The advances in computing and communication technologies and software tools have resulted in an explosive growth in networked applications and information services that cover all aspects of our life. These services and applications are inherently complex, dynamic and heterogeneous. In a similar way, the underlying information infrastructure, e.g. the Internet, is large, complex, heterogeneous and dynamic, globally aggregating large numbers of independent computing and communication resources. The combination of the two results in application development and management complexities that break current computing paradigms, which are based on static behaviors. As a result, applications, programming environments and information infrastructures are rapidly becoming fragile, unmanageable and insecure. This has led researchers to consider alternative programming paradigms and management techniques that are based on strategies used by biological systems. Autonomic programming paradigm is inspired by the human autonomic nervous system that handles complexity, uncertainties and abnormality. The overarching goal of the autonomic programming paradigm is to help building systems and applications capable of self-management. Firstly, we investigated the large-scale scientific computing applications which generally experience different execution phases at run time and each phase has different computational, communication and storage requirements as well as different physical characteristics. In this dissertation, we present Physics Aware Optimization (PAO) paradigm that enables programmers to identify the appropriate solution methods to exploit the heterogeneity and the dynamism of the application execution states. We implement a Physics Aware Optimization Manager to exploit the PAO paradigm. On the other hand we present a self configuration paradigm based on the principles of autonomic computing that can handle efficiently complexity, dynamism and uncertainty in configuring server and networked systems and their applications. Our approach is based on making any resource/application to operate as an Autonomic Component (that means it can be self-managed component) by using our autonomic programming paradigm. Our POA technique for medical application yielded about 3X improvement of performance with 98.3% simulation accuracy compared to traditional techniques for performance optimization. Also, our Self-configuration management for power and performance management in GPU cluster demonstrated 53.7% power savings for CUDAworkload while maintaining the cluster performance within given acceptable thresholds.

With the rapid growth of servers and applications spurred by the Internet economy, power consumption in today's data centers is reaching unsustainable limits. This has led to an imminent financial, technical and environmental crisis that is impacting the society at large. Hence, it has become critically important that power consumption be efficiently managed in these computing power-houses of today. In this work, we revisit the issue of adaptive power and performance management of data center server platforms. Traditional data center servers are statically configured and always over-provisioned to be able to handle peak load. We transform these statically configured data center servers to clairvoyant entities that can sense changes in the workload and dynamically scale in capacity to adapt to the requirements of the workload. The over-provisioned server capacity is transitioned to low-power states and they remain in those states for as long as the performance remains within given acceptable thresholds. The platform power expenditure is minimized subject to performance constraints. This is formulated as a performance-per-watt optimization problem and solved using analytical power and performance models. Coarse-grained optimizations at the platform-level are refined by local optimizations at the devices-level namely - the processor & memory subsystems. Our adaptive interleaving technique for memory power management yielded about 48.8% (26.7 kJ) energy savings compared to traditional techniques measured at 4.5%. Our adaptive platform power and performance management technique demonstrated 56.25% energy savings for memory-intensive workload, 63.75% savings for processor-intensive workload and 47.5% savings for a mixed workload while maintaining platform performance within given acceptable thresholds.

Distributed systems, characterized by their ability to ensure the execution of multiple transactions across a myriad of applications, constitute a prime platform for building Web applications. However, Web application interactions raise issues pertaining to security and performance that make manual security management both time-consuming and challenging. This thesis is a testimony to the security and performance enhancements afforded by using the autonomic computing paradigm to design an adaptive cryptographic access control framework for dynamic data sharing environments. One of the methods of enforcing cryptographic access control in these environments is to classify users into one of several groups interconnected in the form of a partially ordered set. Each group is assigned a single cryptographic key that is used for encryption/decryption. Access to data is granted only if a user holds the "correct" key, or can derive the required key from the one in their possession. This approach to access control is a good example of one that provides good security but has the drawback of reacting to changes in group membership by replacing keys, and re-encrypting the associated data, throughout the entire hierarchy. Data re-encryption is time-consuming, so, rekeying creates delays that impede performance. In order to support our argument in favor of adaptive security, we begin by presenting two cryptographic key management (CKM) schemes in which key updates affect only the class concerned or those in its sub-poset. These extensions enhance performance, but handling scenarios that require adaptability remain a challenge. Our framework addresses this issue by allowing the CKM scheme to monitor the rate at which key updates occur and to adjust resource (keys and encrypted data versions) allocations to handle future changes by anticipation rather than on demand. Therefore, in comparison to quasi-static approaches, the adaptive CKM scheme minimizes the long-term cost of key updates. Finally, since self-protecting CKM requires a lesser degree of physical intervention by a human security administrator, we consider the case of "collusion attacks" and propose two algorithms to detect as well as prevent such attacks. A complexity and security analysis show the theoretical improvements our schemes offer. Each algorithm presented is supported by a proof of concept implementation, and experimental results to show the performance improvements. / Thesis (Ph.D, Computing) -- Queen's University, 2008-10-16 16:19:46.617

As the use of Web expands, Web Service is gradually becoming the basic system infrastructure. However, as it matures and a large number of Web Service becomes available, the focus will shift from service development to service management. One key component in management systems is monitoring. The growing complexity of Web Service platforms and their dynamically varying workloads make manually monitoring them a demanding task. Therefore monitoring tools are required to support the management efforts. Our approach, Web Service Monitoring System (WSMS), utilizes Autonomic Computing technology to monitor Web Service for an automated manager. WSMS correlates lower level events into a meaningful diagnosed symptom which provides higher level information for problem determination. It also gains the ability to take autonomic actions and solve the original problem using corrective actions. In this thesis, a complete design of WSMS is presented along with a practical implementation showing viability and proof of concept of WSMS. / Thesis (Master, Computing) -- Queen's University, 2008-11-12 16:20:13.738

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The first chapter of this thesis consists in a critical review of the literature on cardiac and cardiac-related autonomic activity, and infant development. Empirical findings are presented on mechanisms of interaction between heart rate and the autonomic nervous system; their relationship with infant development; their genetic and environmental influences; their gender effects; and related quantification issues. / This is followed by a study of 322 5-month-old twin pairs that investigated the genetic and environmental influences on sleeping heart rate and cardiac-related autonomic activity, as indexed by spectral analysis of heart rate variability and response to postural change. The postural change elicited only minor changes in cardiovascular activity, perhaps due to immaturity of the baroreflex. As a result, analyses focused on supine cardiovascular activity. Multivariate genetic modeling indicated that individual differences in sleeping HR and high frequency HR variability were determined by unique environmental and distinct additive genetic factors. These variables, along with low frequency HR variability, were also affected by overlapping familial environmental influences. Familial influences on individual differences in high frequency HR variability were more pronounced for baby girls than boys. Estimates of relative low and high frequency HR variability were determined by common (familial) and unique environmental factors; familial influences on these estimates of HR variability did not overlap with familial influences on sleeping HR. / A second study using the same twin sample is then presented. Its objectives were to investigate the indices of genetic and environmental etiology of individual differences in five month-old twins' HR reactivity and to evaluate the possible overlap, if any, between the familial influences on HR in states of sleep and reactivity. Multivariate genetic modeling showed that the total variance of individual differences was decomposed in the following manner: Sleeping and awake HR were under the influence of shared additive genetic factors; sleeping HR also shared common environmental influences with the absolute power spectrum values; and absolute high frequency power additionally had phenotype-specific additive genetic factors influencing its expression. Relative power spectrum values were under the influence of phenotype-specific common environmental factors. / Overall, these results suggest the presence of important familial (genetic and environmental) influences on heart rate and cardiac-related autonomic activity at five months of age: There is an absence of overlap of these (familial) additive genetic influences but the presence of a partial overlap of the (familial) environmental influences.

Introduction Heart rate variability (HRV) is regarded as a useful, non-invasive method for investigating the autonomic nervous system (ANS). Over the past decade there has been an increase in the number of HRV investigations in the disciplines of medical, sport and exercise science. Despite the extensive use of HRV in investigations of ANS functioning, there are questions relating to the reliability of the technique. Therefore, HRV reliability studies for different population groups have been advocated. Furthermore, research on gender differences in HRV is contradictory. This has resulted in the need to investigate gender characteristics in HRV. Objectives The objective of this study was to evaluate the reliability of short-term (5min) recordings of HRV, and to determine the association between HRV and gender. Methods Forty four physically active students (n= 21, age= 21.17 (1.55) males and n=23, age= 19.75 (1.76) females) participated in the study. Heart rate variability parameters were determined from five minute recording of interbeat intervals (IBI) using a Suunto t6 heart rate monitor (HRM). Testing was repeated over 4 consecutive days under the same conditions. The following HRV time and frequency domain measures were calculated using Kubios HRV Software Version 2.0: mean heart rate (HR), standard deviation of normal to normal intervals (SDNN), root mean square of successive differences (RMSSD), percentage of beats that changed more than 50 ms from the previous beat (pNN50), low frequency in normalized units (LFnu), high frequency in normalized units (HFnu) and low frequency to high frequency ratio in normalized units (LF/HFnu ratio). The data was summarized using routine descriptive statistics. Relative reliability was calculated using interclass correlation coefficients (ICC) (ICC of >0.80 indicated good to excellent reliability) and absolute reliability using typical error of measurement (TEM) and TEM as a percentage of the mean score (TEM%). This statistical measures were computed for days 2 vs 3 (REL 1), 3 vs 4 (REL 2). Day 1 was used as a familiarization day. An unpaired T-test was used to determine whether there were any differences between males and females for the above HRV parameters. Significance was set at p .0.05. Results The ICCs for both REL 1 and REL 2 indicated good to excellent (ICC >0.8) reliability for IBIs and pNN50 for the time domain results. In general, the time domain results had a higher relative reliability than the frequency domain results. Males had an overall lower relative reliability than females for frequency domain parameters. Absolute reliability for REL 2 showed a slightly lower TEM value as compared to REL 1.The largest gender differences in TEM were seen in the frequency domain parameters. Specifically, for males, the TEM was higher than females for the LF/HFnu ratio (REL 2: 116%), the HFnu (REL 1: 90%) and the LFnu (REL 1: 68%). Overall the TEM% was relatively high in most HRV parameters specifically for LF/HFnu (REL 1: 31.4% females and 48.1% males; REL 2: 29.7% females and 40.4% males). These findings indicate that males have decreased absolute reliability compared to females and that random error is greater in men for the frequency domain parameters. Gender differences illustrated significant differences for resting HR (16% higher in females (p < 0.0001)), IBIs (21% higher in females (p <0.0001)) and LF/HFnu ratio (41% higher in males (p = 0.003)). The findings indicate that females have higher total HRV. Conclusions Short term recordings of HRV over consecutive days using the Suunto t6 HRM and Kubios custom HRV software are reliable depending on the HRV parameter being analysed. Overall, the relative reliability results suggest that HRV using the Suunto t6 and Kubios is good. However, the absolute reliability results suggest low reliability. In particular, males demonstrated a poorer absolute reliability (high TEM and TEM%) than females, suggesting a larger day to day random error in males. Furthermore, specific HRV measures differed between males and females demonstrating that females have higher parasympathetic modulation compared to men. The overall higher HRV in females could explain the possible cardio-protective mechanism observed in premenopausal women. Key words: Heart rate variability, Parasympathetic, Reliability, Interbeat Intervals / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2011.

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Apart from motor and sensory function loss, an injury to the spinal cord can cause sympathetic dysfunction, which has been shown to affect immune responses. In this thesis, data from five experimental studies have been collected to compare physiological and psychophysiological exercise responses between wheelchair athlete subgroups with different disabilities (tetraplegic, paraplegic, and non-spinal cord-injured). In two preparatory studies, physiological exercise responses to exhaustive (Chapter 4) and submaximal exercise (Chapter 5) were investigated in all three disability subgroups. Whilst reliability measures for peak oxygen uptake (VO2peak) were in a range observed previously in able-bodied athletes, the variation in tetraplegic athletes was larger when expressed relative to their VO2peak, questioning the use of this variable to track small changes in aerobic capacity in athletic populations. Submaximal physiological and psychophysiological exercise responses were found to be similar between disability subgroups when expressed as a percentage of VO2peak, justifying the protocol used in the laboratory study on mucosal immune function, which was based on the same percentages of VO2peak for all disability subgroups. The most extensive study of this thesis, detailed in Chapter 6, showed that single laboratory-controlled 60-min exercise sessions increase both salivary secretory immunoglobulin A (sIgA), a marker of mucosal immunity, and α-amylase, a marker of sympathetic activation in all three disability subgroups. However, the impaired sympathetic nervous system in tetraplegic athletes seemed to influence the fine-tuning of their sIgA response when compared with paraplegic and non-spinal cord-injured athletes, resulting in a larger exercise-induced increase of sIgA secretion rate when compared to paraplegic and non-spinal cord-injured athletes. Based on these results, the study detailed in Chapter 7 investigated sIgA responses in tetraplegic athletes during wheelchair rugby court training. Despite their disability, these athletes showed responses thought to be governed by the sympathetic nervous system, such as reductions of saliva flow rate as a result of strenuous exercise. Similarly, the responses observed in Chapter 8 imply a comparable trend of chronic sIgA exercise responses in tetraplegic athletes as found in the able-bodied population, namely a decrease in sIgA secretion rate during periods of heavy training. These are the first studies in wheelchair athlete populations to investigate mucosal immune responses. Interestingly, despite the disruption of their sympathetic nervous system, some responses in tetraplegic athletes are comparable with findings in able-bodied populations. It is possible that due to their highly trained nature, these tetraplegic individuals are able to compensate for their loss of central sympathetic innervation. This may be by way of adapted spinal reflex or parasympathetic nervous system activity, or increased sensitivity of receptors involved in autonomic pathways. Therefore, sympathetic nervous function in tetraplegic athletes may be qualitatively altered, but in parts still be functional.

Cardiovascular control in the human is significantly impaired after spinal cord injury(SCI) having a direct effect on the sympathetic nervous system (SNS) causing an inability toregulate vasoconstriction below the level of the lesion. The effects of SCI on the two majorcomponents of blood pressure regulation, control of plasma volume and neural control of theheart and peripheral vasculature are poorly understood. In particular, no index to diagnosedisorders to autonomic control of the heart and vasculature has been developed. The presentstudy primarily utilized noninvasively acquired, easily accessible variables that may havepromise as indicators of autonomic activity for assessing the level of autonomic injury andrecovery of visceral control following SCI. The most significant results and the clearestdifferences between the three groups (able-bodied, paraplegic and tetraplegic) were evident inspectral analysis obtained in the frequency domain: Arterial blood pressure and lower body (at aregion on the shin) skin perfusion spectral power in the low frequency (LF) region are ofsignificance. These variables could be good discriminators of the three groups, as well as showlevel of SCI and autonomic function.