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1. A Programming Model for Reliable and Efficient Edge-Based Execution under Resource Variability

   https://doi.org/10.1109/EDGE.2019.00026  

   Song, Zheng ; Tilevich, Eli ( July 2019 , 2019 IEEE International Conference on Edge Computing (EDGE))

   Edge computing applications use the computational, sensor, and networking resources of nearby mobile and stationary computing devices. Because dissimilar devices can provide these resources, one cannot predict which exact combinations of resources will be available at runtime. The resulting variability hinders the development of edge computing applications. To address this problem, we present a new programming model that employs a domain-specific language (DSL), through which the developer declaratively specifies a collection of microservices and how they invoke each other. Given a concise declarative service suite specification, the DSL compiler automatically generates an execution plan, carried out by our distributed runtime. The resulting programming model is both reliable and efficient. The reliability is achieved by enabling the developer to provide equivalent microservices as switch-over recovery strategies. The efficiency is achieved by the DSL compiler orchestrating the speculatively parallel execution of certain equivalent microservices. Our evaluation demonstrates the reliability, efficiency, and expressiveness of the programming model, which can help developers who need to cope with variable resources at the edge. 

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2. 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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3. Equivalence-Enhanced Microservice Workflow Orchestration to Efficiently Increase Reliability

   https://doi.org/10.1109/ICWS.2019.00076  

   Song, Zheng ; Tilevich, Eli ( July 2019 , 2019 IEEE International Conference on Web Services (ICWS))

   The applicability of the microservice architecture has extended beyond traditional web services, making steady inroads into the domains of IoT and edge computing. Due to dissimilar contexts in different execution environments and inherent mobility, edge and IoT applications suffer from low execution reliability. Replication, traditionally used to increase service reliability and scalability, is inapplicable in these resourcescarce environments. Alternately, programmers can orchestrate the parallel or sequential execution of equivalent microservices— microservices that provide the same functionality by different means. Unfortunately, the resulting orchestrations rely on parallelization, synchronization, and failure handing, all tedious and error-prone to implement. Although automated orchestration shifts the burden of generating workflows from the programmer to the compiler, existing programming models lack both syntactic and semantic support for equivalence. In this paper, we enhance compiler-generated execution orchestration with equivalence to efficiently increase reliability. We introduce a dataflow-based domain-specific language, whose dataflow specifications include the implicit declarations of equivalent microservices and their execution patterns. To automatically generate reliable workflows and execute them efficiently, we introduce new equivalence workflow constructs. Our evaluation results indicate that our solution can effectively and efficiently increase the reliability of microservice-based applications. 

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4. E3: Energy-Efficient Microservices on SmartNIC-Accelerated Servers

   Liu, Ming ; Peter, Simon ; Krishnamurthy, Arvind ; Phothilimthana, Phitchaya M ( July 2019 , 2019 USENIX Annual Technical Conference (USENIX ATC 19))

   We investigate the use of SmartNIC-accelerated servers to execute microservice-based applications in the data center. By offloading suitable microservices to the SmartNIC’s low-power processor, we can improve server energy-efficiency without latency loss. However, as a heterogeneous computing substrate in the data path of the host, SmartNICs bring several challenges to a microservice platform: network traffic routing and load balancing, microservice placement on heterogeneous hardware, and contention on shared SmartNIC resources. We present E3, a microservice execution platform for SmartNIC-accelerated servers. E3 follows the design philosophies of the Azure Service Fabric microservice platform and extends key system components to a SmartNIC to address the above-mentioned challenges. E3 employs three key techniques: ECMP-based load balancing via SmartNICs to the host, network topology-aware microservice placement, and a data-plane orchestrator that can detect SmartNIC overload. Our E3 prototype using Cavium LiquidIO SmartNICs shows that SmartNIC offload can improve cluster energy-efficiency up to 3× and cost efficiency up to 1.9× at up to 4% latency cost for common microservices, including real-time analytics, an IoT hub, and virtual network functions. 

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5. 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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