Generating Representative Web Workloads for Network and Server Performance Evaluation

One role for workload generation is as a means for understanding how servers and networks respond to variation in load. This enables management and capacity planning based on current and projected usage. This paper applies a number of observations of Web server usage to create a realistic Web workload generation tool which mimics a set of real users accessing a server. The tool, called Surge (Scalable URL Reference Generator) generates references matching empirical measurements of 1) server file size distribution; 2) request size distribution; 3) relative file popularity; 4) embedded file references; 5) temporal locality of reference; and 6) idle periods of individual users. This paper reviews the essential elements required in the generation of a representative Web workload. It also addresses the technical challenges to satisfying this large set of simultaneous constraints on the properties of the reference stream, the solutions we adopted, and their associated accuracy. Finally, we present evidence that Surge exercises servers in a manner significantly different from other Web server benchmarks.

Improving the Performance of Overlay Routing and P2P File Sharing using Selfish Neighbor Selection

A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into the existing mesh and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are tractable to address via theoretical analyses, especially game-theoretic analysis. Our work unifies these two thrusts first by distilling insights gleaned from clean theoretical models, notably that under natural resource constraints, selfish players can select neighbors so as to efficiently reach near-equilibria that also provide high global performance. Using Egoist, a prototype overlay routing system we implemented on PlanetLab, we demonstrate that our neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics; that Egoist is competitive with an optimal, but unscalable full-mesh approach; and that it remains highly effective under significant churn. We also describe variants of Egoist's current design that would enable it to scale to overlays of much larger scale and allow it to cater effectively to applications, such as P2P file sharing in unstructured overlays, based on the use of primitives such as scoped-flooding rather than routing.

Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins.

As many as 20-70% of patients undergoing breast conserving surgery require repeat surgeries due to a close or positive surgical margin diagnosed post-operatively [1]. Currently there are no widely accepted tools for intra-operative margin assessment which is a significant unmet clinical need. Our group has developed a first-generation optical visible spectral imaging platform to image the molecular composition of breast tumor margins and has tested it clinically in 48 patients in a previously published study [2]. The goal of this paper is to report on the performance metrics of the system and compare it to clinical criteria for intra-operative tumor margin assessment. The system was found to have an average signal to noise ratio (SNR) >100 and <15% error in the extraction of optical properties indicating that there is sufficient SNR to leverage the differences in optical properties between negative and close/positive margins. The probe had a sensing depth of 0.5-2.2 mm over the wavelength range of 450-600 nm which is consistent with the pathologic criterion for clear margins of 0-2 mm. There was <1% cross-talk between adjacent channels of the multi-channel probe which shows that multiple sites can be measured simultaneously with negligible cross-talk between adjacent sites. Lastly, the system and measurement procedure were found to be reproducible when evaluated with repeated measures, with a low coefficient of variation (<0.11). The only aspect of the system not optimized for intra-operative use was the imaging time. The manuscript includes a discussion of how the speed of the system can be improved to work within the time constraints of an intra-operative setting.

Neuromuscular-skeletal constraints on the acquisition of skill in a discrete torque production task

The organisation of the human neuromuscular-skeletal system allows an extremely wide variety of actions to be performed, often with great dexterity. Adaptations associated with skill acquisition occur at all levels of the neuromuscular-skeletal system although all neural adaptations are inevitably constrained by the organisation of the actuating apparatus (muscles and bones). We quantified the extent to which skill acquisition in an isometric task set is influenced by the mechanical properties of the muscles used to produce the required actions. Initial performance was greatly dependent upon the specific combination of torques required in each variant of the experimental task. Five consecutive days of practice improved the performance to a similar degree across eight actions despite differences in the torques required about the elbow and forearm. The proportional improvement in performance was also similar when the actions were performed at either 20 or 40% of participants' maximum voluntary torque capacity. The skill acquired during practice was successfully extrapolated to variants of the task requiring more torque than that required during practice. We conclude that while the extent to which skill can be acquired in isometric actions is independent of the specific combination of joint torques required for target acquisition, the nature of the kinetic adaptations leading to the performance improvement in isometric actions is influenced by the neural and mechanical properties of the actuating muscles.

Interaction of directional, neuromuscular and egocentric constraints on the stability of preferred bimanual coordination patterns

We investigated how the relative direction of limb movements in external space (iso- and non-isodirectionality), muscular constraints (the relative timing of homologous muscle activation) and the egocentric frame of reference (moving simultaneously toward/away the longitudinal axis of the body) contribute to the stability of coordinated movements. In the first experiment, we attempted to determine the respective stability of isodirectional and non-isodirectional movements in between-persons coordination. In a second experiment, we determined the effect of the relative direction in external space, and of muscular constraints, on pattern stability during a within-person bimanual coordination task. In the third experiment we dissociated the effects on pattern stability of the muscular constraints, relative direction and egocentric frame of reference. The results showed that (1) simultaneous activation of homologous muscles resulted in more stable performance than simultaneous activation of non-homologous muscles during within-subject coordination, and that (2) isodirectional movements were more stable than non-isodirectional movements during between-persons coordination, confirming the role of the relative direction of the moving limbs in the stability of bimanual coordination. Moreover, the egocentric constraint was to some extent found distinguishable from the effect of the relative direction of the moving limbs in external space, and from the effect of the relative timing of muscle activation. In summary, the present study showed that relative direction of the moving limbs in external space and muscular constraints may interact either to stabilize or destabilize coordination patterns. (C) 2003 Published by Elsevier B.V.

Non-Prismatic Sub-Stiffening for Stiffened Panel Plates — Stability Behaviour and Performance Gains

Previous work has demonstrated the potential to introduce plate element sub-stiffening to increase the local stability and thus static strength performance of integrally machined aluminium alloy stiffened panels. The introduction of plate element prismatic sub-stiffening modifies local plate buckling behaviour and within realistic design constraints, may produce sizable performance gains with equivalent mass designs. This article examines through experimental and computational analysis the potential of non-prismatic sub-stiffening for tailoring local plate stability performance. Using non-prismatic sub-stiffening, the experimental work demonstrates potential initial buckling performance gains with equivalent mass designs (+185%), and computationally, potential mass savings with equivalent static strength performance designs (-9.4%). (C) 2010 Elsevier Ltd. All rights reserved.

Playing with Constraints: Stylistic Variation with a Simple Electronic Instrument

A study was conducted by researchers to address the individuation of performance with electronic instruments. The researchers derived a working concept of style as distinct from structure in an activity, which was proposed as a useful framework for considering virtuosity and individuality in interactions with technology, including musical ones. The researchers proposed an alliance between constraint and the development of style. Another study was described, which explored the emergence of personal performance styles in experienced performers with a novel, constrained electronic musical instrument. The study aimed to represent aspects of a realistic situation within the new interfaces for musical expression (NIME) community where a performer needed to determine how to perform with a new instrument for which there was no established performance practice and instruction manual.

A constraints-based resource discovery model for multi-provider cloud environments

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

Towards Utilizing Model-Driven Engineering of Composite Applications for Business Performance Analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Impact of composite manufacturing constraints on aerospace stiffened panel design

This paper reports on a design study assessing the impact of laminate manufacturing constraints on the structural performance and weight of composite stiffened panels. The study demonstrates that maximizing ply continuity results in weight penalties, while various geometric constraints related to manufacture and repair can be accommodated without significant weight penalties, potentially generating robust flexible designs.

Opportunistic spectrum aggregation for cognitive communications under collision constraints

We consider a collision-sensitive secondary system that intends to opportunistically aggregate and utilize spectrum of a primary system to achieve higher data rates. In such opportunistic spectrum access, secondary transmission can collide with primary transmission. When the secondary system aggregates more channels for data transmission, more frequent collisions may occur, limiting the performance obtained by the opportunistic spectrum aggregation. In this context, dynamic spectrum aggregation problem is formulated to maximize the ergodic channel capacity under the constraint of collision tolerable level. To solve the problem, we develop the optimal spectrum aggregation approach, deriving closed-form expressions for the collision probability in terms of primary user traffic load, secondary user transmission interval, and the random number of sub-channels aggregated. Our results show that aggregating only a subset of sub-channels will be a better choice, depending on the ratio of collision sensitivity requirement to the primary user traffic.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Enabling Complexity-Performance Trade-Offs for Successive Cancellation Decoding of Polar Codes

Polar codes are one of the most recent advancements in coding theory and they have attracted significant interest. While they are provably capacity achieving over various channels, they have seen limited practical applications. Unfortunately, the successive nature of successive cancellation based decoders hinders fine-grained adaptation of the decoding complexity to design constraints and operating conditions. In this paper, we propose a systematic method for enabling complexity-performance trade-offs by constructing polar codes based on an optimization problem which minimizes the complexity under a suitably defined mutual information based performance constraint. Moreover, a low-complexity greedy algorithm is proposed in order to solve the optimization problem efficiently for very large code lengths.

Effect of feed space allowance and period of access to food on dairy cow performance

Two experiments were conducted to examine the ‘long-term’ effect of feed space allowance and period of access to feed on dairy cow performance. In Experiment 1, three horizontal feed space allowances (20, 40 and 60 cm cow−1) were examined over a 127-d period (14 cows per treatment). In Experiment 2, 48 dairy cows were used in a continuous design (10-week duration) 2 × 2 factorial design experiment comprising two horizontal feed space allowances (15 and 40 cm cow−1), and two periods of access to feed (unrestricted and restricted). With the former, uneaten feed was removed at 08·00 h, while feeding took place at 09·00 h. With the latter, uneaten feed was removed at 06·00 h, while feeding was delayed until 12·00 h. Mean total dry-matter (DM) intakes were 19·0, 18·7 and 19·3 kg cow−1 d−1 with the 20, 40 and 60 cm cow−1 treatments in Experiment 1, and 18·1 and 18·2 kg cow−1 d−1 with the ‘restricted feeding time’ treatments, and 17·8 and 18·1 kg d−1 with the ‘unrestricted feeding time’ treatments (15 and 40 cm respectively) in Experiment 2. None of milk yield, milk composition, or end-of-study live weight or condition score were significantly affected by treatment in either experiment (P > 0·05), while fat + protein yield was reduced with the 15-cm treatment in Experiment 2 (P < 0·05). When access to feed was restricted by space or time constraints, cows modified their time budgets and increased their rates of intake.

Executing bag of distributed tasks on the cloud: Investigating the trade-offs between performance and cost

Bag of Distributed Tasks (BoDT) can benefit from decentralised execution on the Cloud. However, there is a trade-off between the performance that can be achieved by employing a large number of Cloud VMs for the tasks and the monetary constraints that are often placed by a user. The research reported in this paper is motivated towards investigating this trade-off so that an optimal plan for deploying BoDT applications on the cloud can be generated. A heuristic algorithm, which considers the user's preference of performance and cost is proposed and implemented. The feasibility of the algorithm is demonstrated by generating execution plans for a sample application. The key result is that the algorithm generates optimal execution plans for the application over 91% of the time.