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1. Intent to share: enhancing Android inter-component communication for distributed devices

   https://doi.org/10.1145/3197231.3197245  

   Cruz, Breno Dantas; Tilevich, Eli (January 2018, Proceedings of the 5th International Conference on Mobile Software Engineering and Systems)

   Data-intensive applications in diverse domains, including video streaming, gaming, and health monitoring, increasingly require that mobile devices directly share data with each other. However, developing distributed data sharing functionality introduces low-level, brittle, and hard-to-maintain code into the mobile codebase. To reconcile the goals of programming convenience and performance efficiency, we present a novel middleware framework that enhances the Android platform's component model to support seamless and efficient inter-device data sharing. Our framework provides a familiar programming interface that extends the ubiquitous Android Inter-Component Communication (ICC), thus lowering the learning curve. Unlike middleware platforms based on the RPC paradigm, our programming abstractions require that mobile application developers think through and express explicitly data transmission patterns, thus treating latency as a first-class design concern. Our performance evaluation shows that using our framework incurs little performance overhead, comparable to that of custom-built implementations. By providing reusable programming abstractions that preserve component encapsulation, our framework enables Android devices to efficiently share data at the component level, providing powerful building blocks for the development of emerging distributed mobile applications. 

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2. A Case Study of API Design for Interoperability and Security of the Internet of Things

   Kim, Dongha; Lee, Chanhee; Kim, Hokeun (November 2024, EAI)

   Heterogeneous distributed systems, including the Internet of Things (IoT) or distributed cyber-physical systems (CPS), often su↵er a lack of interoperability and security, which hinders the wider deployment of such systems. Specifically, the di↵erent levels of security requirements and the heterogeneity in terms of communication models, for instance, point-to-point vs. publish-subscribe, are the example challenges of IoT and distributed CPS consisting of heterogeneous devices and applications. In this paper, we propose a working application programming interface (API) and runtime to enhance interoperability and security while addressing the challenges that stem from the heterogeneity in the IoT and distributed CPS. In our case study, we design and implement our application programming interface (API) design approach using opensource software, and with our working implementation, we evaluate the e↵ectiveness of our proposed approach. Our experimental results suggest that our approach can achieve both interoperability and security in the IoT and distributed CPS with a reasonably small overhead and better-managed software. 

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3. Automated Code-Smell Detection in Microservices Through Static Analysis: A Case Study

   https://doi.org/10.3390/app10217800  

   Walker, Andrew; Das, Dipta; Cerny, Tomas (November 2020, Applied Sciences)

   null (Ed.)

   Microservice Architecture (MSA) is becoming the predominant direction of new cloud-based applications. There are many advantages to using microservices, but also downsides to using a more complex architecture than a typical monolithic enterprise application. Beyond the normal poor coding practices and code smells of a typical application, microservice-specific code smells are difficult to discover within a distributed application setup. There are many static code analysis tools for monolithic applications, but tools to offer code-smell detection for microservice-based applications are lacking. This paper proposes a new approach to detect code smells in distributed applications based on microservices. We develop an MSANose tool to detect up to eleven different microservice specific code smells and share it as open-source. We demonstrate our tool through a case study on two robust benchmark microservice applications and verify its accuracy. Our results show that it is possible to detect code smells within microservice applications using bytecode and/or source code analysis throughout the development process or even before its deployment to production. 

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4. STOIC: Serverless TeleOperable Hybrid Cloud for Machine Learning Applications on Edge Device

   Zhang, M; Krintz, C; Wolski, R. (March 2020, International Workshop on Smart Edge Computing and Networking)

   Serverless computing is a promising new event- driven programming model that was designed by cloud vendors to expedite the development and deployment of scalable web services on cloud computing systems. Using the model, developers write applications that consist of simple, independent, stateless functions that the cloud invokes on-demand (i.e. elastically), in response to system-wide events (data arrival, messages, web requests, etc.). In this work, we present STOIC (Serverless TeleOperable HybrId Cloud), an application scheduling and deployment system that extends the serverless model in two ways. First, it uses the model in a distributed setting and schedules application functions across multiple cloud systems. Second, STOIC sup- ports serverless function execution using hardware acceleration (e.g. GPU resources) when available from the underlying cloud system. We overview the design and implementation of STOIC and empirically evaluate it using real-world machine learning applications and multi-tier (e.g. edge-cloud) deployments. We find that STOIC’s combined use of edge and cloud resources is able to outperform using either cloud in isolation for the applications and datasets that we consider. 

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5. Programming support for sharing resources across heterogeneous mobile devices

   https://doi.org/10.1145/3197231.3197250  

   Song, Zheng; Chadha, Sanchit; Byalik, Antuan; Tilevich, Eli (January 2018, Proceedings of the 5th International Conference on Mobile Software Engineering and Systems)

   Modern mobile users commonly use multiple heterogeneous mobile devices, including smartphones, tablets, and wearables. Enabling these devices to seamlessly share their computational, network, and sensing resources has great potential benefit. Sharing resources across collocated mobile devices creates mobile device clouds (MDCs), commonly used to optimize application performance and to enable novel applications. However, enabling heterogeneous mobile devices to share their resources presents a number of difficulties, including the need to coordinate and steer the execution of devices with dissimilar network interfaces, application programming models, and system architectures. In this paper, we describe a solution that systematically empowers heterogeneous mobile devices to seamlessly, reliably, and efficiently share their resources. We present a programming model and runtime support for heterogeneous mobile device-to-device resource sharing. Our solution comprises a declarative domain-specific language for device-to-device cooperation, supported by a powerful runtime infrastructure. we evaluated our solution by conducting a controlled user study and running performance/energy efficiency benchmarks. The evaluation results indicate that our solution can become a practical tool for enhancing the capabilities of modern mobile applications by leveraging the resources of nearby mobile devices. 

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