As IoT and robotics applications continue to become increasingly complex and decentralized, there is an increase in the difficulty of verifying requirements such as guarantees of reliability, efficiency, and correctness of the entire system. Modern IoT and robotics research and applications employ a variety of technologies to accommodate the distribution of real world IoT devices. Many of these technologies support the orchestration of these devices with concurrent computation and workflow-based processing, e.g., Intel Service Orchestration Layer. We developed a new workflow-based programming language VIPLE (Visual IoT/Robotics Programming Language Environment), which supports the orchestration of decentralized IoT and robotics devices through concurrent computation. VIPLE has been used by many universities for teaching robotics programming, event-driven computing, service-oriented computing, and parallel computing concepts. Historically, simple single threaded applications could be verified by employing formal systems such as Hoare logic. It is difficult to verify parallel and distributed computing. In our recent research, we developed a novel system to verify the semantics and other requirements of decentralized applications written in VIPLE. This system is developed using a combination of the techniques offered in Hoare logic and Rely-Guarantee logic, and it is applied using the automatically generated Pi-Calculus representation of VIPLE applications. This paper focuses on the foundations of this system, its ability to handle concurrent computing and decentralized applications, as well as its ability to support automated verification and semantic analysis.

In cloud computing, data is duplicated to prevent data loss. One way to achieve data consistency in such a distributed computing systems is to use a blockchain. Based on practical Byzantine fault tolerance (PBFT), a specific type of blockchain, this paper proposes a synchronous Byzantine fault tolerance (SBFT) algorithm that not only maintains data consistency, but also has much higher efficiency than other general blockchain algorithms. We provide experimental results that demonstrate the algorithm's data consistency, efficiency, and reliability.

Machine learning is a new paradigm of problem solving. Teaching machine learning in schools and colleges to prepare the industry's needs becomes imminent, not only in computing majors, but also in all engineering disciplines. This paper develops a new, hands-on approach to teaching machine learning by training a linear classifier and applying that classifier to solve Multirotor Activity Recognition (MAR) problems in an online lab setting. MAR labs leverage cloud computing and data storage technologies to host a versatile environment capable of logging, orchestrating, and visualizing the solution for an MAR problem through a user interface. This work extends Arizona State University's Visual IoT/Robotics Programming Language Environment (VIPLE) as a control platform for multi-rotors used in data collection. VIPLE is a platform developed for teaching computational thinking, visual programming, Internet of Things (IoT) and robotics application development.

Information processing of guide dog robot requires expensive computing resources to meet real-time performance. We propose an edge computing framework based on Intel Up-Squared board and neural compute stick. Image processing and real-time control are performed on the framework. In addition, the voice recognition and commanding are also implemented, which are processed on Amazon cloud service. Vision, speech, and control services are integrated by ASU VIPLE (Visual IoT/Robotics Programming Language Environment). A prototype is developed, which implements the guide dog's obstacle avoidance, traffic sign recognition and following, and voice interaction with human.

With the wide deployment of various kinds of sensors in fixed infrastructures and in mobile devices, technologies and applications of crowd-sensing has drawn attentions in the fields of mobile computing. This paper studies the design of frameworks for crowd-sensing process in a distributed environment. We discuss the realization of the compatibilities of devices and services, as well as the algorithms of dealing with transmitting and accessing large amount of sensing data. We present a new distributed crowd-sensing framework called DASF, which is based on context data servers. The framework consists of three layers: hardware device layer, context data layer, and smart service layer. The key innovations and features of the framework are illustrated in detail. Through experiments and results analyses, DASF is shown to have good compatibility in heterogeneous device platforms, and it is capable of dealing with heavy load of accessing with practical significance.

As IoT/robotics research and applications expand explosively into many domains in computing, information, and control systems, schools and universities must prepare students to understand and be able to program IoT devices and robots. However, programming IoT and physical devices is hard and depends on good understanding of hardware and low-level programming. Workflow and visual programming environments have been developed to address this issue, including MIT App Inventor, Microsoft Robotics Developer Studio and VPL (Visual Programming Language), and Intel Service Orchestration Layer. We have developed a new visual programming language and its development environment: ASU VIPLE (Visual IoT/Robotics Programming Language Environment). ASU VIPLE is specifically developed to support different device platforms. It supports LEGO EV3 and all IoT devices based on an open architecture. ASU VIPLE integrates engineering design process, workflow, fundamental programming concepts, control flow, parallel computing, and event-driven programming seamlessly into the curriculum. It has been pilot tested at Arizona State University in summers 2015 and 2016, and is now taught in an ASU regular class, Introduction to Engineering. It has been adopted by numerous universities around the world. This paper focuses on the mathematical model of ASU VIPLE. π-calculus is used to describe the basic activities in VIPLE, as well as the workflow defined by the basic activities.

Cloud computing and virtualization technologies play important roles in modern service-oriented computing paradigm. More conventional services are being migrated to virtualized computing environments to achieve flexible deployment and high availability. We introduce a schedule algorithm based on fuzzy inference system (FIS), for global container resource allocation by evaluating nodes' statuses using FIS. We present the approaches to build containerized test environment and validates the effectiveness of the resource allocation policies by running sample use cases. Experiment results show that the presented infrastructure and schema derive optimal resource configurations and significantly improves the performance of the cluster.

This paper reports the newly designed programming course developed and taught at Zhejiang University for a freshman class majoring in information science and electronic engineering, and disseminated to many other universities, to address the enrollment crisis as reported by ACM Curriculum Committee Review Task Force. The course teaches the basic information science and electronic engineering concepts and gives the students practical programming experience through robotics programming. The initial curriculum and the ongoing improvement of the course are presented. The course started with its experiment environment using ASU Visual IoT/Robotics Programming Environment (VIPLE). The environment supports a variety of platforms, including open architecture-based robots, such as Intel robots, PCDuino robots, vendor-specific robots, such as Lego EV3, as well as simulated robots, such as Web simulated robots in HTML5 and Unity-based 3D robots.

This paper reports the newly designed first computer science and first programming course CSE101 developed and taught at Arizona State University, and disseminated to many other universities, to address the enrollment crisis as reported by ACM CS Curriculum Committee Review Task Force in 2008. The course teaches the basic computer science and engineering concepts and gives the students the first programming experience through robotics programming. The initial curriculum and the ongoing improvement of the course are presented. The course started with its experiment environment using Microsoft Robotics Developer Studio, Visual Programming Language, and Lego Mind storms robots. The environment is extended to a Web-based programming environment and Intel architecture-based robots.

We present a 3D indoor positioning system with foot mounted low cost MEMS sensors. The sensors includes the accelerometers, gyroscopes, and barometer. The output of accelerometers and gyroscopes are used to calculate the zero velocity update (ZUPT) and the movement of one step. The barometer is used to detect the altitude changes. A Kalman filter based framework is used to fusion the outputs of the sensors and estimate the non-linear errors of the position and heading, which increased over time. A particle filter is used to further reduce the errors. The test result shows that the designed system perform well.

Cloud storage provides a virtually unlimited storage spaces for customers. Customers can combine their data storages from different types of cloud storage following their own requirements. End customers often stuck in choosing desirable configuration from different types of cloud storage. How to spend the minimum costs on using the highly efficient cloud storage? How to balance the relationship between the expenditures and performance? This paper proposes a cost-effective optimal configuration model using the repeated game model that can provide optimal configuration solutions to customers. The data mining techniques are used in provisioning on cloud storage. Classification helps users to find the related data and trend analysis assists users to mine the future trend on data storage. A simulate experiment is discussed and verify the correctness of the proposed model.

Service-oriented computing and Web services are becoming the dominating computing model as internet and cloud computing become pervasive. More and more services with the same functionality are becoming available, and QoS (Quality of Service) is the main factor to differentiate them. The overall QoS of a business process must meet user's requirement. Our study proposes a proxy-based framework to facilitate the dynamic integration of Web services into business process and fast detection of abnormalities. The major functions of our dynamic proxy-based framework include service collection, composition, selection and adaptation. Our study concerns both functionality and QoS characteristics of Web services to identify the optimal business process solutions.

The development of computing and communication systems has gone through a spiral cycle of centralization and decentralization schemas. The earliest telephone network used decentralized point-to-point connections. It moved to centralized switching system as the number of devices increased. The centralized computing and communication systems further moved into a decentralized paradigm, as devices expand and dependability of large systems becomes a dominating factor. The current cloud computing and communication systems appear to be a centralized system where computing and communication resources are not in the client computers but in an integrated infrastructure. Nevertheless, the implementation of the centralized infrastructure is equipped with decentralized and redundant resources, which makes the system more dependable as any internal failures can be tolerated internally. However, the terminal devices and their interfaces to the centralized infrastructure remain vulnerable to the single-point-of-failures. This paper focuses on terminal devices and their interfaces to the new generation of assurance network and presents the challenges of making the devices and the interfaces as dependable as the assurance network. The idea of achieving the goal is through a pool of Mobile Physical Services (MPS) that can connect to multiple networks and can be shared by neighboring users.

Service-oriented architecture and cloud computing have become the prevalent computing paradigm. In this paradigm, computing resources can be accessed like other utility services available in today's society. In the meantime, robotics applications are joining the trend. More and more robot applications are shifting from manufacture to non-manufacture and service industries. However, for the on-demand supply of the large-scale heterogeneous robots, It is still a problem have not yet been studied, including the fundamental management and efficiency issues in using of these resources. In this paper, we design a framework of "Robot Cloud Center" (RCC) following the general cloud computing paradigm to address the current limitations in capacity and versatility of robotic applications. In this framework, a robot can be provided as a service just like a public utility service so that everyone can access the powerful robotic services easily, efficiently, and cheaply. Based on a given scenario, a robot scheduling algorithm in RCC is proposed to take advantage of the heterogeneous robot resources to meet the end user's requirement with the minimum cost.

An autonomous decentralized system and a series of methods for reducing the detection time of path failures in the system are developed. Computing devices in the proposed system are organized into at least three groups based on their connectivity of system's graph model. Each computing device is assigned three identification values associated with their group memberships. The identification values are stored in a router connected to the communications network. Heartbeat packets are sent from the computing devices to the router periodically. If the router fails to receive a heartbeat packet from a computing device, a failed communication path from the router to the computing device is determined based on the three identification values.

As cloud services proliferate, it becomes difficult to facilitate service composition and testing in clouds. In traditional service-oriented computing, service composition and testing are carried out independently. This paper proposes a new approach to manage services on the cloud so that it can facilitate service composition and testing. The paper uses service implementation selection to facilitate service composition similar to Google's Guice and Spring tools, and apply the group testing technique to identify the oracle, and use the established oracle to perform continuous testing for new services or compositions. The paper extends the existing concept of template based service composition and focus on testing the same workflow of service composition. In addition, all these testing processes can be executed in parallel, and the paper illustrates how to apply service-level MapReduce technique to accelerate the testing process.

The current implementations of cloud environment do not have suitable mechanism through which services can be managed to make use of cloud resources. The services in these environments can passively serve users' request only. If a service receives more requests than it can handle in a certain time period, it is subject to malfunctioning. This paper proposes a new approach to service replications that allows a cloud to adjust its service instance deployments in response to existing and projected service request loads. This approach defines an optimal service replication strategy based on MapReduce, a processing model used extensively in GAE (Google App Engine) to solve huge data processing tasks. This service replication strategy is implemented by Service Level MapReduce (SLMR). To better support for SLMR, service replication technology is introduced, which include dynamic service replication and pre-deployed service replication. Furthermore, a passive SLMR approach that depends on the cloud management service (CMS) and a positive SLMR approach that does not need the support from CMS will be introduced.

This paper proposes a collaborative runtime monitoring framework to enhance the dependability of the software developed in traditional Web services architecture. The enabling mechanism is an active service broker (ASB) architecture which allows the service broker not only to serve as a passive service repository, but also to involve itself in service interactions and thus to play an active role in service execution and monitoring. The ASB communicates remotely with the distributed monitoring agents deployed at the service providerspsila sites. Sensors are instrumented in services at different levels, including the composition level, interface level, and component level. The model-based approach is discussed for automatic sensor generation and runtime enforcement based on service's process model and verification model. A prototype is implemented for the research of the user and science data center of the astronomic satellite system at Tsinghua University.

Testing is useful to establish trust between service providers and clients. To test the service-oriented applications, automated and specification-based test generation and test collaboration are necessary. The paper proposes an ontology-based approach for Web services (WS) testing. A test ontology model (TOM) is defined to specify the test concepts, relationships, and semantics from two aspects: test design (such as test data, test behavior, and test cases) and test execution (such as test plan, schedule and configuration). The TOM specification using OWL (Web ontology language) can serve as test contracts among test components. Based on the WS semantic specification in OWL-S, the paper discusses the techniques to generate the sub-domains for input partition testing. Data pools are established for each parameter of the specified service. Data partitions are derived by class property and relationship analysis. Completeness and consistency (C&C) checking can be performed on the data partitions and data values, both within the TOM and against the OWL-S, by ontology class computation and reasoning. A prototype tool is implemented to support OWL-S analysis, test ontology generation and C&C checking.

This paper proposes a new approach to teach the STEM (Science, Technology, Engineering, and Mathematics) knowledge informally via robotic games. In this approach, a robotic playground is built to provide a hands-on programming and playing experience with robots controlled by Service-Oriented Computing (SOC) software, which is based on a new approach that uses reusable services (components) with standard interfaces and platform-independent interoperability. Services in the repository are annotated with STEM knowledge to enforce the required contents. In this way, students can learn computing and STEM in an entertaining manner.

Web services (WS) and service-oriented architecture (SOA) present a set of unique testing challenges. As services are distributed, it is necessary to test them using a distributed architecture. Furthermore, as these services may keep on changing, testing needs to be adaptive. This paper proposes an adaptive testing framework which can continuously learn and improve the built-in test strategies. The framework allows different test cases to be selected based on the recent test results. The framework also has a windowing mechanism to evaluate and select test cases.

Service-oriented architecture (SOA) techniques are being increasingly used for developing critical applications, especially network-centric systems. While the SOA paradigm provides flexibility and agility to better respond to changing business requirements, the task of assessing the reliability of SOA-based systems is challenging, especially for composite services. However, deriving high confidence reliability estimates for mission- critical systems can require huge costs and time. This paper presents a reliability assessment and prediction model for SOA-based systems. The services are assumed to be realized with reuse and logical composition of components. The model uses AI reasoning techniques on dynamically collected failure data of each service and its components as one of the evidences together with results from random testing. Memory-Based Reasoning technique and Bayesian Belief Networks are used as reasoning tools to guide the prediction analysis. The least tested and "high usage " input subdomains are identified and necessary remedial actions are taken depending on the predicted results from the proposed model. The model is illustrated using a simulated case study based on a real-time dataset from the NASA software repository.

Governance by policies is an important feature in service-oriented architecture (SOA). This paper introduces a collaboration policy generation technique to govern dynamic collaboration in SOA systems. Dynamic collaboration allows two parties not knowing each other establish their collaboration protocol at runtime. Traditional SOA allows parties to collaborate but with a known collaboration protocol before execution. In dynamic collaboration, as collaboration protocols will be negotiated and determined at runtime, policies need to be generated at runtime to manage the interaction. This paper presents the concepts, architecture, and illustrative examples that demonstrate the dynamic collaboration policy generation technique

Due to the dynamic nature, such as runtime composition and evaluation, it is critical for an SOA system to consider its data provenance, which concerns security, reliability, and integrity of data as it is routed in the system. In a traditional software system, one can focus on the software itself to determine the security, reliability, and integrity; however, in an SOA system, one also needs to consider the origins and routes of data and their impact, i.e., data provenance. This paper first analyzes the unique natures and characteristics of data provenance in an SOA system. Then it proposes a new framework to classify data provenance and collect data in SOA systems. Finally, this paper uses an example to illustrate these concepts and techniques

Service-oriented architecture (SOA) is a system architecture in which a collection of loosely coupled services communicate with each other using standard interfaces and message-exchanging protocols. As an emerging technology in software development, the SOA presents a new paradigm, and it affects the entire software development cycle including analysis, specification, design, implementation, verification, validation, maintenance and evaluation. This paper proposes several testability evaluation criteria for SOA software, which serves as a reference for both service providers and application builders to evaluate the test support to SOA software. The proposed evaluation criteria are illustrated in a stock-trading case study

The architecture of SOA-based applications is different from traditional software architecture where the architecture is mainly static. The architecture of an SOA-based application is dynamic, i.e., the application may be composed at runtime using existing services. Thus SOA has provided a new direction for software architecture study, where the architecture is determined at runtime and architecture can be dynamically changed at runtime to meet the new software requirements. This paper proposes an architecture classification scheme for SOA-based applications. Using this classification, several well-known SOA-based applications are reviewed including the architectures proposed and adopted by major computer companies and standard organizations. The architecture classification provides a unified way to evaluate a variety of architectures for SOA-based applications.

Patching technologies are commonly applied to improve the dependability of software after release. This paper proposes an autonomous hot patching (AHP) framework to fully automate the reasoning for the causes of failures, and to patch the binary code of Web-based applications. AHP admits the hardness for rooting out all faults before product release, and autonomously patches problems of application programs. By directly operating on binary code, AHP is universal to virtually all applications. A promising application of AHP is to shortcut the remote maintenance center (RMC) and hence to reduce the turn around time for patches.

Web services and service-oriented architecture are emerging technologies that are changing the way we develop and use computer software. Due to the standardization of Web services related description languages and protocols, as well as the open platforms, for the same Web service specification, many different implementations can be offered from different service providers. This paper presents an adaptive group testing technique that can test large number Web services simultaneously and effectively. Based on a case study, experiments are performed to validate the correctness and effectiveness of the technique.

This paper presents an integrated development process for Web services. The key differences with the traditional software development are that this new process involves collaboration and cooperation among all parties involved: developers, brokers, and clients. The process defines a new way of developing trustworthy Web services based on the existing Internet infrastructure. The paper serves as a roadmap to research on Web services specification, discovery, ontology, composition, re-composition, testing, reliability assessing, ranking, and collaboration and cooperation among all parities involved in Web services research, development, and application.

Web services are emerging technologies that are changing the way we develop and use computer systems and software. Current Web services testing techniques are unable to assure the desired level of trustworthiness, which presents a barrier to WS applications in mission and business critical environments. This paper presents a framework that assures the trustworthiness of Web services. New assurance techniques are developed within the framework, including specification verification via completeness and consistency checking, specification refinement, distributed Web services development, test case generation, and automated Web services testing. Traditional test case generation methods only generate positive test cases that verify the functionality of software. The Swiss cheese test case generation method proposed in this paper is designed to perform both positive and negative testing that also reveal the vulnerability of Web services. This integrated development process is implemented in a case study. The experimental evaluation demonstrates the effectiveness of this approach. It also reveals that the Swiss cheese negative testing detects even more faults than positive testing and thus significantly reduces the vulnerability of Web services.

Web services form a new distributed computing paradigm. Collaborative verification and validation are important when Web services from different vendors are integrated together to carry out a coherent task. This paper presents a new approach to verify Web services by model checking the process model of OWL-S (Web ontology language for Web services) and to validate them by the test cases automatically generated in the model checking process. We extend the BLAST, a model checker that handles control flow model naturally, to handle the concurrency in OWL-S. We also propose enhancement in OWL-S and PDDL (Planning Domain Definition Language) to facilitate the automated test case generation. Experiments on realistic examples are provided to illustrate the process.

The reliability of distributed systems & computer networks in which computing nodes and/or communication links may fail with certain probabilities have been modeled by a probabilistic network. Computing the residual connectedness reliability (RCR) of probabilistic networks under the fault model with both node & link faults is very useful, but is an NP-hard problem. Up to now, there has been little research done under this fault model. There are neither accurate solutions nor heuristic algorithms for computing the RCR. In our recent research, we challenged the problem, and found efficient algorithms for the upper & lower bounds on RCR. We also demonstrated that the difference between our upper & lower bounds gradually tends to zero for large networks, and are very close to zero for small networks. These results were used in our dependable distributed system project to find a near-optimal subset of nodes to host the replicas of a critical task.

In the past few years we have developed an experimental distributed system that supports multi-task applications with different levels of criticality. Software implemented fault-tolerant protocols are used to support dependable computing. This paper first presents Markov models of a distributed system under the occurrence of faults, reconfiguration and repair. As a part of our overall project, these models are intended for solving our particular problems, like assessing the merits of redundant schemes, task allocation and reallocation policies, and fault handling used in our experimental system. However, these models are developed in a generic way. They can also be used in evaluating individual task's reliability, risk and availability under various redundant schemes in any homogeneous distributed system. Then, we extend our study in analysing the dependability of the heterogeneous system consisting of a number homogeneous distributed systems connected through gateways.

For the comparison-based self-diagnosis of multiprocessor systems, an extended model that considers both processor and comparator faults is presented. It is shown that in this model the system diagnosability is t>