Software portability

About: Software portability is a research topic. Over the lifetime, 8987 publications have been published within this topic receiving 164922 citations. The topic is also known as: portability.

A lightweight and extensible Complex Event Processing system for sense and respond applications

Abstract: Complex Event Processing (CEP) is considered as a promising technology for enabling the evolution of service-oriented enterprise systems towards operational aware systems. CEP effectively supports the implementation of ''sense and respond'' behaviours, as it enables to extract meaningful events from raw data streams originated by sensing infrastructures, for enterprise processes and applications consumption. This paper proposes a novel CEP engine conceived with ease of use, extensibility, portability, and scalability requirements in mind. More specifically, we propose a Lightweight Stage-based Event Processor (LiSEP) based on a layered architectural design. Thanks to the adoption of Staged Event-Driven Architecture principles, core event processing logic is decoupled from low-level thread management issues. This results in an easy-to-understand and extensible implementation while testing results show performance scalability. We report on the carrying out of a case study on dangerous goods monitoring in maritime transport. The objective of the case study is to develop a Proof of Concept application leveraging on LiSEP capabilities in sensor and RFID events processing for monitoring and alerting purposes.

Lightweight Application-Level Task Migration for Mobile Cloud Computing

Abstract: Mobile cloud computing allows mobile applications to use the enormous resources in the clouds. In order to seamlessly utilize the resources, it is common to migrate computation among mobile nodes and cloud nodes. Therefore, a highly portable and transparent migration approach is needed. In terms of portability, application-level migration with code instrumentation is the most portable approach. However, in the existing literature, this approach imposes significant runtime overhead, even when no migration takes place. Most of these works are for mobile agents, and migrations are to be invoked by the programs. Migration points are also restricted to certain locations where migration status is being polled. In this paper, we propose a Java byte code transformation technique for realizing task migration without imposing significant overhead on normal execution. Asynchronous migration technique is used to allow migrations to take place virtually anywhere in the user codes, and the proposed Twin Method Hierarchy minimizes the overhead resulting from state-restoration codes in normal execution. We have implemented our approach in our middleware. The results show that our approach can allow lightweight computation migration at application level, achieve considerable speedups and utilize the cloud resources from mobile devices.

Semantic Representation of Cloud Patterns and Services with Automated Reasoning to Support Cloud Application Portability

Abstract: During the past years the Cloud Computing offer has exponentially grown, with new Cloud providers, platforms and services being introduced in the IT market. The extreme variety of services, often providing non uniform and incompatible interfaces, makes it hard for customers to decide how to develop, or even worse to migrate, their own application into the Cloud. This situation can only get worse when customers want to exploit services from different providers, because of the portability and interoperability issues that often arise. In this paper we propose a uniform, integrated, machine-readable, semantic representation of cloud services, patterns, appliances and their compositions. Our approach aims at supporting the development of new applications for the Cloud environment, using semantic models and automatic reasoning to enhance potability and interoperability when multiple platforms are involved. In particular, the proposed reasoning procedure allows to: perform automatic discovery of Cloud services and Appliances; map between agnostic and vendor dependent Cloud Patterns and Services; automatically enrich the semantic knowledge base.

APOLLO: automatic detection and diagnosis of performance regressions in database systems

Abstract: The practical art of constructing database management systems (DBMSs) involves a morass of trade-offs among query execution speed, query optimization speed, standards compliance, feature parity, modularity, portability, and other goals. It is no surprise that DBMSs, like all complex software systems, contain bugs that can adversely affect their performance. The performance of DBMSs is an important metric as it determines how quickly an application can take in new information and use it to make new decisions.Both developers and users face challenges while dealing with performance regression bugs. First, developers usually find it challenging to manually design test cases to uncover performance regressions since DBMS components tend to have complex interactions. Second, users encountering performance regressions are often unable to report them, as the regression-triggering queries could be complex and database-dependent. Third, developers have to expend a lot of effort on localizing the root cause of the reported bugs, due to the system complexity and software development complexity.Given these challenges, this paper presents the design of Apollo, a toolchain for automatically detecting, reporting, and diagnosing performance regressions in DBMSs. We demonstrate that Apollo automates the generation of regression-triggering queries, simplifies the bug reporting process for users, and enables developers to quickly pinpoint the root cause of performance regressions. By automating the detection and diagnosis of performance regressions, Apollo reduces the labor cost of developing efficient DBMSs.