20 resultados para service-oriented computing (SOC)

em Indian Institute of Science - Bangalore - Índia


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Service systems are labor intensive. Further, the workload tends to vary greatly with time. Adapting the staffing levels to the workloads in such systems is nontrivial due to a large number of parameters and operational variations, but crucial for business objectives such as minimal labor inventory. One of the central challenges is to optimize the staffing while maintaining system steady-state and compliance to aggregate SLA constraints. We formulate this problem as a parametrized constrained Markov process and propose a novel stochastic optimization algorithm for solving it. Our algorithm is a multi-timescale stochastic approximation scheme that incorporates a SPSA based algorithm for ‘primal descent' and couples it with a ‘dual ascent' scheme for the Lagrange multipliers. We validate this optimization scheme on five real-life service systems and compare it with a state-of-the-art optimization tool-kit OptQuest. Being two orders of magnitude faster than OptQuest, our scheme is particularly suitable for adaptive labor staffing. Also, we observe that it guarantees convergence and finds better solutions than OptQuest in many cases.

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In this paper we present the design of ``e-SURAKSHAK,'' a novel cyber-physical health care management system of Wireless Embedded Internet Devices (WEIDs) that sense vital health parameters. The system is capable of sensing body temperature, heart rate, oxygen saturation level and also allows noninvasive blood pressure (NIBP) measurement. End to end internet connectivity is provided by using 6LoWPAN based wireless network that uses the 802.15.4 radio. A service oriented architecture (SOA) 1] is implemented to extract meaningful information and present it in an easy-to-understand form to the end-user instead of raw data made available by sensors. A central electronic database and health care management software are developed. Vital health parameters are measured and stored periodically in the database. Further, support for real-time measurement of health parameters is provided through a web based GUI. The system has been implemented completely and demonstrated with multiple users and multiple WEIDs.

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A number of companies are trying to migrate large monolithic software systems to Service Oriented Architectures. A common approach to do this is to first identify and describe desired services (i.e., create a model), and then to locate portions of code within the existing system that implement the described services. In this paper we describe a detailed case study we undertook to match a model to an open-source business application. We describe the systematic methodology we used, the results of the exercise, as well as several observations that throw light on the nature of this problem. We also suggest and validate heuristics that are likely to be useful in partially automating the process of matching service descriptions to implementations.

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In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.

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Loads that miss in L1 or L2 caches and waiting for their data at the head of the ROB cause significant slow down in the form of commit stalls. We identify that most of these commit stalls are caused by a small set of loads, referred to as LIMCOS (Loads Incurring Majority of COmmit Stalls). We propose simple history-based classifiers that track commit stalls suffered by loads to help us identify this small set of loads. We study an application of these classifiers to prefetching. The classifiers are used to train the prefetcher to focus on the misses suffered by LIMCOS. This, referred to as focused prefetching, results in a 9.8% gain in IPC over naive GHB based delta correlation prefetcher along with a 20.3% reduction in memory traffic for a set of 17 memory-intensive SPEC2000 benchmarks. Another important impact of focused prefetching is a 61% improvement in the accuracy of prefetches. We demonstrate that the proposed classification criterion performs better than other existing criteria like criticality and delinquent loads. Also we show that the criterion of focusing on commit stalls is robust enough across cache levels and can be applied to any prefetcher without any modifications to the prefetcher.

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REDEFINE is a reconfigurable SoC architecture that provides a unique platform for high performance and low power computing by exploiting the synergistic interaction between coarse grain dynamic dataflow model of computation (to expose abundant parallelism in applications) and runtime composition of efficient compute structures (on the reconfigurable computation resources). We propose and study the throttling of execution in REDEFINE to maximize the architecture efficiency. A feature specific fast hybrid (mixed level) simulation framework for early in design phase study is developed and implemented to make the huge design space exploration practical. We do performance modeling in terms of selection of important performance criteria, ranking of the explored throttling schemes and investigate effectiveness of the design space exploration using statistical hypothesis testing. We find throttling schemes which give appreciable (24.8%) overall performance gain in the architecture and 37% resource usage gain in the throttling unit simultaneously.

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An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.

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An efficient location service is a prerequisite to any robust, effective and precise location information aided Mobile Ad Hoc Network (MANET) routing protocol. Locant, presented in this paper is a nature inspired location service which derives inspiration from the insect colony framework, and it is designed to work with a host of location information aided MANET routing protocols. Using an extensive set of simulation experiments, we have compared the performance of Locant with RLS, SLS and DLS, and found that it has comparable or better performance compared to the above three location services on most metrics and has the least overhead in terms of number of bytes transmitted per location query answered.

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The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.

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Floquet analysis is widely used for small-order systems (say, order M < 100) to find trim results of control inputs and periodic responses, and stability results of damping levels and frequencies, Presently, however, it is practical neither for design applications nor for comprehensive analysis models that lead to large systems (M > 100); the run time on a sequential computer is simply prohibitive, Accordingly, a massively parallel Floquet analysis is developed with emphasis on large systems, and it is implemented on two SIMD or single-instruction, multiple-data computers with 4096 and 8192 processors, The focus of this development is a parallel shooting method with damped Newton iteration to generate trim results; the Floquet transition matrix (FTM) comes out as a byproduct, The eigenvalues and eigenvectors of the FTM are computed by a parallel QR method, and thereby stability results are generated, For illustration, flap and flap-lag stability of isolated rotors are treated by the parallel analysis and by a corresponding sequential analysis with the conventional shooting and QR methods; linear quasisteady airfoil aerodynamics and a finite-state three-dimensional wake model are used, Computational reliability is quantified by the condition numbers of the Jacobian matrices in Newton iteration, the condition numbers of the eigenvalues and the residual errors of the eigenpairs, and reliability figures are comparable in both the parallel and sequential analyses, Compared to the sequential analysis, the parallel analysis reduces the run time of large systems dramatically, and the reduction increases with increasing system order; this finding offers considerable promise for design and comprehensive-analysis applications.

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We consider the problem of wireless channel allocation to multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. Each metric sequence can be Markov. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

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Precision, sophistication and economic factors in many areas of scientific research that demand very high magnitude of compute power is the order of the day. Thus advance research in the area of high performance computing is getting inevitable. The basic principle of sharing and collaborative work by geographically separated computers is known by several names such as metacomputing, scalable computing, cluster computing, internet computing and this has today metamorphosed into a new term known as grid computing. This paper gives an overview of grid computing and compares various grid architectures. We show the role that patterns can play in architecting complex systems, and provide a very pragmatic reference to a set of well-engineered patterns that the practicing developer can apply to crafting his or her own specific applications. We are not aware of pattern-oriented approach being applied to develop and deploy a grid. There are many grid frameworks that are built or are in the process of being functional. All these grids differ in some functionality or the other, though the basic principle over which the grids are built is the same. Despite this there are no standard requirements listed for building a grid. The grid being a very complex system, it is mandatory to have a standard Software Architecture Specification (SAS). We attempt to develop the same for use by any grid user or developer. Specifically, we analyze the grid using an object oriented approach and presenting the architecture using UML. This paper will propose the usage of patterns at all levels (analysis. design and architectural) of the grid development.

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Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

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The Reeb graph of a scalar function tracks the evolution of the topology of its level sets. This paper describes a fast algorithm to compute the Reeb graph of a piecewise-linear (PL) function defined over manifolds and non-manifolds. The key idea in the proposed approach is to maximally leverage the efficient contour tree algorithm to compute the Reeb graph. The algorithm proceeds by dividing the input into a set of subvolumes that have loop-free Reeb graphs using the join tree of the scalar function and computes the Reeb graph by combining the contour trees of all the subvolumes. Since the key ingredient of this method is a series of union-find operations, the algorithm is fast in practice. Experimental results demonstrate that it outperforms current generic algorithms by a factor of up to two orders of magnitude, and has a performance on par with algorithms that are catered to restricted classes of input. The algorithm also extends to handle large data that do not fit in memory.

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Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.