http://emamispnu.persiangig.com/Projects/Cloud%20Computing/science_2.pdf

Review: A survey on security issues in service delivery models of cloud computing

Matrix Factorization Techniques for Recommender Systems

An exact characterization of the ability of the rate monotonic scheduling algorithm to meet the deadlines of a periodic task set is represented. In addition, a stochastic analysis which gives the probability distribution of the breakdown utilization of randomly generated task sets is presented. It is shown that as the task set size increases, the task computation times become of little importance, and the breakdown utilization converges to a constant determined by the task periods. For uniformly distributed tasks, a breakdown utilization of 88% is a reasonable characterization. A case is shown in which the average-case breakdown utilization reaches the worst-case lower bound of C.L. Liu and J.W. Layland (1973). >

The rate monotonic scheduling algorithm: exact characterization and average case behavior

Service-Oriented Architecture (SOA) provides a flexible framework for service composition Using standard-based protocols (such as SOAP and WSDL), composite services can be constructed by integrating atomic services developed independently Algorithms are needed to select service components with various QoS levels according to some application-dependent performance requirements We design a broker-based architecture to facilitate the selection of QoS-based services The objective of service selection is to maximize an application-specific utility function under the end-to-end QoS constraints The problem is modeled in two ways: the combinatorial model and the graph model The combinatorial model defines the problem as a multidimension multichoice 0-1 knapsack problem (MMKP) The graph model defines the problem as a multiconstraint optimal path (MCOP) problem Efficient heuristic algorithms for service processes of different composition structures are presented in this article and their performances are studied by simulations We also compare the pros and cons between the two models

Efficient algorithms for Web services selection with end-to-end QoS constraints

New languages, programming disciplines, operating systems, and software engineering techniques sometimes hold considerable potential for real-time software developers. A promising area of interest-but one fairly new to the real-time community-is object-oriented programming. Java, for example, draws heavily from object orientation and is highly suitable for extension to real-time and embedded systems. Recognizing this fit between Java and real-time software development, the Real-Time for Java Experts Group (RTJEG) began developing the real-time specification for Java (RTSJ) in March 1999 under the Java Community Process. This article explains RTSJ's features and the thinking behind the specification's design. The goal of the RTJEG, of which the authors are both members, was to provide a platform-a Java execution environment and application program interface (API)-that lets programmers correctly reason about the temporal behavior of executing software.

https://database.sarang.net/study/java/rtj/rtj.pdf

The Real-Time Specification for Java

The imprecise computation technique, which prevents timing faults and achieves graceful degradation by giving the user an approximate result of acceptable quality whenever the system cannot produce the exact result in time, is considered. Different approaches for scheduling imprecise computations in hard real-time environments are discussed. Workload models that quantify the tradeoff between result quality and computation time are reviewed. Scheduling algorithms that exploit this tradeoff are described. These include algorithms for scheduling to minimize total error, scheduling periodic jobs, and scheduling parallelizable tasks. A queuing-theoretical formulation of the imprecise scheduling problem is presented. >

Algorithms for scheduling imprecise computations

The problem of scheduling periodic jobs in hard real-time systems that support imprecise computations is discussed. Timing faults are avoided in such systems by making available intermediate, imprecise results of acceptable quality when results of the desired quality cannot be produced on time. Two workload models of imprecise computations are presented. These models differ from traditional models in that a task may be terminated any time after it has produced an acceptable result. Each task is logically decomposed into a mandatory part followed by an optional part. In a feasible schedule, the mandatory part of every task is completed before the deadline of the task. The optional part refines the result produced by the mandatory part to reduce the error in the result. >

Scheduling periodic jobs that allow imprecise results

Web services are new forms of Internet software that can be universally deployed and invoked using standard protocols. Services from different providers can be integrated into a composite service regardless of their locations, platforms, and/or execution speeds to implement complex business processes and transactions. In this paper, we study the end-to-end QoS issues of composite services by utilizing a QoS broker that is responsible for selecting and coordinating the individual service component. We design the service selection algorithms used by QoS brokers to construct the optimal composite service. The objective of the algorithms is to maximize the user-defined utility function value while meeting the end-to-end delay constraint. We propose two solution approaches to the service selection problem: the combinatorial approach, by modeling the problem as the Multiple Choice Knapsack Problem (MCKP), and the graph approach, by modeling the problem as the constrained shortest path problem in the graph theory. We study efficient solutions for each approach.

Service selection algorithms for Web services with end-to-end QoS constraints

The imprecise computation technique has been proposed as a way to handle transient overload and to enhance fault tolerance of real-time systems. In a system based on this technique, each time-critical task is designed in such a way that it can produce a usable, approximate result in time whenever a failure or overload prevents it from producing the desired, precise result. This paper describes ways to implement imprecise computations, models to characterize them and algorithms for scheduling them. An imprecise mechanism for the generation and use of approximate results can be integrated in a natural way with a traditional fault-tolerance mechanism. An architectural framework for this integration is described. >

Kwei-Jay Lin

Papers

Efficient algorithms for Web services selection with end-to-end QoS constraints

Algorithms for scheduling imprecise computations

Scheduling periodic jobs that allow imprecise results

Service selection algorithms for Web services with end-to-end QoS constraints

Imprecise computations