Chaotic systems have attracted extensive research due to their pseudorandomness, ergodicity, and unique properties. Most studies focus on chaotic systems in the real number domain, but recent research has explored the design of complex chaotic systems. However, the chaotic behaviors of previous complex chaotic systems can only be observed through experiments and lack theoretical proof. In this article, we construct a 2-D coupled complex chaotic (2D-CCC) map using two nonlinear functions in the complex number domain. We theoretically prove the robust and complex chaotic behavior of the 2D-CCC map using the Lyapunov exponent. In addition, we conduct extensive experiments to demonstrate the map's intricate dynamics and high performance indicators. Comparison results highlight its superiority over previous chaotic systems. We also implement our 2D-CCC map on a hardware platform to validate its implementation feasibility on hardware devices. Finally, we investigate the 2D-CCC map's application in pseudorandom number generation and the testing results validate the high degree of randomness in the generated pseudorandom numbers.

The recent emergence of gig economy facilitates the exchange of skilled labor by allowing workers to showcase and sell their skills to a global market. Despite the recent effort on thoroughly examining who workers in the gig economy are and what their experience in the gig economy are like, our knowledge on how exactly do workers provide their skills in gig economy, and how worker's strategies on skill provision and expansion relate to their success in gig economy is still lacking. In this paper, we conduct a case study on a prominent gig economy platform, Fiverr.com, to better understand the provision of skills on it through large-scale, data-driven analysis. In particular, we propose the concept of "skill space" from a network perspective to characterize the relationship between different skills by measuring how frequently workers provide different skills together. Through our analysis, we reveal interesting patterns in worker's provision of skills on Fiverr. We then show how these patterns change over time and differ across subgroups of workers with different characteristics. In addition, we find that providing a set of skills that are highly related with each other correlates with a better overall performance in gig economy, and when workers expand their skillsets, expanding to a new skill that is highly-related to the existing skills takes less time and is associated with better performance on the new skill. We conclude by discussing the implications of our findings for gig economy workers and platform in general.

With the sweeping progress of service computing technology and crowdsourcing, individuals are offering their capability as human services online. Companies are orchestrating human services for complex problem-solving, resulting in the rapid growth of human service ecosystems nowadays. Considering the unique characteristics of human services, like capability growth and human-involving collaboration, it is essential to understand the patterns of the development and collaboration among human services. Therefore, this paper proposes a three-layer time-aware heterogeneous network model to quantify the evolution in the human service ecosystem. Based on the model, an exploratory empirical study is presented to uncover how human service providers and consumers develop their capability in service provision and orchestration, as well as how human services collaborate with each other over time. Insights from the emerging patterns open a gateway for further research to facilitate human service adoption, including human service composition recommendation, human skill expansion suggestion, and systematic mechanism design.

Android system has been the crucial platform for the mobile service ecosystem. As a typical open source project, the release of the android system is a challenging issue because many developers are working on the related projects and it will affect millions of mobile service running on the platform. Therefore, investigating the release process of Android system is important for the mobile service ecosystem. Particularly, in this paper, we will focus on the release features prediction issue of what features should be included in the new publishing version. The valid changes and release notes are transformed into low-dimensional vectors and then the automatic labelling methodology is developed to detect the features. Combing with the time series forecasting model, an approach to predict the published features in the new version is presenting. Based on the data collected from the Android Open Source Project (AOSP), the experiments show that: comparing with the state-of-the-art, our approach achieves 13.83% to 17.69% precision improvement in releasing feature predictions and we can effectively detect the spike features for further compatibility management.

A wide array of clouds have been built and adopted by business and research communities. Similarly, many research communities use workflow environments and tools such as Taverna and Galaxy to model the execution of tasks to support and expedite the reenactment of complex processes, and ultimately support the repeatability of science. As a result, a number of systems that integrate clouds with these workflow systems have emerged including CloudMap, CloudMan, Galaxy cloud, BioBlend, etc. Though these systems have proven to be successful in service and data integration, they have not dealt with the data security issue inherent in cloud-based systems with the outsourced models of infrastructure provisioning. For many domains, e.g., health, this poses serious challenges regarding the adoption of cloud infrastructures. Yet such domains also have much to gain from clouds especially given the explosion of genomics data and opportunities for personalized medicine in the big data era. This paper addresses this problem by presenting a trusted storage cloud for scientific workflows, called TruXy. The paper describes the TruXy architecture, the corresponding protocols and illustrates the adoption of TruXy to support collaborative bioinformatics research in endocrine genomics. A range of experiments have been performed to measure the performance of TruXy for processing of exome data sets on individuals with a rare genetic disorders: disorders of sex development (DSD). Our results show that the performance of TruXy is comparable to that of using a standalone workflow tool and that it can handle the big data security challenges required.

In the paradigm of service oriented science, scientific computing applications and data are all wrapped as web accessible services. Scientific workflows further integrate these services to answer complex research questions. However, our earlier study conducted on myExperiment has revealed that although the sharing of service-based capabilities opens a gateway to resource reuse, in practice, the degree of reuse is very low. This finding has motivated us to propose ServiceMap to provide navigation facility through the network of services to facilitate the design and development of scientific workflows. This paper proposes ReputationNet as an enhancement of ServiceMap, to incorporate the often-ignored reputation aspects of services/workflows and their publishers, in order to offer better service and workflow recommendations. We have developed a novel model to reflect the reputation of e-Science services/workflows, and developed heuristic algorithms to provide service recommendations based on reputations. Experiments on myExperiment have illustrated a strong positive correlation (with Pearson correlation coefficient 0.82) between the reputation scores computed and the actual performance (i.e. usage frequency) of the services/workflows, which demonstrates the effectiveness of our approach.

The Internet has been encouraging and enabling business collaborations via online transactions over the Web. However, managing transactions in a long-running business process across domains still remains a challenge. In this paper, we propose a novel financial-compensation-based transaction management model, fcBTxM, to address this challenge. Unlike classical transaction management, fcBTxM does not attempt to recover data consistency via rollback when a failure occurs. Instead, our model always tries to forward-roll a business process via financial compensation. We use a state machine to capture and describe the states of our transaction model and their relationships. We also develop a set of technologies and protocols for enabling the new transaction management. A real business collaboration example is used to demonstrate the concept, and preliminary testing results are provided to evaluate our technologies.

In this paper, we propose a secure cloud storage service architecture with the focus on Data Integrity as a Service (DIaaS) based on the principles of Service-Oriented Architecture and Web services. Our approach not only releases the burdens of data integrity management from a storage service by handling it through an independent third party data Integrity Management Service (IMS), but also reduces the security risk of the data stored in the storage services by checking the data integrity with the help of IMS. We define data integrity protocols for a number of different scenarios, and demonstrate the feasibility of the proposed architecture, service and protocols by implementing them on a public cloud, Amazon S3. We also study the impact of our proposed protocols on the performance of the storage service and show that the benefits of our approach outweigh the little penalty on the storage service performance.

In recent years, we witnessed a range of innovations in the 'service' related technologies, such as Software as a Service, Platform as a Service and Infrastructure as a Service. Along with the Service Oriented Architecture, companies can wrap their technological product as a service, to collaborate with others. Facing the ever-escalating global competition, such collaboration is crucial. The viability of this paradigm highly depends on the compliance and therefore the trustworthiness of all collaborators. However, it is challenging to achieve trustworthiness in such a dynamic cross-domain environment, as each participator may deceit for individual benefits. As a solution, we have proposed to enforce strong accountability to enhance the trustworthiness. With this accountability, incompliance can always be determined in a provable and undeniable way. In this paper, we extend our work by proposing a novel modeling of the collaborative business process. Based on this modeling, we thoroughly analyze the evidence and proving procedure needed for different types of compliance, and evaluate the extent to which those compliance can be indeed proved. We have implemented a demonstrative system to show its effectiveness in real practice.

The enormous amount of data generated in daily operations and the increasing demands for data accessibility across organizations are pushing individuals and organizations to outsource their data storage to cloud storage services. However, the security and the privacy of the outsourced data goes beyond the data owners' control. In this paper, we propose a service composition approach to preserve privacy for data stored in untrusted storage service. A virtual file system, called Trust Store, is prototyped to demonstrate this concept. It allows users utilize untrusted storage service provider with confidentiality and integrity of the data preserved. We deployed the prototype with Amazon S3 and evaluate its performance.

Summary form only given. Accountability in Service Oriented Architecture (SOA) is a capability of making business processes across all participants (services, applications and people) accountable in terms of both business logic and Quality of Services (QoS). While accountability is a critical mechanism to enhance trust between collaborative services, there is the lack of standard accountability support in the current SOA infrastructure. For example, it is difficult with the existing technologies/infrastructure to resolve a dispute between two (web) services if some interactions between the two services go wrong; there is also little existing accountability support for a service consumer to collect quantity evidences to complain a service provider, who fails to meet its Service Level Agreement (SLA). As the increasing real-world activities are performed through the Internet connected services, we envision that there will be growing requirements for making the behaviors of both service providers and consumers accountable. In the business world, one may be reluctant to transact directly with a stranger. But a mutually trusted middleman can be used to facilitate transactions and resolve possible disputes. In this tutorial, we will share our observations and research results on building accountability into SOA. First, we will review related work on accountability in traditional distributed systems, ranging from Internet protocols and network file systems to outsourced database management systems. We will examine what methods embodied in these work can fit service computing in Internet scale and what cannot. Then we will present our research work on middleman-based approach to delivering accountability as a service, including our recent research results. This tutorial will focus on the major technical challenges of enabling SOA accountable and our solutions to these challenges. Finally, we will demonstrate our solutions using a collaborative services scenario deployed in Amazon EC^2 cloud. The goal of this tutorial is to provide detailed understanding of accountability issues and related technologies in SOA with in-depth related work discussions, recent research outcomes and a deployed accountability service prototype.