Dianhui Chu

A Service Composition Approach for the Fulfillment of Temporally Sequential Requirements

Traditional service composition approaches focus on selecting and composing multiple service components together to fulfill one single requirement. But in most real-world scenarios, there are multiple requirements raised by multiple consumers and they form a discrete and uneven flow (i.e., a temporal sequence). Due to the limited number of available services and their limited capacities, how to ensure the equilibrium between the satisfaction degrees of these temporally sequential requirements becomes an important issue to be addressed. This paper proposes an equilibrium-oriented service composition approach taking into account both the limitedness of service capacity and utilization of historical data. The temporal sequential requirements are divided gradually along with the formation of length-flexible time-segments one by one. Based on this segmentation, service capacity is preserved proportionally for the estimated future requirements, and multiple requirements within one segment are ensured to get relatively equal chances of being satisfied with relatively equal quality. Experiments reveal improved sustainability and superior temporal stability of service quality compared with applying traditional methods to this scenario.

Value Network Based Service Choreography Design and Evolution

We present a pattern-oriented service design and evolution approach by transforming the high-level service value network into service choreography scenario. In this approach, “value” is considered the ultimate goal of a service, and designing an executable SOA-based service system starts from the acquisition of business-level value exchange relationships between participants in the service. Such value information is modeled as Service Value Network (SVN). Following a four-step process, SVN is gradually mapped to software-level service choreography and the corresponding interface design, thereby keeping the consistency between both levels. Especially, we present five typical service value exchange patterns to facilitate the construction and transformation of SVN with higher efficiency. A case study from ocean transportation service is shown for demonstration.

A Case Study on Bi-lateral Resource Integration Oriented Marine Logistics Service System

Marine logistics service is one of the fundamental production services supporting the import and export businesses of other industries. The current marine logistics service eco-system formed spontaneously, and during its development, various types of service providers were stepwise imported and complex business collaborations formed between them. Based on our investigation on marine logistics services between South Korea and Weihai, China, we found that some deficiencies existed in such a decentralized service eco-system and led to non-optimized quality of marine logistics service. To solve these issues, we designed a bi-lateral resource integration oriented solution, in which a third-party service agency is established to help cargo owners and various logistics providers set up mutual service relationships, integrate bi-lateral resources, and monitor and evaluate quality/credit of services, thereby improving QoS and customer satisfaction. Business operation mechanisms, especially profit patterns, are briefly discussed. Benefits and disadvantages of BIRIS-based solutions are analyzed. Business and technological lessons learned from the solution are briefly put forward. Finally some possible directions for future innovations and improvements are discussed.

A Value-Driven Approach for the Determination of Global Optimization Objective of Service Composition

We present a value-driven approach capable of determining the global optimization objective of service composition to satisfy high-level value expectations. In traditional service composition methods, global and local QoS requirements and constraints are directly raised by customers, then a set of service components (web services) are selected to achieve the optimized QoS. Yet in practice, there is no mechanism helping customers accurately and comprehensively determine their QoS desires. In our approach, a customer’s initial expectations of high-level global values are first put forward, and then five types of dependencies between service values are analyzed. Because values are realized under the facilitation of specific service components, value expectations and value dependencies are transformed into the objective and constraints of service selection and composition, respectively. Another feature of our approach is that, besides web services, other generalized service components such as human activity and physical resources are considered as potential components for fulfilling value expectations. The effectiveness of our approach is demonstrated in a case study of ocean transportation service (OTS).

Architectural Design of BIRIS-Based Marine Logistics Service Platform and Related Interoperability Issues

Marine logistics service is one of the fundamental production services to support importing and exporting business. There are so many types of service providers (e.g., ship owners, freight forwarders, docks, warehouses, trucking companies, etc) interacting with each other to co-produce value to customers (i.e., cargo owners). Designing an IT-enabled service system to support such complex co-production and improve service quality is quite necessary. Based on investigation of current states and business requirements of this domain, we import BIRIS (bilateral resource integration service) as the mode of the marine logistics service platform. Architectural design of BIRIS-based platform is presented. Key business services are listed and a set of softwarized web services and their choreographic scenarios that support implementation of business services are illustrationally demonstrated. Several interoperability issues concerned in this platform are summarized and briefly discussed.

The Bundling of Multiple Requirements for Maximizing the Utilization of Service Resources

We present a service resource selection and scheduling approach capable of maximizing the resource utilization rate (RUT) and the requirement satisfaction degree (RSD) by bundling multiple customer requirements (CRs). In traditional approaches, each CR is optimally satisfied by independently selecting a set of candidate service resources. This possibly leads to a low RUT and low RSD. In our approach, multiple CRs raised within a certain time period are bundled and a virtual service resource (VSR) is constructed to satisfy these requirements simultaneously by making full use of the sharing nature of resources. Specifically, each CR is first decomposed into a set of atomic requirements, which are then re-aggregated according to their requested resources. For four types of service-resource sharing patterns, we present the corresponding greedy algorithms that construct the VSR and its scheduling. The goals of our methods are (1) maximizing the satisfaction degree of CRs and (2) maximizing the RUT of service resources. The effectiveness of our approach is demonstrated in an experiment for a typical scenario of ocean transportation service.

Personal Service Eco-Environment (PSE2): A User-Centric Services Computing Paradigm

Compared with manufacturing industries, service industries have a distinct characteristic called “heterogeneity”, i.e., there is a wide variation in service offerings to different customers due to their individualized demands. Traditional resource-centric services computing paradigm tries to make use of mass customization approaches to fulfill customer demands in a cost-effective way, but sacrifices the personalization degree and decreases customer satisfaction. We propose a user-centric paradigm called “Personal Service Eco-Environment (PSE2)” which plays as a “personal assistant” of each user. PSE2 is composed of personal data, services, and social relations around a user, and fully-personalized service/social collaboration solutions are to be planned on the basis of the individualized characteristics extracted from his personal data and the dynamic multi-end context. This paper introduces the high-level architecture and design philosophy of PSE2.

A Collaborative Filtering Recommendation Algorithm Based on User Preferences on Service Properties

In the service recommendation, the data of user ratings are usually very sparse. In the case of data sparsity, item similarity which is based on user ratings in the traditional item-based collaborative filtering algorithm ignores the situation that users are different in regarding various item properties. That results in the low accuracy when predicting. Based on this point, this paper proposed a collaborative filtering algorithm based on user preferences on service properties to solve the data sparsity problem in the service recommendation. This method firstly builds the service property preference model for each user based on information theory. Secondly, computes the service similarity correction factors of each user on any two services with service properties similarity. And finally the similarity of two services is the sum of service similarity correction factor and the Pearson correlation coefficient of them. The experiment results suggest that the proposed algorithm can efficiently improve the recommendation accuracy in the case of data sparsity.

Redundancy-Based Reliability Enhancement for Composite Services

Reliability is a key performance indicator of distributed service systems. On the condition that a customer raises a demand with a very strict reliability, it is possibly difficult for a service broker to offer a composite service that fully satisfies the reliability expectation. In the real world, the customers would like to pay extra money to assure the successful execution of a composite service, and the brokers usually adopt a redundancy-based mechanism to enhance the reliability of the composite service. The authors consider two scenarios of reliability enhancement: 1 a composite service exists but its reliability fails to meet the expectations of customers; and 2 no composite services exist yet, but it is known that the expected reliability is too high to be met. To handle them, the authors propose the RE-ECS and RE-PLN algorithms, respectively, in which three heuristic rules are proposed and the Artificial Bee Colony ABC algorithm are adopted to find an approximate optimal trade-off between the improvement extent and the total cost of the reliability enhancement. The authors use two traditional redundancy strategies i.e., sequential and parallel for enhancing the reliability a single service task, and a new redundancy strategy called path redundancy for extending a new path into a composite service to improve the global reliability. Nine experiments are conducted and some factors having potential influences on the effect, cost, and efficiency of the reliability enhancement are analyzed. This work is of significance for service brokers to build and enhance their composite services to satisfy those strict expectations on reliability.

A Classification Framework of Service Composition Issues in BIRIS Scenario

Service composition (SC) is currently one of the most popular research topics in service computing domain. Given a specific functional and non-functional requirements on a specific service, a composition algorithm selects a set of service components from an existing repository and composes them together as a total solution to fulfill the requirement. There have been fruitful achievements, e.g., template-based composition, planning-based composition, automated/semi-automated/manual composition, etc. However, along with BIRIS becomes a dominate form of modern service systems, a series of new appearing features bring great challenges to traditional SC researches, e.g., (1) from one single requirement to temporally sequential requirements, (2) the available services from abundant to limited, (3) from orchestration-oriented composition solution to choreography-oriented ones, (4) from specified requirements to ambiguous and personalized ones, (5) from the objective of maximizing customer satisfaction to ensuring the benefits of customers and providers together, etc. This paper analyzes these challenges elaborately and presents a classification framework which includes 4 dimensions and 13 sub-dimensions. Several typical SC issues in BIRIS scenario are identified under the framework.