Distributed data mining in grid computing environments

The official published version of this article can be found at the link below.The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an effective scheduling framework. DDM often shares the computing paradigm of local processing and global synthesizing. It involves every phase of Data Mining (DM) processes, which makes the workflow of DDM very complex and can be modelled only by a Directed Acyclic Graph (DAG) with multiple data entries. Motivated by the need for a practical solution of the Grid scheduling problem for the DDM workflow, this paper proposes a novel two-phase scheduling framework, including External Scheduling and Internal Scheduling, on a two-level Grid architecture (InterGrid, IntraGrid). Currently a DM IntraGrid, named DMGCE (Data Mining Grid Computing Environment), has been developed with a dynamic scheduling framework for competitive DAGs in a heterogeneous computing environment. This system is implemented in an established Multi-Agent System (MAS) environment, in which the reuse of existing DM algorithms is achieved by encapsulating them into agents. Practical classification problems from oil well logging analysis are used to measure the system performance. The detailed experiment procedure and result analysis are also discussed in this paper

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

The Runtime Behavior of Composite SOAP Web Services under Transient Loads

Services are computational elements that expose functionality in a platform independent manner. They are the basic building blocks of the service-oriented (SO) design/integration paradigm. Composite Web Services (CWS) aggregate multiple Web Services (WSs), which is typically achieved by use of a workflow language. A workflow coordinates services in a manner that is consistent with the desired overall functionality (e.g. business process). When the atomic and composite services are exposed to various users, the performance and runtime behavior of WSs becomes important. To ensure wide deployment of CWS, the performance issues must be studied. This research focuses on the performance of atomic and composite SOAP (Simple Object Access Protocol) WSs under transient overloads. This research includes conducting experiments with WSs, studying the runtime behavior, and building simulation models of WSs workflow patterns. Simulation models of different WSs workflow patterns are built to study different situations. Timeout and network latency are added to the model to better simulate real systems. The simulation models are used to predict the runtime behavior of WSs and CWS, as well as to improve the performance with existing, limited resources

Dual-phase just-in-time workflow scheduling in P2P grid systems

This paper presents a fully decentralized justin-time workflow scheduling method in a P2P Grid system. The proposed solution allows each peer node to autonomously dispatch inter-dependent tasks of workflows to run on geographically distributed computers. To reduce the workflow completion time and enhance the overall execution efficiency, not only does each node perform as a scheduler to distribute its tasks to execution nodes (or resource nodes), but the resource nodes will also set the execution priorities for the received tasks. By taking into account the unpredictability of tasks' finish time, we devise an efficient task scheduling heuristic, namely dynamic shortest makespan first (DSMF), which could be applied at both scheduling phases for determining the priority of the workflow tasks. We compare the performance of the proposed algorithm against seven other heuristics by simulation. Our algorithm achieves 20%~60% reduction on the average completion time and 37.5%~90% improvement on the average workflow execution efficiency over other decentralized algorithms. © 2010 IEEE.published_or_final_versionProcessing (ICPP 2010), San Diego, CA., 13-16 September 2010. In Proceedings of the 39th ICCP, 2010, p. 238-24

Workflow scheduling for service oriented cloud computing

Service Orientation (SO) and grid computing are two computing paradigms that when put together using Internet technologies promise to provide a scalable yet flexible computing platform for a diverse set of distributed computing applications. This practice gives rise to the notion of a computing cloud that addresses some previous limitations of interoperability, resource sharing and utilization within distributed computing. In such a Service Oriented Computing Cloud (SOCC), applications are formed by composing a set of services together. In addition, hierarchical service layers are also possible where general purpose services at lower layers are composed to deliver more domain specific services at the higher layer. In general an SOCC is a horizontally scalable computing platform that offers its resources as services in a standardized fashion. Workflow based applications are a suitable target for SOCC where workflow tasks are executed via service calls within the cloud. One or more workflows can be deployed over an SOCC and their execution requires scheduling of services to workflow tasks as the task become ready following their interdependencies. In this thesis heuristics based scheduling policies are evaluated for scheduling workflows over a collection of services offered by the SOCC. Various execution scenarios and workflow characteristics are considered to understand the implication of the heuristic based workflow scheduling

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels. Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load. To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions. The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments. The proposed InterCloud environment supports scaling of applications across multiple vendor clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape

Decentralized Resource Scheduling in Grid/Cloud Computing

In the Grid/Cloud environment, applications or services and resources belong to different organizations with different objectives. Entities in the Grid/Cloud are autonomous and self-interested; however, they are willing to share their resources and services to achieve their individual and collective goals. In such open environment, the scheduling decision is a challenge given the decentralized nature of the environment. Each entity has specific requirements and objectives that need to achieve. In this thesis, we review the Grid/Cloud computing technologies, environment characteristics and structure and indicate the challenges within the resource scheduling. We capture the Grid/Cloud scheduling model based on the complete requirement of the environment. We further create a mapping between the Grid/Cloud scheduling problem and the combinatorial allocation problem and propose an adequate economic-based optimization model based on the characteristic and the structure nature of the Grid/Cloud. By adequacy, we mean that a comprehensive view of required properties of the Grid/Cloud is captured. We utilize the captured properties and propose a bidding language that is expressive where entities have the ability to specify any set of preferences in the Grid/Cloud and simple as entities have the ability to express structured preferences directly. We propose a winner determination model and mechanism that utilizes the proposed bidding language and finds a scheduling solution. Our proposed approach integrates concepts and principles of mechanism design and classical scheduling theory. Furthermore, we argue that in such open environment privacy concerns by nature is part of the requirement in the Grid/Cloud. Hence, any scheduling decision within the Grid/Cloud computing environment is to incorporate the feasibility of privacy protection of an entity. Each entity has specific requirements in terms of scheduling and privacy preferences. We analyze the privacy problem in the Grid/Cloud computing environment and propose an economic based model and solution architecture that provides a scheduling solution given privacy concerns in the Grid/Cloud. Finally, as a demonstration of the applicability of the approach, we apply our solution by integrating with Globus toolkit (a well adopted tool to enable Grid/Cloud computing environment). We also, created simulation experimental results to capture the economic and time efficiency of the proposed solution

Scheduling in Grid Computing Environment

Scheduling in Grid computing has been active area of research since its beginning. However, beginners find very difficult to understand related concepts due to a large learning curve of Grid computing. Thus, there is a need of concise understanding of scheduling in Grid computing area. This paper strives to present concise understanding of scheduling and related understanding of Grid computing system. The paper describes overall picture of Grid computing and discusses important sub-systems that enable Grid computing possible. Moreover, the paper also discusses concepts of resource scheduling and application scheduling and also presents classification of scheduling algorithms. Furthermore, the paper also presents methodology used for evaluating scheduling algorithms including both real system and simulation based approaches. The presented work on scheduling in Grid containing concise understandings of scheduling system, scheduling algorithm, and scheduling methodology would be very useful to users and researchersComment: Fourth International Conference on Advanced Computing & Communication Technologies (ACCT), 201