Efficient read monotonic data aggregation across shards on the cloud

Client-centric consistency models define the view of the data storage expected by a client in relation to the operations done by a client within a session. Monotonic reads is a client-centric consistency model which ensures that if a process has seen a particular value for the object, any subsequent accesses will never return any previous values. Monotonic reads are used in several applications like news feeds and social networks to ensure that the user always has a forward moving view of the data. The idea of Monotonic reads over multiple copies of the data and for lightly loaded systems is intuitive and easy to implement. For example, ensuring that a client session always fetches data from the same server automatically ensures that the user will never view old data. However, such a simplistic setup will not work for large deployments on the cloud, where the data is sharded across multiple high availability setups and there are several million clients accessing data at the same time. In such a setup it becomes necessary to ensure that the data fetched from multiple shards are logically consistent with each other. The use of trivial implementations, like sticky sessions, causes severe performance degradation during peak loads. This paper explores the challenges surrounding consistent monotonic reads over a sharded setup on the cloud and proposes an efficient architecture for the same. Performance of the proposed architecture is measured by implementing it on a cloud setup and measuring the response times for different shard counts. We show that the proposed solution scales with almost no change in performance as the number of shards increases

A Fractional-Order Transitional Butterworth-Butterworth Filter and Its Experimental Validation

This paper introduces the generalization of the classical Transitional Butterworth-Butterworth Filter (TBBF) to the Fractional-Order (FO) domain. Stable rational approximants of the FO-TBBF are optimally realized. Several design examples demonstrate the robustness and modeling efficacy of the proposed method. Practical circuit implementation using the current feedback operational amplifier employed as an active element is presented. Experimental results endorse good agreement (R2= 0.999968) with the theoretical magnitude-frequency characteristic

Optimal Modelling of (1 + α) Order Butterworth Filter under the CFE Framework

This paper presents the optimal rational approximation of (1+α) order Butterworth filter, where α ∊ (0,1) under the continued fraction expansion framework, by employing a new cost function. Two simple techniques based on the constrained optimization and the optimal pole-zero placements are proposed to model the magnitude-frequency response of the fractional-order lowpass Butterworth filter (FOLBF). The third-order FOLBF approximants achieve good agreement to the ideal characteristic for six decades of design bandwidth. Circuit realization using the current feedback operational amplifier is presented, and the modelling efficacy is validated in the OrCAD PSPICE platform

Hornblende-dehydration melting in mafic rocks and the link between massif-type charnockite and associated granulites, Eastern Ghats Granulite Belt, India

A massif-type (intrusive) charnockite body in the Eastern Ghats granulite belt, India, is associated with hornblende-bearing mafic granulite, two-pyroxene granulite and enderbitic granulite. The charnockite is characterised by pervasive gneissic foliation (S1). This is axial planar to the folded layers of hornblende-bearing mafic granulite (F1 folds), indicating that the granulite protoliths were present before the development of S1. Two-pyroxene granulite and enderbitic granulite occur as lenticular patches disposed along the foliation and hence could be syngenetic to S1. The tonalitic to granodioritic, metaluminous to weakly peraluminous compositions and relatively high Sr/Rb of the charnockite are consistent with its derivation by partial melting of a mafic protolith. Strong Y depletion, lack of Sr depletion and strongly fractionated REE patterns with high (La Yb)N ratio, but relatively lower HREE (Gd/Lu) fractionation with marked positive Eu anomalies, suggest major residual hornblende (as well as garnet), but not plagioclase, consistent with the hornblende dehydration melting in the source rocks. Such a residual mineralogy is broadly similar to those of some of the hornblende-bearing matic granulite inclusions, which have compositional features indicative of a restitic nature. Quantitative modelling supports an origin for the charnockite melts by partial melting of a hornblende-rich mafic granulite source, although source heterogeneity is very likely given the rather variable trace element contents of the charnockite. The wholerock and mineral compositions of the two-pyroxene granulites and enderbitic granulites are consistent with them representing peritectic phase segregations of hornblende-dehydration melting. A clockwise P-T path implies that melting could have occurred in thickened continental crust undergoing decompression

First International Conference on Intelligent Computing and Applications

The idea of the 1st International Conference on Intelligent Computing and Applications (ICICA 2014) is to bring the Research Engineers, Scientists, Industrialists, Scholars and Students together from in and around the globe to present the on-going research activities and hence to encourage research interactions between universities and industries. The conference provides opportunities for the delegates to exchange new ideas, applications and experiences, to establish research relations and to find global partners for future collaboration. The proceedings covers latest progresses in the cutting-edge research on various research areas of Image, Language Processing, Computer Vision and Pattern Recognition, Machine Learning, Data Mining and Computational Life Sciences, Management of Data including Big Data and Analytics, Distributed and Mobile Systems including Grid and Cloud infrastructure, Information Security and Privacy, VLSI, Electronic Circuits, Power Systems, Antenna, Computational fluid dynamics & Heat transfer, Intelligent Manufacturing, Signal Processing, Intelligent Computing, Soft Computing, Bio-informatics, Bio Computing, Web Security, Privacy and E-Commerce, E-governance, Service Orient Architecture, Data Engineering, Open Systems, Optimization, Communications, Smart wireless and sensor Networks, Smart Antennae, Networking and Information security, Machine Learning, Mobile Computing and Applications, Industrial Automation and MES, Cloud Computing, Green IT, IT for Rural Engineering, Business Computing, Business Intelligence, ICT for Education for solving hard problems, and finally to create awareness about these domains to a wider audience of practitioners

Infinite Impulse Response Approximations to the Non-integer Order Integrator Using Cuckoo Search Algorithm

Part 6: Modelling and OptimizationInternational audienceA popular metaheuristic global optimization technique called Cuckoo Search Algorithm (CSA) is employed to design non-integer order integrators (NOIs) in terms of the Infinite Impulse Response (IIR) templates in this paper. Extensive comparisons on the basis of design quality robustness, error convergence, and optimization time of the CSA-based NOIs are carried out with the Particle Swarm Optimization (PSO) based designs. Results demonstrate the efficient performance of CSA in exploring the multimodal, non-linear, and non-uniform error surface for this optimization problem. The CSA-based designs also outperform the recent literature by 9.67 decibel (dB) and 19.26 dB in terms of mean absolute relative magnitude error (MARME) and maximum absolute magnitude error (MAME) metrics, respectively

Gravitation search algorithm: Application to the optimal IIR filter design

This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA) and standard Particle Swarm Optimization (PSO). Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability