AI Planning and Combinatorial Optimization for Web Service Composition in Cloud Computing
25 Apr 2010-pp 28-35
TL;DR: Experimental results show that a proposed method based on artificial intelligence (AI) planning and combinatorial optimization can more effectively and efficiently find sub-optimal cloud combinations.
Abstract: years, there has been an increasing interest in web service composition due to its importance in practical applications. At the same time, cloud computing is gradually evolving as a widely used computing platform where many different web services are published and available in cloud data centers. The issue is that traditional service composition methods mainly focus on how to find service composition sequence in a single cloud, but not from a multi-cloud service base. It is challenging to efficiently find a composition solution in a multiple cloud base because it involves not only service composition but also combinatorial optimization. In this paper, we first propose a framework of service composition in multi-cloud base environments. Next, three different cloud combination methods are presented to select a cloud combination subject to not only finding feasible composition sequence, but also containing minimum clouds. Experimental results show that a proposed method based on artificial intelligence (AI) planning and combinatorial optimization can more effectively and efficiently find sub-optimal cloud combinations.
Citations
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TL;DR: This paper develops a novel multi-cloud IoT service composition algorithm called E2C2 that aims at creating an energy-aware composition plan by searching for and integrating the least possible number of IoT services, in order to fulfil user requirements.
162 citations
Cites methods or result from "AI Planning and Combinatorial Optim..."
...Four different algorithms for selecting the cloud services combination were adopted for our comparative evaluation purposes: (All Clouds, Base Cloud, Smart Cloud [65], and COM2 [66])....
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...4 shows a comparison of the % reduction in the number of examined atomic services (relative to the baseline case for each MCP) by E2C2, All Clouds, Base Cloud, Smart Cloud, and COM2....
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...d have all confirmed previously published results in [65, 66]....
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TL;DR: Empirical results obtained from an agent-based testbed show that agents in this work can successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers’ service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants.
Abstract: Service composition in multi-Cloud environments must coordinate self-interested participants, automate service selection, (re)configure distributed services, and deal with incomplete information about Cloud providers and their services. This work proposes an agent-based approach to compose services in multi-Cloud environments for different types of Cloud services: one-time virtualized services, e.g., processing a rendering job, persistent virtualized services, e.g., infrastructure-as-a-service scenarios, vertical services, e.g., integrating homogenous services, and horizontal services, e.g., integrating heterogeneous services. Agents are endowed with a semi-recursive contract net protocol and service capability tables (information catalogs about Cloud participants) to compose services based on consumer requirements. Empirical results obtained from an agent-based testbed show that agents in this work can: successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers' service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants.
118 citations
TL;DR: A new hybrid method is proposed for efficient service composition in the cloud computing where the agent-based method is used to compose services by identifying the QoS parameters and the particle swarm optimization (PSO) algorithm is employed for selecting the best services based on fitness function.
Abstract: Cloud computing as a new computing paradigm has a great capacity for storing and accessing the remote data and services. Presently, many organizations decide to reduce the burden of local resources and support them by outsourcing the resources to the cloud. Typically, scalable resources are provided as services over the Internet. The way of choosing appropriate services in the cloud computing is done by determining the different Quality of Service (QoS) parameters to perform optimized resource allocation. Therefore, service composition as a developing approach combines the existing services to increase the number of cloud applications. Independent services can be integrated into complex composited services through service composition. In this paper, a new hybrid method is proposed for efficient service composition in the cloud computing. The agent-based method is also used to compose services by identifying the QoS parameters and the particle swarm optimization (PSO) algorithm is employed for selecting the best services based on fitness function. The simulation results have shown the performance of the method in terms of reducing the combined resources and waiting time.
117 citations
30 Nov 2010
TL;DR: This work presents a three-layered self-organizing multi-agent system that establishes a Cloud service composition framework and an experimental test bed, and indicates that service composition is efficiently achieved despite dealing with incomplete information as well as coping with dynamic service fees.
Abstract: In Cloud service composition, collaboration between brokers and service providers is essential to promptly satisfy incoming Cloud consumer requirements. These requirements should be mapped to Cloud resources, which are accessed via web services, in an automated manner. However, distributed and constantly changing Cloud-computing environments pose new challenges to automated service composition such as: (i) dynamically contracting service providers, which set service fees on a supply-and-demand basis, and (ii) dealing with incomplete information regarding Cloud resources (e.g., location and providers). To address these issues, in this work, an agent-based Cloud service composition approach is presented. Cloud participants and resources are implemented and instantiated by agents. These agents sustain a three-layered self-organizing multi-agent system that establishes a Cloud service composition framework and an experimental test bed. The self-organizing agents make use of acquaintance networks and the contract net protocol to evolve and adapt Cloud service compositions. The experimental results indicate that service composition is efficiently achieved despite dealing with incomplete information as well as coping with dynamic service fees.
97 citations
Patent•
24 Nov 2010TL;DR: In this paper, a deployment engine can identify similar target resources available in a set of target clouds, and the engine can receive selection criteria for selecting target clouds for a migration of the user's deployment.
Abstract: Embodiments relate to systems and methods for combinatorial optimization of multiple resources across a set of cloud-based networks. In aspects, a set of usage histories can store patterns for users in a host cloud-based network recording the consumption of processor, memory, storage, operating system, application, or other resources subscribed to by the user. The user can be a corporation or other collective user. A deployment engine can identify similar target resources available in a set of target clouds. The engine can receive selection criteria for selecting target clouds for a migration of the user's deployment. In the combinatorial selection, each target cloud can independently supply one or more target resources. The engine can thus identify a series of combinations of target resources and target clouds supplying those resources to discover combinations of target clouds and target resources that can satisfy or optimize the selection criteria, such as cost or others.
90 citations
References
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Proceedings Article•
30 Jul 2001
TL;DR: The overall structure of the ontology, the service profile for advertising services, and the process model for the detailed description of the operation of services are described, which compare DAML-S with several industry efforts to define standards for characterizing services on the Web.
Abstract: The Semantic Web should enable greater access not only to content but also to services on the Web. Users and software agents should be able to discover, invoke, compose, and monitor Web resources offering particular services and having particular properties. As part of the DARPA Agent Markup Language program, we have begun to develop an ontology of services, called DAML-S, that will make these functionalities possible. In this paper we describe the overall structure of the ontology, the service profile for advertising services, and the process model for the detailed description of the operation of services. We also compare DAML-S with several industry efforts to define standards for characterizing services on the Web.
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2,472 citations
06 Jul 2004
TL;DR: An overview of recent research efforts of automatic Web service composition both from the workflow and AI planning research community is given.
Abstract: In today’s Web, Web services are created and updated on the fly. It’s already beyond the human ability to analysis them and generate the composition plan manually. A number of approaches have been proposed to tackle that problem. Most of them are inspired by the researches in cross-enterprise workflow and AI planning. This paper gives an overview of recent research efforts of automatic Web service composition both from the workflow and AI planning research community.
1,216 citations
"AI Planning and Combinatorial Optim..." refers background in this paper
...In recent years, people become more interested in web services because of its potential power in real applications....
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...Keywords Service Composition, Multi-Cloud Base, Cloud Combination, Composition Planner...
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09 Jun 2002
TL;DR: DAML-S is presented, a DAML+OIL ontology for describing the properties and capabilities of Web Services, and three aspects of the ontology are described: the service profile, the process model, and the service grounding.
Abstract: In this paper we present DAML-S, a DAML+OIL ontology for describing the properties and capabilities of Web Services. Web Services - Web-accessible programs and devices - are garnering a great deal of interest from industry, and standards are emerging for low-level descriptions of Web Services. DAML-S complements this effort by providing Web Service descriptions at the application layer, describing what a service can do, and not just how it does it. In this paper we describe three aspects of our ontology: the service profile, the process model, and the service grounding. The paper focuses on the grounding, which connects our ontology with low-level XML-based descriptions of Web Services.
1,018 citations
"AI Planning and Combinatorial Optim..." refers background in this paper
...…cloud computing platforms, such as Windows Azure Platform [3] and Amazon S3[4], it will be very common for service providers to publish their web services at different cloud platforms, which has distinctive advantages such as adaptivity, scalability and transparency of load scheduling....
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TL;DR: A sound and complete algorithm is provided to translate OWL-S service descriptions to a SHOP2 domain and it is proved the correctness of the algorithm by showing the correspondence to the situation calculus semantics of OWl-S.
819 citations
"AI Planning and Combinatorial Optim..." refers background in this paper
...When there is no single service has the capability to satisfy a service requester’s requirement, service composition is needed to select several correlative web services together for the purpose of fulfilling the service requester’s goal....
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