Being a popular runtime infrastructure in the era of Internet, middleware provides more and more services to support the development, deployment and management of distributed systems. At the same time, the reliability of middleware services has a significant impact on the overall reliability of the system. Different services have different impacts and different service fault-tolerance solutions have different costs and risks. Therefore, the identification of the services that greatly affect the whole system reliability is the major obstacle to achieving reliable middleware-based systems. In this paper, we present an analytical framework to automatically reason and quantify such impacts when deploying the target system. In this framework, faults are represented by exceptions in modern programming languages; service failures are simulated by software fault injection; reliability impacts are measured by scenarios. This framework is demonstrated on multiple JEE application servers, including JBoss, JonAS and PKUAS. The experiments on two JEE blueprint applications, namely JPS and ECperf, show the feasibility, the applicability and the usability of this framework.

Web browsing is always a key requirement of Internet users. Current mobile Web apps can contain computation-intensive JavaScript logics and thus affect browsing performance. Learning from our over-decade research and development experiences of the Internetware paradigm, we present the novel and generic i-Jacob approach to improving the performance of mobile Web browsing with effective JavaScript-code offloading. Our approach proposes a programming abstraction to make mobile Web situational and adaptive to contexts, by specifying the computation-intensive and “ offloadable ” code, and develops a platform-independent lightweight runtime spanning the mobile devices and the cloud. We demonstrate the efficiency of i-Jacob with some typical computation-intensive tasks over various combinations of hardware, operating systems, browsers, and network connections. The improvements can reach up to 49× speed-up in response time and 90% saving in energy.

Imperfect Web resource loading prevents mobile Web browsing from providing satisfactory user experience. In this article, we design and implement the SWAROVsky system to address three main issues of current inefficient Web resource loading: (1) on-demand and thus slow loading of sub-resources of webpages; (2) duplicated loading of resources with different URLs but the same content; and (3) redundant loading of the same resource due to improper cache configurations. SWAROVsky employs a dual-proxy architecture that comprises a remote cloud-side proxy and a local proxy on mobile devices. The remote proxy proactively loads webpages from their original Web servers and maintains a resource loading graph for every single webpage. Based on the graph, the remote proxy is capable of deciding which resources are “really” needed for the webpage and their loading orders, and thus can synchronize these needed resources with the local proxy of a client efficiently and timely. The local proxy also runs an intelligent and light-weight algorithm to identify resources with different URLs but the same content, and thus can avoid duplicated downloading of the same content via network. Our system can be used with existing Web browsers and Web servers, and does not break the normal semantics of a webpage. Evaluations with 50 websites show that on average our system can reduce the page load time by 43.1 percent and the network data transmission by 57.6 percent, while imposing marginal system overhead.

Runtime software architectures (RSA) are architecture-level, dynamic representations of running software systems, which help monitor and adapt the systems at a high abstraction level. The key issue to support RSA is to maintain the causal connection between the architecture and the system, ensuring that the architecture represents the current system, and the modifications on the architecture cause proper system changes. The main challenge here is the abstraction gap between the architecture and the system. In this paper, we investigate the synchronization mechanism between architecture configurations and system states for maintaining the causal connections. We identify four required properties for such synchronization, and provide a generic solution satisfying these properties. Specifically, we utilize bidirectional transformation to bridge the abstraction gap between architecture and system, and design an algorithm based on it, which addresses issues such as conflicts between architecture and system changes, and exceptions of system manipulations. We provide a generative tool-set that helps developers implement this approach on a wide class of systems. We have successfully applied our approach on JOnAS JEE system to support it with C2-styled runtime software architecture, as well as some other cases between practical systems and typical architecture models.

Service computing promotes a large number of web-delivered services, including web services, APIs and data feeds. Composing data, functionalities and even UI from these web-delivered services into a single web application, usually called service mashup, becomes a popular web development paradigm. The web-delivered services can be modeled as mashup components, while the development of mashup actually yields a set of inter-connected mashup components. The growing popularity of mashup components enriches functionality and user experiences, while the possible connections among components are complex and difficult to mashup developers, who might be non-professional programmers or even end-users, as actions over one component may have potential impacts on another. This paper proposes a novel approach for recommending developers in terms of navigation and completion of mashup components with a large-scale components repository. From data-driven perspective, we model the relationships between mashup components by a generic layered-graph model. Developers are allowed to select some initial components as starting point, while a graph-based algorithm recommends how to navigate to potentially relevant mashup components and complete the relevant mashup application. We experimentally demonstrate the efficiency and effectiveness of our approach for rapid mashup construction.