. The proposed framework consists of two components, the security component (SC) and the trust management component (TMC). SC ensures data confidentiality, integrity, authentication, and authorization. TMC evaluates Fog-IoT entities’ performance using a trust model based on a set of QoS and network communication features. Subsequently, trust is embedded as an attribute within SC’s access control policies, ensuring that only trusted entities are granted access to fog resources. Several attacking scenarios, namely DoS, DDoS, probing, and data theft are designed to elaborate on how the change in trust triggers the change in access rights and, therefore, validates the proposed integrated framework’s design principles. The framework is evaluated on a Raspberry Pi 3 Model B to benchmark its performance in terms of time and memory complexity. Our results show that both SC and TMC are lightweight and suitable for resource-constrained devices

Differentiating Violent and Non-Violent Extremists: Lessons from 70 Years of Social Control Theory

P/CVE programs engaging in primary (prior to radicalization) or secondary (following exposure to radicalizing influences) prevention are often predicated on delivering interventions to individuals or groups at-risk of engaging in violent extremism. Preventative actions must take place before the potential negative outcome; however, additional research is still required to identify and empirically validate the factors that distinguish violent from non-violent extremists. In the interim, P/CVE programs have instead targeted all individuals within a community or those deemed “at-risk” of adhering to extremist belief systems or movements. Due to resource limitations, this approach dilutes the allocation of resources to individuals and/or communities with higher propensities for extremist violence and may incidentally increase the likelihood of violence. This paper argues that empirical and theoretical insights from criminological theories of social control can enhance the understanding of violent extremism and can be used to tailor P/CVE programs. Unlike most criminological theories, social control theories focus on why people do not commit these acts, giving it a unique perspective on identifying how to prevent violent extremism. Drawing on 70 years of research, we explore how variation in various forms of control can explain differences in extremist offending. We hypothesize how the antecedents to low social control may be connected to violent extremism and propose a research agenda to test these hypotheses. Finally, we examine how existing measures of self-control can be incorporated by P/CVE programming to better distribute services to their target population and reduce the risk of adverse outcomes

Application of the California Institute of Technology Electric Analog Computer to Nonlinear Mechanics and Servomechanisms

This paper describes the non-linear elements and circuit techniques used with the California Institute of Technology electric analog computer. Their application to nonlinear mechanical vibratory systems and nonlinear servomotors is discussed in detail. These techniques have been found to be generally suitable for representing single valued nonlinear functions of a dependent variable. Nonlinear springs, spring loaded backlash, and nonlinear damping factors can be readily simulated as well as saturation effects and other single valued non-linearities in servomotors. Methods of analysis are illustrated for several typical problems including a nonlinear rotating mechanical system and an autopilot employing a solenoid-operated rate and position limited hydraulic motor. Numerous servos of this type have now been studied and correlation of computer solutions with actual servo test data have shown in every case that the mathematical equations presented here accurately describe this type of motor