Secure Publish-Process-Subscribe System for Dispersed Computing

Publish-subscribe protocols enable real-time multi-point-to-multi-point communications for many dispersed computing systems like Internet of Things (IoT) applications. Recent interest has focused on adding processing to such publish-subscribe protocols to enable computation over real-time streams such that the protocols can provide functionalities such as sensor fusion, compression, and other statistical analysis on raw sensor data. However, unlike pure publish-subscribe protocols, which can be easily deployed with end-to-end transport layer encryption, it is challenging to ensure security in such publish-process-subscribe protocols when the processing is carried out on an untrusted third party. In this work, we present XYZ, a secure publish-process-subscribe system that can preserve the confidentiality of computations and support multi-publisher-multi-subscriber settings. Within XYZ, we design two distinct schemes: the first using Yao\u27s garbled circuits (the GC-Based Scheme) and the second using homomorphic encryption with proxy re-encryption (the Proxy-HE Scheme). We build implementations of the two schemes as an integrated publish-process-subscribe system. We evaluate our system on several functions and also demonstrate real-world applications. The evaluation shows that the GC-Based Scheme can finish most tasks two orders of magnitude times faster than the Proxy-HE Scheme while Proxy-HE can still securely complete tasks within an acceptable time for most functions but with a different security assumption and a simpler system structure

DEBS Grand Challenge: Glasgow Automata Illustrated

The challenge is solved using Glasgow automata, concise complex event processing engines executable in the context of a topic-based publish/subscribe cache of event streams and relations. The imperative programming style of the Glasgow Automaton Programming Language (GAPL) enables multiple, efficient realisations of the two challenge queries

Publishing LO(D)D: Linked Open (Dynamic) Data for Smart Sensing and Measuring Environments

The paper proposes a distributed framework that provides a systematic way to publish environment data which is being updated continuously; such updates might be issued at specific time intervals or bound to some environment- specific event. The framework targets smart environments having networks of devices and sensors which are interacting with each other and with their respective environments to gather and generate data and willing to publish this data. This paper addresses the issues of supporting the data publishers to maintain up-to-date and machine understandable representations, separation of views (static or dynamic data) and delivering up-to-date information to data consumers in real time, helping data consumers to keep track of changes triggered from diverse environments and keeping track of evolution of the smart environment. The paper also describes a prototype implementation of the proposed architecture. A preliminary use case implementation over a real energy metering infrastructure is also provided in the paper to prove the feasibility of the architectur

Architecture for Analysis of Streaming Data

While several attempts have been made to construct a scalable and flexible architecture for analysis of streaming data, no general model to tackle this task exists. Thus, our goal is to build a scalable and maintainable architecture for performing analytics on streaming data. To reach this goal, we introduce a 7-layered architecture consisting of microservices and publish-subscribe software. Our study shows that this architecture yields a good balance between scalability and maintainability due to high cohesion and low coupling of the solution, as well as asynchronous communication between the layers. This architecture can help practitioners to improve their analytic solutions. It is also of interest to academics, as it is a building block for a general architecture for processing streaming data

The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity

Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the management of natural disasters or in community empowerment. However, current social sensing services depend on Internet connectivity since the services are deployed on central Cloud platforms. In many circumstances, Internet connectivity is constrained, for instance when a natural disaster causes Internet outages or when people do not have Internet access due to economical reasons. In this paper, we propose the emerging Fog Computing infrastructure to become a key-enabler of social sensing services in situations of constrained Internet connectivity. To this end, we develop a generic architecture and API of Fog-enabled social sensing services. We exemplify the usage of the proposed social sensing architecture on a number of concrete use cases from two different scenarios.Comment: Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity. In Proceedings of The 2nd International Workshop on Social Sensing, Pittsburgh, PA, USA, April 21 2017 (SocialSens'17), 6 page

Chemistry by Mobile Phone (or how to justify more time at the bar)

By combining automatic environment monitoring with Java smartphones a system has been produced for the real-time monitoring of experiments whilst away from the lab. Changes in the laboratory environment are encapsulated as simple XML messages, which are published using an MQTT compliant broker. Clients subscribe to the MQTT stream, and produce a user display. An MQTT client written for the Java MIDP platform, can be run on a smartphone with a GPRS Internet connection, freeing us from the constraints of the lab. We present an overview of the technologies used, and how these are helping chemists make the best use of their time