Dynamic QoS optimization architecture for cloud-based DDDAS

Cloud computing urges the need for novel on-demand approaches, where the Quality of Service (QoS) requirements of cloud-based services can dynamically and adaptively evolve at runtime as Service Level Agreement (SLA) and environment changes. Given the unpredictable, dynamic and on-demand nature of the cloud, it would be unrealistic to assume that optimal QoS can be achieved at design time. As a result, there is an increasing need for dynamic and self- adaptive QoS optimization solutions to respond to dynamic changes in SLA and the environment. In this context, we posit that the challenge of self-adaptive QoS optimization encompasses two dynamics, which are related to QoS sensitivity and conflicting objectives at runtime. We propose novel design of a dynamic data-driven architecture for optimizing QoS influenced by those dynamics. The architecture leverages on DDDAS primitives by employing distributed simulations and symbiotic feedback loops, to dynamically adapt decision making metaheuristics, which optimizes for QoS tradeoffs in cloud-based systems. We use a scenario to exemplify and evaluate the approach

Efficiently Handling Skew in Outer Joins on Distributed Systems

Outer joins are ubiquitous in databases and big data systems. The question of how best to execute outer joins in large parallel systems is particularly challenging as real world datasets are characterized by data skew leading to performance issues. Although skew handling techniques have been extensively studied for inner joins, there is little published work solving the corresponding problem for parallel outer joins. Conventional approaches to this problem such as ones based on hash redistribution often lead to load balancing problems while duplication-based approaches incurs significant overhead in terms of network communication. In this paper, we propose a new algorithm, query with counters (QC), for directly handling skew in outer joins on distributed architectures. We present an efficient implementation of our approach based on the asynchronous partitioned global address space (APGAS) parallel programming model. We evaluate the performance of our approach on a cluster of 192 cores (16 nodes) and datasets of 1 billion tuples with different skew. Experimental results show that our method is scalable and, in cases of high skew, faster than the state-of-the-art

Design and evaluation of parallel hashing over large-scale data

High-performance analytical data processing systems often run on servers with large amounts of memory. A common data structure used in such environment is the hash tables. This paper focuses on investigating efficient parallel hash algorithms for processing large-scale data. Currently, hash tables on distributed architectures are accessed one key at a time by local or remote threads while shared-memory approaches focus on accessing a single table with multiple threads. A relatively straightforward “bulk-operation” approach seems to have been neglected by researchers. In this work, using such a method, we propose a high-level parallel hashing framework, Structured Parallel Hashing, targeting efficiently processing massive data on distributed memory. We present a theoretical analysis of the proposed method and describe the design of our hashing implementations. The evaluation reveals a very interesting result - the proposed straightforward method can vastly outperform distributed hashing methods and can even offer performance comparable with approaches based on shared memory supercomputers which use specialized hardware predicates. Moreover, we characterize the performance of our hash implementations through extensive experiments, thereby allowing system developers to make a more informed choice for their high-performance applications

Exact-Differential Large-Scale Traffic Simulation

Analyzing large-scale traffics by simulation needs repeating execution many times with various patterns of scenarios or parameters. Such repeating execution brings about big redundancy because the change from a prior scenario to a later scenario is very minor in most cases, for example, blocking only one of roads or changing the speed limit of several roads. In this paper, we propose a new redundancy reduction technique, called exact-differential simulation, which enables to simulate only changing scenarios in later execution while keeping exactly same results as in the case of whole simulation. The paper consists of two main efforts: (i) a key idea and algorithm of the exact-differential simulation, (ii) a method to build large-scale traffic simulation on the top of the exact-differential simulation. In experiments of Tokyo traffic simulation, the exact-differential simulation shows 7.26 times as much elapsed time improvement in average and 2.26 times improvement even in the worst case as the whole simulation

Towards large-scale what-if traffic simulation with exact-differential simulation

To analyze and predict a behavior of large-scale traffics with what-if simulation, it needs to repeat many times with various patterns of what-if scenarios. In this paper, we propose new techniques to efficiently repeat what-if simulation tasks with exact-differential simulation. The paper consists of two main efforts: what-if scenario filtering and exact-differential cloning. The what-if scenario filtering enables to pick up meaningful what-if scenarios and reduces the number of what-if scenarios, which directly decreases total execution time of repeating. The exact-differential cloning enables to execute exact-differential simulation tasks in parallel to improve its total execution time. In our preliminary evaluation in Tokyo bay area's traffic simulation, we show potential of our proposals by estimating how the what-if scenarios filtering reduces the number of meaningless scenarios and also by estimating a performance improvement from our previous works with the exact-differential cloning

Spin Waves in Disordered III-V Diluted Magnetic Semiconductors

We propose a new scheme for numerically computing collective-mode spectra for large-size systems, using a reformulation of the Random Phase Approximation. In this study, we apply this method to investigate the spectrum and nature of the spin-waves of a (III,Mn)V Diluted Magnetic Semiconductor. We use an impurity band picture to describe the interaction of the charge carriers with the local Mn spins. The spin-wave spectrum is shown to depend sensitively on the positional disorder of the Mn atoms inside the host semiconductor. Both localized and extended spin-wave modes are found. Unusual spin and charge transport is implied.Comment: 14 pages, including 11 figure

Sleep in Frontotemporal Dementia is Equally or Possibly More Disrupted, and at an Earlier Stage, When Compared to Sleep in Alzheimer's Disease

Background: Conversely to other neurodegenerative diseases (i.e., Alzheimer's disease, AD), sleep in frontotemporal dementia (FTD) has not been studied adequately. Although some evidence exists that sleep-wake disturbances occur in FTD, very little is known regarding sleep macrostructure and/or primary sleep disorders. Objective: To investigate these issues in this population and compare them to similar issues in AD and in healthy elderly (HE). Methods: Twelve drug-naïve behavioral-variant FTD (bvFTD) patients (7 men/5 women) of mean age 62.5 ± 8.6 years were compared to seventeen drug-naïve AD patients (9 men/8 women) of mean age 69.0 ± 9.9 years and twenty drug-naïve HE (12 men/8 women) of mean age 70.2 ± 12.5 years. All participants were fully assessed clinically, through a sleep questionnaire, an interview, and video-polysomnography recordings. Results: The two patient groups were comparably cognitively impaired. However, compared to FTD patients, the AD patients had a statistically significant longer disease duration. Overall, the sleep profile was better preserved in HE. Sleep complaints did not differ considerably between the two patient groups. Sleep parameters and sleep macrostructure were better preserved in AD compared to FTD patients, regardless of primary sleep disorders, which occurred equally in the two groups. Conclusions: With respect to AD, FTD patients had several sleep parameters similarly or even more affected by neurodegeneration, but in a much shorter time span. The findings probably indicate a centrally originating sleep deregulation. Since in FTD patients sleep disturbances may be obvious from an early stage of their disease, and possibly earlier than in AD patients, physicians and caregivers should be alert for the early detection and treatment of these symptoms

On interconnecting and orchestrating components in disaggregated data centers:The dReDBox project vision

Computing systems servers-low-or high-end ones have been traditionally designed and built using a main-board and its hardware components as a 'hard' monolithic building block; this formed the base unit on which the system hardware and software stack design build upon. This hard deployment and management border on compute, memory, network and storage resources is either fixed or quite limited in expandability during design time and in practice remains so throughout machine lifetime as subsystem upgrades are seldomely employed. The impact of this rigidity has well known ramifications in terms of lower system resource utilization, costly upgrade cycles and degraded energy proportionality. In the dReDBox project we take on the challenge of breaking the server boundaries through materialization of the concept of disaggregation. The basic idea of the dReDBox architecture is to use a core of high-speed, low-latency opto-electronic fabric that will bring physically distant components more closely in terms of latency and bandwidth. We envision a powerful software-defined control plane that will match the flexibility of the system to the resource needs of the applications (or VMs) running in the system. Together the hardware, interconnect, and software architectures will enable the creation of a modular, vertically-integrated system that will form a datacenter-in-a-box

TCT-481 Treatment of "resistant" in-stent restenosis in the drug-eluting era: comparison of repeat stent versus balloon only strategy

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