A Multiagent System for the Reliable Execution of Automatically Composed Ad-hoc Processes

This article presents an architecture to automatically create ad-hoc processes for complex value-added services and to execute them in a reliable way. The uniqueness of ad-hoc processes is to support users not only in standardized situations like traditional workflows do, but also in unique non-recurring situations. Based on user requirements, a service composition engine generates such ad-hoc processes, which integrate individual services in order to provide the desired functionality. Our infrastructure executes ad-hoc processes by transactional agents in a peer-to-peer style. The process execution is thereby performed under transactional guarantees. Moreover, the service composition engine is used to re-plan in the case of execution failures. The work presented in this article was supported by the Swiss National Science Foundation as part of the project MAGIC (FNRS-68155), as well as by the Swiss National Funding Agency OFES as part of the European projects KnowledgeWeb (FP6-507482) and DIP (FP6-507483). Authors in alphabetic order     

Efficient access to Web services

For Web services to expand across the Internet, users need to be able to efficiently access and share Web services. The authors present a query infrastructure that treats Web services as first-class objects. It evaluates queries through the invocations of different Web service operations. Because efficiency plays a central role in such evaluations, the authors propose a query optimization model based on aggregating the quality of Web service (QoWS) parameters of different Web services. The model adjusts QoWS through a dynamic rating scheme and multilevel matching in which the rating provides an assessment of Web services' behavior. Multilevel matching allows the expansion of the solution space by enabling similar and partial answers.     

Enabling portability in advanced information-centric services over structured peer-to-peer systems

A common factor among all the existing distributed, peer-to-peer systems is their lack of genericity. Typically, information-centric services (such as range queries) are deployed ad-hoc onto a specific peer-to-peer overlay. These kinds of solutions make them probably efficient but non-portable to other peer-to-peer infrastructures, and so the services and applications constructed over them. We do believe, instead, that a peer-to-peer-generic solution is feasible. In this paper, we tackle the genericity and portability issue specifically on structured peer-to-peer networks (SPNs).To do so, we introduce a distributed 3-layer architecture, which abstracts applications (on top of the architecture) and the peer-to-peer network currently in use (in the bottom layer). Our middleware appears in the middle layer, which is responsible to address two major challenges: (i) supporting complex, multi-dimensional application data domains and (ii) performing efficiently for a wide variety of information-centric services in the large scale.Broadly speaking, information-centric services are classified as data management (such as range or spatial queries) and content distribution services (like publish/subscribe), and our middleware is an umbrella for all them. Notice that data management services are based on the pull mode (i.e., a user lookups information previously stored in the system), whilst content distribution services obey to a push mode (i.e., the system delivers the information timely to users).The benefits of our approach are clear: (i) Our middleware can be easily deployed over existing SPNs, guaranteeing the portability of a critical mass of services and end-user applications; (ii) Several services can be added to the middleware, which will facilitate the appearance of new synergies; and (iii) our middleware deals with the application data domain transparently to services and applications, including the necessary algorithms for services to be efficiently deployed into our middleware.     

A two-phase framework for quality-aware Web service selection

Service-oriented computing is gaining momentum as the next technological tool to leverage the huge investments in Web application development. The expected large number of Web services poses a set of new challenges for efficiently accessing these services. We propose an integrated service query framework that facilitates users in accessing their desired services. The framework incorporates a service query model and a two-phase optimization strategy. The query model defines service communities that are used to organize the large and heterogeneous service space. The service communities allow users to use declarative queries to retrieve their desired services without worrying about the underlying technical details. The two-phase optimization strategy automatically generates feasible service execution plans and selects the plan with the best user-desired quality. In particular, we present an evolutionary algorithm that is able to “co-evolve” multiple feasible execution plans simultaneously and allows them to compete with each other to generate the best plan. We conduct a set of experiments to assess the performance of the proposed algorithms.     

Network-Sensitive Service Discovery

We consider the problem of network-sensitive service selection (NSSS): finding services that match a particular set of functional and network properties. Current solutions handle this problem using a two-step process. First, a user obtains a list of candidates through service discovery. Then, the user applies a network-sensitive server selection technique to find the best service. Such approaches are complex and expensive since each user has to solve the NSSS problem independently. In this paper, we present a simple alternative: network-sensitive service discovery (NSSD). By integrating network-sensitivity into the service discovery process, NSSD allows users who are looking for services to specify both the desired functional and network properties at the same time. Users benefit since they only have to solve a restricted version of the server selection problem. Moreover, NSSD can solve the NSSS problem more efficiently by amortizing the overhead over many users. We present the design of NSSD, a prototype implementation, and experimental results that illustrate how NSSD can be used for different applications.     

Gneiss: spreadsheet programming using structured web service data

Web services offer a more reliable and efficient way to access online data than scraping web pages. However, interacting with web services to retrieve data often requires people to write a lot of code. Moreover, many web services return data in complex hierarchical structures that make it difficult for people to perform any further data manipulation. We developed Gneiss, a tool that extends the familiar spreadsheet metaphor to support using structured web service data. Gneiss lets users retrieve or stream arbitrary JSON data returned from web services to a spreadsheet using interaction techniques without writing any code. It introduces a novel visualization that represents hierarchies in data using nested spreadsheet cells and allows users to easily reshape and regroup the extracted structured data. Data flow is two-way between the spreadsheet and the web services, enabling people to easily make a new web service call and retrieve new data by modifying spreadsheet cells. We report results form a user study that showed that Gneiss helped spreadsheet users use and analyze structured data more efficiently than Excel and even outperform professional programmers writing code. We further use a set of examples to demonstrate our tool's ability to create reusable data extraction and manipulation programs that work with complex web service data.     

有向图上的广义可达性查询处理方法

随着社会网络、生物信息学、本体等应用的迅速发展,如何在图上进行高效的信息检索成为一个亟待解决的问题。两点间可达性查询是一种常见的查询方式,目前针对此类查询已经提出了许多算法。但是在一些应用中,这种查询语义并不能满足用户需求。基于此,提出了两种广义可达性查询语义。研究了如何在大图上进行高效的广义可达性查询的问题,依据Path-tree编码的特性提出了一种新的二级索引机制——RB+索引。基于RB+索引,针对不同类型查询提出了两种高效的查询处理方法。该方法充分利用Path-tree编码的特性,有效地处理广义可达性查询。通过实验对提出的索引和查询算法进行了验证。     

Automatic Transaction Compensation for Reliable Grid Applications

Abstract As grid technology is expanding from scientific computing to business applications, service oriented grid computing is aimed at providing reliable services for users and hiding complexity of service processes from them. The grid services for coordinating long-lived transactions that occur in business applications play an important role in reliable grid applications. In this paper, the grid transaction service （GridTS） is proposed for dealing with long-lived business transactions. We present a compensation-based long-lived transaction coordination algorithm that enables users to select results from committed sub-transactions. Unlike other long-lived transaction models that require application programmers to develop corresponding compensating transactions, GridTS can automatically generate compensating transactions on execution of a long-lived grid transaction. The simulation result has demonstrated the feasibility of GridTS and effectiveness of the corresponding algorithm.     

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system,in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers.Such queries are based on local filter query statistics,and require as less communication cost as possible,which makes it more difficult than the existing distributed k-NN queries.Especially,we hope to reduce candidate peers and degrade communication cost.In this paper,we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries.Our approach is especially suitable for continuous k-NN queries when updating peers,including changing ranges of peers,dynamically leaving or joining peers,and updating data in a peer. In addition,simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR.)-based query approaches,especially for continuous queries.     

基于对等网络的全球信息网格服务发现机制研究

全球信息网格采用面向服务的架构提高系统的可重用性、柔性设计能力以及按需快速构建能力。这些优势的充分发挥需要快速及时发现各类可用的数据和服务。该文提出了两种扩展性很好的分布式服务发现机制：面向完全自治UDDI注册中心的非结构化UDDI对等网络和面向协同UDDI注册中心的结构化UDDI对等网络。     

Network-aware service placement and selection algorithms on large-scale overlay networks

Currently many service providers offer their services on a private and proprietary hard- and software infrastructure. These infrastructures often share many similarities. Hence we believe a generic service management architecture, that allows service providers to offer a large array of different services on a single infrastructure or multiple providers to offer their services cooperatively, would provide many advantages over current silo-based approaches. Additionally, by allowing the distributed service management components to cooperate in a peer-to-peer overlay network, scalability and resilience of the system could be greatly improved.In this paper we propose an optimal algorithm, based on an integer linear programming (ILP) formulation, and several heuristics to support such a generic overlay-based service management architecture. More specifically, we propose algorithms for dynamically allocating server and network resources to a set of services and selecting a suitable service instance for each client. Service instances are placed on a set of servers, taking into account server resource constraints (e.g. CPU and memory). Unlike existing algorithms for this problem, those proposed in this paper also support service level agreements (SLAs), which take the form of Quality of Service demands such as transmission latency constraints and bandwidth requirements. The optimisation goal is to maximise the percentage of satisfied demand (answered requests) and minimise the total number of required overlay servers, while satisfying the SLAs and resource constraints. Additionally, we propose an extension that allows the algorithms to find overlay routing paths to improve the transmission latency for latency-sensitive services.Extensive simulations were performed to evaluate the performance and scalability of the heuristics. They showed that in many cases the heuristics perform close to optimal and they scale well in terms of network size.     

Enhancing Computational Grids with Peer-to-Peer Technology for Large Scale Service Discovery

Within computational Grids, some services (typically software components, e.g., linear algebra libraries) are made available by some servers to some clients. In spite of the growing popularity of such Grids, the service discovery, although efficient in many cases, does not reach several requirements. Among them, the flexibility of the discovery and its efficiency on wide-area dynamic platforms are two major issues. Therefore, it becomes crucial to propose new tools coping with such platforms. Emerging peer-to-peer technologies provide algorithms allowing the distribution and the retrieval of data items while addressing the dynamicity of the underlying network. Whereas merging peer-to-peer technology and Grid infrastructures has been widely suggested, very few implementations are available. The contribution of this paper is twofold. First, we present the design, the implementation and the experimentation of the first architecture, to our knowledge, extending traditional Network-Enabled Servers (NES) systems with an unstructured peer-to-peer network. This extension allows to dynamically connect distributed agents thus providing to clients an entry point to servers geographically distributed. Our implementation is based on the Diet middleware and the JXTA toolbox and experimentation have been conducted on a high speed network. Then, we study the service discovery in a pure peer-to-peer environment. We describe a new trie-based approach for the peer-to-peer service discovery service, supporting range queries while providing fault-tolerance and taking into account the topology of the underlying network. We validate this approach both by analysis and simulation. This work has been supported in part by the ANR project LEGO (ANR-05-CIGC-11).     

User-private information retrieval based on a peer-to-peer community

Private information retrieval (PIR) is normally modeled as a game between two players: a user and a database. The user wants to retrieve some item from the database without the latter learning which item is retrieved. Most current PIR protocols are ill-suited to provide PIR from a search engine or large database: (i) their computational complexity is linear in the size of the database; (ii) they assume active cooperation by the database server in the PIR protocol. If the database cannot be assumed to cooperate, a peer-to-peer (P2P) user community is a natural alternative to achieve some query anonymity: a user gets her queries submitted on her behalf by other users in the P2P community. In this way, the database still learns which item is being retrieved, but it cannot obtain the real query histories of users, which become diffused among the peer users. We name this relaxation of PIR user-private information retrieval (UPIR). A peer-to-peer UPIR system is described in this paper which relies on an underlying combinatorial structure to reduce the required key material and increase availability. Extensive simulation results are reported and a distributed key management version of the system is described.     

Fuzzy approach to the intelligent management of virtual spaces.

This paper presents research carried out toward the improvement of current virtual environments from an intelligent systems approach. A novel architecture to solve vague queries that allows users to find objects and scenes in virtual environments is described. As a base, a new virtual worlds representation model and an associated fuzzy querying approach are used. The new representation model adds a semantic level to the usual models, providing more suitable environments for the interaction with users. The query solver is able to work with queries expressing the vagueness inherent to human conceptualization of visual perception (for example, tall tree, a park with many tall trees, or a park bench near approximately five tall trees). The system has been developed and evaluated with user experiments, where comparison with navigation and keyword-based query approaches have been realized. The results of this study show that the proposed architecture is more powerful and intuitive for finding the targets.     

Toward high-precision service retrieval

Online repositories are increasingly called on to provide access to services that describe or provide useful behaviors. Existing techniques for finding services offer low retrieval precision, returning many irrelevant matches. We introduce a novel service retrieval approach that captures service semantics using process models, and applies a pattern-matching algorithm to find the services with the behavior the user wants. Evaluations suggest that process-based queries offer substantially greater retrieval precision than existing approaches and scale well with the number of services being accessed.     

Modeling and analysis of the effects of QoS and reliability on pricing, profitability, and risk management in multiperiod grid-computing networks

In this paper we develop a network equilibrium model for optimal pricing and resource allocation in Computational Grid Network. We consider a general network economy model with Grid Resource Providers, Grid Resource Brokers and Grid Users. The proposed framework allows for the modeling and theoretical analysis of Computational Grid Markets that considers a non-cooperative behavior of decision-makers in the same tier of the grid computing network (such as, for example, Grid Resource Providers) as well as cooperative behavior between tiers (between Resource Providers and Grid Brokers). We introduce risk management into the decision making process by analyzing the decision-marker's reliability and quality of service (QoS) requirement. We analyze resource allocation patterns as well as equilibrium price based on demand, supply, and cost structure of the grid computing market network. We specifically answer the following questions with several numerical examples: How do system reliability levels affect the QoS levels of the service providers and brokers under competition? How do system reliability levels affect the profits of resource providers and brokers in a competitive market? How do system reliability levels influence the pricing of the services in a competitive environment? How do users' service request types, QoS requirements, and timing concerns affect users' behaviors, costs and risks in equilibrium? How does the market mechanism allocate resources to satisfy the demands of users? We find that for users who request same services certain timing flexibility can not only reduce the costs but also lower the risks. The results indicated that the value of QoS can be efficiently priced based on the heterogeneous service demands.     

The DYNAMOS approach to support context-aware service provisioning in mobile environments

To efficiently make use of information and services available in ubiquitous environments, mobile users need novel means for locating relevant content, where relevance has a user-specific definition. In the DYNAMOS project, we have investigated a hybrid approach that enhances context-aware service provisioning with peer-to-peer social functionalities. We have designed and implemented a system platform and application prototype running on smart phones to support this novel conception of service provisioning. To assess the feasibility of our approach in a real-world scenario, we conducted field trials in which the research subject was a community of recreational boaters.     

Online role mining for context-aware mobile service recommendation

Finding and recommending suitable services for mobile devices are increasingly important due to the popularity of mobile Internet. While recent research has attempted to use role-based approaches to recommend services, role discovery is still an ongoing research topic. Using role-based approaches, popular mobile services can be recommended to other members in the same role group in a context- dependent manner. This paper proposes several role mining algorithms, to suit different application requirements, that automatically group users according to their interests and habits dynamically. Most importantly, we propose an online role mining algorithm that can discover role patterns efficiently and incrementally. Finally, we present a complete, question-based framework that can efficiently perform role mining for context-aware service recommendation in a mobile environment—where a device may not be always connected to the server and/or scalability of the role mining algorithm running on the server is critical.     

A Query Routing Approach Based on Users’ Satisfaction for Resource Discovery in Service-Oriented Networks

Service oriented networks are distributed computing infrastructures that provide widely distributed resources. These networks are dynamic and their size and complexity continue to increase and allow to users a ubiquitous access to available resources and services. Therefore, efficient query routing approaches in large and highly distributed service oriented networks are required and need to be adaptive in order to cope with a dynamically changing environment. In this paper, a query routing approach based on mobile agents and random walks with a reinforcement learning technique is presented. By enhancing random walks with a reinforcement learning mechanism centered on users’ satisfaction, this approach allows dynamic and self-adaptive location of required resources. Peers incorporate knowledge from past and present queries which will be used during next searches by mobile agents to select their next hops. This approach is analyzed through two query routing techniques using the network simulator ns2.