The Data Distribution Service – The Communication Middleware Fabric for Scalable and Extensible Systems-of-Systems
Angelo Corsaro, Chris Douglas · InTech eBooks · 2012
IntroductionDuring the past several decades techniques and technologies have emerged to design and implement distributed systems effectively.A remaining challenge, however, is devising techniques and technologies that will help design and implement SoSs.SoSs present some unique challenges when compared to traditional systems since their scale, heterogeneity, extensibility, and evolvability requirements are unprecedented compared to traditional systems Northrop et al. (2006).For instance, in Systems-of-Systems (SoS), such as the one depicted in Figure 1, the computational and communication resources involved are highly heterogeneous, which yields situations where high-end systems connected to high-speed networks must cooperate with embedded devices or resource-constrained edge systems connected over bandwidth-limited links.Moreover, in SoS it is common to find multiple administrative entities that manage the different parts, so upgrading the system must be incremental and never require a full redeployment of the whole SoS.In addition, SoS are often characterized by high degrees of dynamism and thus must enable subsystems and devices dynamically joining and leaving the federation of system elements.The Object Management Group (OMG) Data Distribution Service for Real-Time Systems (DDS) Group ( 2004) is a standard for data-centric Publish/Subscribe (P/S) introduced in 2004 to address the challenges faced by important mission-critical systems and systems-of-systems.As described in the reminder of this Chapter, DDS addresses all the key challenges posed by SoS outlined above.As a result, it provides the most natural choice as the communication middleware fabrice for developing scalable and extensible SoS.Since its inception DDS has experienced a swift adoption in several different domains.The reason for this successful adoption stems largely from its following characteristics:1. DDS has been designed to scale up and down, allowing deployments that range from resource-constrained embedded systems to large-scale systems-of-systems.2. DDS is equipped with a powerful set of QoS policies that allow applications fine-grain control over key data distribution properties, such as data availability, timeliness, resource consumption, and usage.