During the last century, population growth, together with economic development, has considerably increased the energy demand and, although renewable energies are becoming an alternative, still total energy supply is mainly non-renewable, causing well-known negative effects such as pollution and global warming. On the other hand, technological advances have allowed the development of increasingly efficient distributed generation systems and the emergence of microgrids, whose studies have been focused on architecture, elements, and objectives of the associated energy management strategies. In this regard, energy management strategies based on a Fuzzy Logic controller have been developed for electro-thermal microgrids where parameter optimization has been carried out through heuristic procedures of trial and error with acceptable results but involving a high computational cost. To solve the aforementioned drawbacks, in the present work the use of Cuckoo Search optimization nature-inspired algorithm that allows the adjustment of Fuzzy Logic controller parameters and ensures a higher quality of energy management is proposed. Obtained results show encouraging outcomes for the use of these meta-heuristic optimization algorithms.

Geophysics experts are interested in understanding the behavior of volcanoes and forecasting possible eruptions by monitoring and detecting the increment on volcano-seismic activity, with the aim of safeguarding human lives and material losses. This paper presents an automatic volcanic event detection and classification system, which considers feature extraction and feature selection stages, to reduce the processing time toward a reliable real-time volcano early warning system (RT-VEWS). We built the proposed approach in terms of the seismicity presented in 2009 and 2010 at the Cotopaxi Volcano located in Ecuador. In the detection stage, the recordings were time segmented by using a nonoverlapping 15-s window, and in the classification stage, the detected seismic signals were 1-min long. For each detected signal conveying seismic events, a comprehensive set of statistical, temporal, spectral, and scale-domain features were compiled and extracted, aiming to separate long-period (LP) events from volcano-tectonic (VT) earthquakes. We benchmarked two commonly used types of feature selection techniques, namely, wrapper (recursive feature extraction) and embedded (cross-validation and pruning). Each technique was used within a suitable and appropriate classification algorithm, either the support vector machine (SVM) or the decision trees. The best result was obtained by using the SVM classifier, yielding up to 99% accuracy in the detection stage and 97% accuracy and sensitivity in the event classification stage. Selected features and their interpretation were consistent among different input spaces in simple terms of the spectral content of the frequency bands at 3.1 and 6.8 Hz. A comparative analysis showed that the most relevant features for automatic discrimination between LP and VT events were one in the time domain, five in the frequency domain, and nine in the scale domain. Our study provides the framework for an event classification system with high accuracy and reduced computational requirements, according to the orientation toward a future RT-VEWS.

This paper proposes and evaluates an approach for power and performance management in virtualized server clusters. The major goal of our approach is to reduce power consumption in the cluster while meeting performance requirements. The contributions of this paper are: (1) a simple but effective way of modeling power consumption and capacity of servers even under heterogeneous and changing workloads, and (2) an optimization strategy based on a mixed integer programming model for achieving improvements on power-efficiency while providing performance guarantees in the virtualized cluster. In the optimization model, we address application workload balancing and the often ignored switching costs due to frequent and undesirable turning servers on/off and VM relocations. We show the effectiveness of the approach applied to a server cluster test bed. Our experiments show that our approach conserves about 50% of the energy required by a system designed for peak workload scenario, with little impact on the applications' performance goals. Also, by using prediction in our optimization strategy, further QoS improvement was achieved.

The previous research on cluster-based servers has focused on homogeneous systems. However, real-life clusters are almost invariably heterogeneous in terms of the performance, capacity, and power consumption of their hardware components. In this paper, we argue that designing efficient servers for heterogeneous clusters requires defining an efficiency metric, modeling the different types of nodes with respect to the metric, and searching for request distributions that optimize the metric. To concretely illustrate this process, we design a cooperative Web server for a heterogeneous cluster that uses modeling and optimization to minimize the energy consumed per request. Our experimental results for a cluster comprised of traditional and blade nodes show that our server can consume 42 % less energy than an energy-oblivious server, with only a negligible loss in throughput. The results also show that our server conserves 45 % more energy than an energy-conscious server that was previously proposed for homogeneous clusters. 1

In this paper, we propose and evaluate a cluster-based network server called PRESS. The server relies on locality-conscious request distribution and a standard for user-level communication to achieve high performance and portability. We evaluate PRESS by first isolating the performance benefits of three key features of user-level communication: low processor overhead, remote memory accesses, and zero-copy transfers. Next, we compare PRESS to servers that involve less intercluster communication, but are not as easily portable. Our results for an 8-node server cluster and five WWW traces demonstrate that user-level communication can improve performance by as much as 52 percent compared to a kernel-level protocol. Low processor overhead, remote memory writes, and zero-copy all make nontrivial contributions toward this overall gain. Our results also show that portability in PRESS causes no throughput degradation when we exploit user-level communication extensively.

Low disk throughput is one of the main impediments to improving the performance of data-intensive servers. In this paper, we propose two management techniques for the disk controller cache that can significantly increase disk throughput. The first technique, called File-Oriented Read-ahead (FOR), adjusts the number of read-ahead blocks brought into the disk controller cache according to file system information. The second technique, called Host-guided Device Caching (HDC), gives the host control over part of the disk controller cache. As an example use of this mechanism, we keep the blocks that cause the most misses in the host buffer cache permanently cached in the disk controller. Our detailed simulations of real server workloads show that FOR and HDC can increase disk throughput by up to 34% and 24%, respectively, in comparison to conventional disk controller cache management techniques. When combined, the techniques can increase throughput by up to 47%.

In this paper we study four approaches to conserving disk energy in high-performance network servers. The first approach is to leverage the extensive work on laptop disks and power disks down during periods of idleness. The second approach is to replace high-performance disks with a set of lower power disks that can achieve the same performance and reliability. The third approach is to combine high-performance and laptop disks, such that only one of these two sets of disks is powered on at a time. This approach requires the mirroring (and coherence) of all disk data on the two sets of disks. Finally, the fourth approach is to use multi-speed disks, such that each disk is slowed down for lower energy consumption during periods of light load. We demonstrate that the fourth approach is the only one that can actually provide energy savings for network servers. In fact, our results for Web and proxy servers show that the fourth approach can provide energy savings of up to 23%, in comparison to conventional servers, without any degradation in server performance.

Clusters of commodity computers are currently being used to provide the scalability required by several popular Internet services. In this paper we evaluate an efficient cluster-based WWW server, as a function of the characteristics of the intra-cluster communication architecture. More specifically, we evaluate the impact of processor overhead, network bandwidth, remote memory writes, and zero-copy data transfers on the performance of our server. Our experimental results with an 8-node cluster and four real WWW traces show that network bandwidth affects the performance of our server by only 6%. In contrast, user-level communication can improve performance by as much as 29%. Low processor overhead, remote memory writes, and zero-copy all make small contributions towards this overall gain. To be able to extrapolate from our experimental results, we use an analytical model to assess the performance of our server under different workload characteristics, different numbers of cluster nodes, and higher performance systems. Our modeling results show that higher gains (of up to 55%) can be accrued for workloads with large working sets and next-generation servers running on large clusters.

Efficiency and portability are conflicting objectives for cluster-based network servers that distribute the clients' requests across the cluster based on the actual content requested. Our work is based on the observation that this efficiency vs. portability tradeoff has not been fully evaluated in the literature. To fill this gap, in this paper we use modeling and experimentation to study this tradeoff in the context of an interesting class of content-based network servers, the locality-conscious servers, under different inter-node communication subsystems. Based on our results, our main conclusion is that portability should be promoted in cluster-based network servers with low processor overhead, given its relatively low cost ($\leq$ 16%) in terms of throughput performance. For clusters with high processor overhead communication, efficiency should be the overriding concern, as the cost of portability can be very high (as high as 107% on 96 nodes). We also conclude that user-level communication can be useful even for non-scientific applications such as network servers.

Uses analytic modeling and simulation to evaluate network servers implemented on clusters of workstations. More specifically, we model the potential benefits of locality-conscious request distribution within the cluster and evaluate the performance of a cluster-based server called L2S (Locality and Load-balancing Server) which we designed in light of our experience with the model. Our most important modeling results show that locality-conscious distribution on a 16-node cluster can increase server throughput with respect to a locality-oblivious server by up to seven-fold, depending on the average size of the files requested and on the size of the server's working set. Our simulation results demonstrate that L2S achieves throughput that is within 22% of the full potential of locality-conscious distribution on 16 nodes, outperforming and significantly outscaling the best-known locality-conscious server. Based on our results and on the fact that the files serviced by network servers are becoming larger and more numerous, we conclude that our locality-conscious network server should prove very useful for its performance, scalability and availability.

Article Free Access Share on OPTNET: a cost-effective optical network for multiprocessors Authors: Enrique V. Carrera COPPE Systems Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil COPPE Systems Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, BrazilView Profile , Ricardo Bianchini COPPE Systems Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil COPPE Systems Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, BrazilView Profile Authors Info & Claims ICS '98: Proceedings of the 12th international conference on SupercomputingJuly 1998 Pages 401–408https://doi.org/10.1145/277830.277929Published:13 July 1998Publication History 5citation362DownloadsMetricsTotal Citations5Total Downloads362Last 12 Months25Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

This paper presents P-RIO, a parallel programming environment that supports an object based software configuration methodology. It promotes a clear separation of the individual sequential computation components from the interconnection structure used for the interaction between these components. This makes the data and control interactions explicit, simplifying program visualization and understanding. P-RIO includes a graphical tool that helps to configure, monitor and debug parallel programs.

Some of the most common parallel programming idioms include locks, barriers, and reduction operations. The interaction of these programming idioms with the multiprocessor's coherence protocol has a significant impact on performance. In addition, the advent of machines that support multiple coherence protocols prompts the question of how to best implement such parallel constructs, i.e. what combination of implementation and coherence protocol yields the best performance. In this paper we study the running time and communication behavior of (1) centralized (ticket) and MCS spin locks, (2) centralized, dissemination, and tree-based barriers, and (3) parallel and sequential reductions, under pure and competitive update coherence protocols; results for write-invalidate protocol are presented mostly for comparison purposes. Our experiments indicate that parallel programming techniques that are well-established for write invalidate protocols, such as MCS locks and parallel reductions, are often inappropriate for update-based protocols. In contrast, techniques such as dissemination and tree barriers achieve superior performance under update-based protocols. Our results also show that the implementation of parallel programming idioms must take the coherence protocol into account, since update-based protocols often lead to different design decisions than write invalidate protocols. Our main conclusion is that protocol-conscious implementation of parallel programming structures can significantly improve application performance; for multiprocessors that can support more than one coherence protocol both the protocol and implementation should betaken into account when exploiting parallel constructs.