A publish/subscribe middleware for dependable and real-time resource monitoring in the cloud

Abstract

Providing scalable and QoS-enabled (i.e., real-time and reliable) monitoring of resources (both virtual and physical) in the cloud is essential to supporting application QoS properties in the cloud as well as identifying security threats. Existing approaches to resource monitoring in the cloud are based on web interfaces, such as RESTful APIs and SOAP, which cannot provide real-time information efficiently and scalably because of a lack of support for fine-grained and differentiated monitoring capabilities. Moreover, their implementation overhead results in a distinct loss in performance, incurs latency jitter, and degrades reliable delivery of time-sensitive information. To address these challenges this paper presents a novel lighter weight and scalable resource monitoring and dissemination solution based on the publish/subscribe (pub/sub) paradigm. Our solution called SQRT-C leverages the OMG Data Distribution Service (DDS) real-time pub/sub middleware, and uses effective software engineering principles to make it usable with multiple cloud platforms. Preliminary empirical results comparing SQRT-C with contemporary web-based resource usage monitoring services reveals that SQRT-C is significantly better than the conventional approaches in terms of latency, jitter and scalability.

The Internet of Simulation: Enabling agile model based systems engineering for cyber-physical systems

“…Additionally, DDS has previously been applied to distributed co-simulation and has an overlap with HLA [7]. The one drawback of DDS is the limited support for cloud applications [21].…”

Supporting SIP-based end-to-end Data Distribution Service QoS in WANs

“…Management Enterprise DRE systems increasingly use DDS middleware to disseminate data over large-scale networks [2,12]. To ensure end-to-end interoperability without requiring proprietary bridges [38], the OMG defined a DDS Interoperability (DDSI) protocol [43] that enables seamless QoS-enabled communication between DDS implementations from different suppliers.…”

“…The purpose of this configuration is to perform topic transformation from DDS domain "A" to DDS domain "B" (as shown in Figure 12), thereby transforming topics published on domain "A" to another topics having the same data content on domain "B." Figure 12 also shows how the Topic-Bridge Analysis Figure 13a shows the traffic flow sent by the publisher in participant "A" and received by the remote subscribers (participant "B" and "C"): traffic (1) describes the flow sent by publisher at 20Kbps (distribution of a single topic instance (square)) and traffic (2) shows topic data received by the DDS-RS at 40Kbps, which corresponds to a subscriber registering for two topic instances (circle and triangle). Figure 13b shows the traffic sent and received by the Topic-Bridge on participant "B".…”

“…In this sce- Figure 13a. Traffic (2) shows topic data published by participant "A" to the bridge. Traffic (3) shows topic data retransmitted by the bridge and received by participant "C" at 80Kbps, which corresponds to the distribution of two and four topics instances.…”

“…In particular, the OMG Data Distribution Service (DDS) [44] defines a standard architecture for real-time, data-centric publish/subscribe (pub/sub) middleware capabilities that are used in many DRE systems to provide efficient and predictable dissemination of time-critical data [36]. Due to its flexible programming abstractions and rich support for QoS policies/mechanisms capable of controlling the end-to-end properties of data distribution [27], DDS is a popular technology for building enterprise DRE systems [2].…”