Abstract
Data Distribution Service (DDS) has emerged as a potential solution for data communication challenges in smart grids. DDS is designed to support quality communication for large scale real-time systems through a wide range of QoS policies. However, a smart grid involves various types of communication applications running on different computing environments. Some environments have limited computing resources such as small memory and low performance, which makes it difficult to accommodate DDS. In this paper, we present a feature-based approach for tailoring DDS to configure lightweight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment. This allows DDS to serve as a uniform communication middleware across the smart grid, which is critical for interoperability. We analyze DDS in terms of features and design them using Unified Modeling Language (UML) and Object Constraint Language (OCL) based on inheritance and overriding. We define a formal notion of feature composition to build DDS configurations. We implemented the approach in OpenDDS and demonstrate its application to different application environments. We also experimented the approach for the efficiency of configured DDS in terms of resource utilization. The results show that configured DDS is viable for efficient and quality data communication for applications that run on an environment with limited computing capability.
Highlights
Smart grids have emerged as the generation of power grids for improved efficiency, reliability, and flexibility of power production and consumption
We load the four configurations into Raspberry Pi equipped with 0.5 GB memory and 0.7 GHz CPU and Raspberry Pi2 equipped with 1 GB memory and 0.9 GHz CPU
We have presented an approach for configuring light-weight Data Distribution Service (DDS) by selecting only the necessary features for the application, so that DDS can be adopted by large applications running on powerful devices, and small application running on resource-constrained devices
Summary
Smart grids have emerged as the generation of power grids for improved efficiency, reliability, and flexibility of power production and consumption. DDS is capable of supporting large scale real-time systems with a wide range of quality of service (QoS) policies It supports TCP, UDP, and shared memory over different network configurations (e.g., LAN, WAN) via various wired/wireless communication technologies (e.g., Ethernet, 4G, Wi-Fi). We present an approach for tailoring DDS for light-weight DDS per the computing capability of application environments so that DDS can serve as a uniform communication platform across a smart grid, which facilitates interoperability. This allows one to configure light-weight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment In this way, DDS can be adopted by various applications across the smart grid, serving as a uniform communication platform.
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