Reliable and timely event notification for publish/subscribe services over the internet

The publish/subscribe paradigm is gaining attention for the development of several applications in wide area networks (WANs) due to its intrinsic time, space, and synchronization decoupling properties that meet the scalability and asynchrony requirements of those applications. However, while the communication in a WAN may be affected by the unpredictable behavior of the network, with messages that can be dropped or delayed, existing publish/subscribe solutions pay just a little attention to addressing these issues. On the contrary, applications such as business intelligence, critical infrastructures, and financial services require delivery guarantees with strict temporal deadlines. In this paper, we propose a framework that enforces both reliability and timeliness for publish/subscribe services over WAN. Specifically, we combine two different approaches: gossiping, to retrieve missing packets in case of incomplete information, and network coding, to reduce the number of retransmissions and, consequently, the latency. We provide an analytical model that describes the information recovery capabilities of our algorithm and a simulation-based study, taking into account a real workload from the Air Traffic Control domain, which evidences how the proposed solution is able to ensure reliable event notification over a WAN within a reasonable bounded time window. © 2013 IEEE

Dimension-Based Subscription Pruning for Publish/Subscribe Systems

Subscription pruning has been proven as valuable routing optimization for Boolean subscriptions in publish/ subscribe systems. It aims at optimizing subscriptions independently of each other and is thus applicable for all kinds of subscriptions regardless of their individual and collective structures. The original subscription pruning approach tries to optimize the event routing process based on the expected increase in network load. However, a closer look at pruning-based routing reveals its further applicability to optimizations in respect to other dimensions. In this paper, we introduce and investigate subscription pruning based on three dimensions of optimization: network load, memory usage, and system throughput. We present the algorithms to perform prunings based on these dimensions and discuss the results of a series of practical experiments. Our analysis reveals the advantages and disadvantages of the different dimensions of optimization and allows conclusions about the suitability of dimension-based pruning for different application requirements

Confidentiality-Preserving Publish/Subscribe: A Survey

Publish/subscribe (pub/sub) is an attractive communication paradigm for large-scale distributed applications running across multiple administrative domains. Pub/sub allows event-based information dissemination based on constraints on the nature of the data rather than on pre-established communication channels. It is a natural fit for deployment in untrusted environments such as public clouds linking applications across multiple sites. However, pub/sub in untrusted environments lead to major confidentiality concerns stemming from the content-centric nature of the communications. This survey classifies and analyzes different approaches to confidentiality preservation for pub/sub, from applications of trust and access control models to novel encryption techniques. It provides an overview of the current challenges posed by confidentiality concerns and points to future research directions in this promising field

Reliable Messaging to Millions of Users with MigratoryData

Web-based notification services are used by a large range of businesses to selectively distribute live updates to customers, following the publish/subscribe (pub/sub) model. Typical deployments can involve millions of subscribers expecting ordering and delivery guarantees together with low latencies. Notification services must be vertically and horizontally scalable, and adopt replication to provide a reliable service. We report our experience building and operating MigratoryData, a highly-scalable notification service. We discuss the typical requirements of MigratoryData customers, and describe the architecture and design of the service, focusing on scalability and fault tolerance. Our evaluation demonstrates the ability of MigratoryData to handle millions of concurrent connections and support a reliable notification service despite server failures and network disconnections

Arbitrary boolean advertisements: the final step in supporting the boolean publish/subscribe model

Publish/subscribe systems allow for an efficient filtering of incoming information. This filtering is based on the specifications of subscriber interests, which are registered with the system as subscriptions. Publishers conversely specify advertisements, describing the messages they will send later on. What is missing so far is the support of arbitrary Boolean advertisements in publish/subscribe systems. Introducing the opportunity to specify these richer Boolean advertisements increases the accuracy of publishers to state their future messages compared to currently supported conjunctive advertisements. Thus, the amount of subscriptions forwarded in the network is reduced. Additionally, the system can more time efficiently decide whether a subscription needs to be forwarded and more space efficiently store and index advertisements. In this paper, we introduce a publish/subscribe system that supports arbitrary Boolean advertisements and, symmetrically, arbitrary Boolean subscriptions. We show the advantages of supporting arbitrary Boolean advertisements and present an algorithm to calculate the practically required overlapping relationship among subscriptions and advertisements. Additionally, we develop the first optimization approach for arbitrary Boolean advertisements, advertisement pruning. Advertisement pruning is tailored to optimize advertisements, which is a strong contrast to current optimizations for conjunctive advertisements. These recent proposals mainly apply subscription-based optimization ideas, which is leading to the same disadvantages. In the second part of this paper, our evaluation of practical experiments, we analyze the efficiency properties of our approach to determine the overlapping relationship. We also compare conjunctive solutions for the overlapping problem to our calculation algorithm to show its benefits. Finally, we present a detailed evaluation of the optimization potential of advertisement pruning. This includes the analysis of the effects of additionally optimizing subscriptions on the advertisement pruning optimization