One-dimensional partitioning for heterogeneous systems: Theory and practice

We study the problem of one-dimensional partitioning of nonuniform workload arrays, with optimal load balancing for heterogeneous systems. We look at two cases: chain-on-chain partitioning, where the order of the processors is specified, and chain partitioning, where processor permutation is allowed. We present polynomial time algorithms to solve the chain-on-chain partitioning problem optimally, while we prove that the chain partitioning problem is NP-complete. Our empirical studies show that our proposed exact algorithms produce substantially better results than heuristics, while solution times remain comparable.     

Earthquake onset detection using spectro-ratio on multi-threshold time–frequency sub-band

Automatic onset detection and picking algorithm has been proposed by applying the spectro-ratio on time–frequency sub-band. The proposed algorithm does not need any parameter settings as it will work on data generated by either short or very broad band seismometers. Our algorithm is applied on local events from Cairo region recorded by three stations of the Egyptian National Seismic Network (ENSN). Maximum standard deviation is observed to be 0.113 s of the corresponding manual picks made by analysts.     

Principles and performance analysis of SeCond: A system for epidemic peer-to-peer content distribution

We propose and design a peer-to-peer system, SeCond, addressing the distribution of large sized content to a large number of end systems in an efficient manner. In contrast to prior work, it employs a self-organizing epidemic dissemination scheme for state propagation of available blocks and initiation of block transmissions. In order to exploit heterogeneity of peers, enhance the utilization of system resources and for the ease of deployment, scalability, and adaptivity to dynamic peer arrivals/departures, we propose mechanisms for adjusting protocol parameters dynamically according to the bandwidth usages. We describe design and analysis details of our protocol SeCond. Comprehensive performance evaluations and comparison with the BitTorrent system model have been accomplished for a wide range of scenarios. Performance results include scalability analysis for different arrival/departure patterns, flash-crowd scenario, overhead analysis, and fairness ratio. The major metrics we study include the average file download time, load on the primary seed, uplink/downlink utilization, and communication overhead. We show that SeCond is a scalable and adaptive protocol which takes the heterogeneity of the peers into account. The protocol is as fair as BitTorrent although it has no explicit strategy addressing free-riding. We also illustrate the applicability of an analytical fluid model to the behavior of SeCond.     

Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks

In wireless multimedia sensor networks (WMSNs) a sensor node may have different types of sensor which gather different kinds of data. To support quality of service (QoS) requirements for multimedia applications having a reliable and fair transport protocol is necessary. One of the main objectives of the transport layer in WMSNs is congestion control. We observe that the information provided may have different levels of importance and argue that sensor networks should be willing to spend more resources in disseminating packets carrying more important information. Some applications of WMSNs may need to send real time traffic toward the sink node. This real time traffic requires low latency and high reliability so that immediate remedial and defensive actions can be taken when needed. Therefore, similar to wired networks, service differentiation in wireless sensor networks is also an important issue. We present a priority-based rate control mechanism for congestion control and service differentiation in WMSNs. We distinguish high priority real time traffic from low priority non-real time traffic, and service the input traffic based on its priority. Simulation results confirm the superior performance of the proposed model with respect to delays, delay variation and loss probability.     

Measuring robustness of computing systems

System builders are becoming increasingly interested in robust design. We believe that a methodology for generating robustness metrics will help the robust design research efforts and, in general, is an important step in the efforts to create robust computing systems. The purpose of the research in this paper is to quantify the robustness of a resource allocation, with the eventual objective of setting a standard that could easily be instantiated for a particular computing system to generate a robustness metric. The paper exposes how not considering the uncertainties can result in gross overestimation of the system capacity, and shows a method for reducing the impact of uncertainty, and even use it to our advantage if the uncertainties are correlated. We present our theoretical foundation for a robustness metric and give its instantiation for a particular system.     

A cost-effective lexical acquisition process for large-scale thesaurus translation

Thesauri and controlled vocabularies facilitate access to digital collections by explicitly representing the underlying principles of organization. Translation of such resources into multiple languages is an important component for providing multilingual access. However, the specificity of vocabulary terms in most thesauri precludes fully-automatic translation using general-domain lexical resources. In this paper, we present an efficient process for leveraging human translations to construct domain-specific lexical resources. This process is illustrated on a thesaurus of 56,000 concepts used to catalog a large archive of oral histories. We elicited human translations on a small subset of concepts, induced a probabilistic phrase dictionary from these translations, and used the resulting resource to automatically translate the rest of the thesaurus. Two separate evaluations demonstrate the acceptability of the automatic translations and the cost-effectiveness of our approach.

Optimization of dynamic response using a monolithic-time formulation

The design of systems for dynamic response may involve constraints that need to be satisfied over an entire time interval or objective functions evaluated over the interval. Efficiently performing the constrained optimization is challenging, since the typical response is implicitly linked to the design variables through a numerical integration of the governing differential equations. Evaluating constraints is costly, as is the determination of sensitivities to variations in the design variables. In this paper, we investigate the application of a temporal spectral element method to the optimization of transient and time-periodic responses of fundamental engineering systems. Through the spectral discretization, the response is computed globally, thereby enabling a more explicit connection between the response and design variables and facilitating the efficient computation of response sensitivities. Furthermore, the response is captured in a higher order manner to increase analysis accuracy. Two applications of the coupling of dynamic response optimization with the temporal spectral element method are demonstrated. The first application, a one-degree-of-freedom, linear, impact absorber, is selected from the auto industry, and tests the ability of the method to treat transient constraints over a large-time interval. The second application, a related mass-spring-damper system, shows how the method can be used to obtain work and amplitude optimal time-periodic control force subject to constraints over a periodic time interval. This research was performed while the first author held a National Research Council Research Associateship Award at the Air Force Research Laboratory. An early version of this paper was presented at the 46th AIAA Aerospace Sciences Meeting and Exhibit, Jan 7–10, 2008, Reno, Nevada.     

Predictive model for shear strength estimation in reinforced concrete beams with recycled aggregates using Gaussian process regression

Neural Computing and Applications - In order to attain sustainable development, recycled concrete aggregates (RCAs) are increasingly utilized in civil engineering projects. Therefore, it is vital...     

Human-centered design of a wearable kinesthetic haptic device for surgical teleoperation

Artificial Life and Robotics - This paper describes the design and performance evaluation of a flexible wearable haptic device that aims to realize full kinesthetic haptic feedback for application...