Tag Archives: 2017

ThingsJS: Towards a Flexible and Self-Adaptable Middleware for Dynamic and Heterogeneous IoT Environments

Gascon-Samson, J., Rafiuzzaman M., Pattabiraman K. (2017) ThingsJS: Towards a Flexible and Self-Adaptable Middleware for Dynamic and Heterogeneous IoT Environments, Middleware for IoT (m4iot)@Middleware 2017, Las Vegas, USA
[Preprint] [Presentation Slides]

Abstract: The Internet of Things (IoT) has gained wide popularity both in academic and industrial contexts. Nowadays, such systems exhibit many important challenges across many dimensions. In this work, we propose ThingsJS, a rich Javascript-based middleware platform and runtime environment that abstracts the inherent complexity of such systems by providing a high-level framework for IoT system developers, built over Javascript. ThingsJS abstracts several large-scale distributed systems considerations, such as scheduling, monitoring and self-adaptation, by means of a rich constraint model, a multi-dimensional resource prediction approach and a SMT-based scheduler to properly schedule and manage the execution of high-level, large-scale distributed applications on heterogeneous physical IoT devices. ThingsJS also provides a rich inter-device communication framework built on top of the widely-used publish/subscribe/MQTT paradigm. Finally, ThingsJS also proposes a rich inter-device Javascript-based code migration framework to support the transparent migration of live IoT components between heterogeneous devices.

SmartJS: Dynamic and Self-Adaptable Runtime Middleware for Next-Generation IoT Systems (Poster)

Gascon-Samson, J., Rafiuzzaman M., Pattabiraman K. (2017) SmartJS: Dynamic and Self-Adaptable Runtime Middleware for Next-Generation IoT Systems (Poster), SPLASH 2017, Vancouver, Canada
[Preprint] [Poster]

Abstract: The Internet of Things (IoT) has gained wide popularity both in the academic and industrial contexts. However, IoT-based systems exhibit many important challenges across many dimensions. In this work, we propose SmartJS, a rich Javascript-based middleware platform and runtime environment that abstracts the complexity of the various IoT platforms by providing a high-level framework for IoT system developers. SmartJS abstracts large-scale distributed system considerations, such as scheduling, monitoring and self-adaptation, and proposes a rich inter-device Javascript-based code migration framework. Finally, it provides debugging and monitoring techniques to analyze performance and observe system-wide security properties.

ARTINALI: Dynamic Invariant Detection for Cyber-Physical System Security

Aliabadi, M., Kamath, A., Gascon-Samson, J., Pattabiraman, K. (2017) ARTINALI: Dynamic Invariant Detection for Cyber-Physical System Security, accepted / to be presented at ESEC/FSE 2017, Paderborn, Germany
> Acceptance ratio: 24% [Preprint] [Presentation Slides]

Abstract: Cyber-Physical Systems (CPSes) are being widely deployed in security critical scenarios such as smart homes and medical devices. Unfortunately, the connectedness of these systems and their relative lack of security measures makes them ripe targets for attacks. Specification-based Intrusion Detection Systems (IDS) have been shown to be effective for securing CPSs. Unfortunately, deriving invariants for capturing the specifications of CPS systems is a tedious and error-prone process. Therefore, it is important to dynamically monitor the CPS system to learn its common behaviors and formulate invariants for detecting security attacks. Existing techniques for invariant mining only incorporate data and events, but not time. However, time is central to most CPS systems, and hence incorporating time in addition to data and events, is essential for achieving low false positives and false negatives. This paper proposes ARTINALI, which mines dynamic system properties by incorporating time as a first-class property of the system. We build ARTINALI-based Intrusion Detection Systems (IDSes) for two CPSes, namely smart meters and smart medical devices, and measure their efficacy. We find that the ARTINALI-based IDSes significantly reduce the ratio of false positives and false negatives by 16 to 48% (average 30.75%) and 89 to 95% (average 93.4%) respectively over other dynamic invariant detection tools.

CacheDOCS: A Dynamic Key-Value Object Caching Service

Gascon-Samson, J., Coppinger, M., Jin, F., Kienzle, J., Kemme, B. (2017) CacheDOCS: A Dynamic Key-Value Object Caching Service, ICDCS-PED2017, Atlanta, USA
[Preprint] [Presentation Slides]

Abstract: Caching plays an important role in many domains, as it can lead to important performance improvements. A key-value based caching system typically stores the results of popular queries in efficient storage locations. While caching enjoys widespread usage in the context of dynamic web applications, most mainstream caching systems store static binary items, which makes them impractical for many real-world applications that would benefit from storing dynamic items. In this paper, we propose CacheDOCS, a dynamic key-value object caching service that allows for caching arbitrary objects. As part of our model, CacheDOCS provides an API that supports the execution of operations against cached objects, and allows for clients to seamlessly subscribe to keep their local copies in sync with cached remote objects. CacheDOCS supports multiple update dissemination strategies in order to optimize performance, and proposes a versioning mechanism to ensure consistency. We implemented a full version of CacheDOCS and we ran several performance-related experiments under three use-case scenarios.

MultiPub: Latency and Cost-Aware Global-Scale Cloud Publish/Subscribe

Gascon-Samson, J., Kemme, B., Kienzle, J. (2017) MultiPub: Latency and Cost-Aware Global-Scale Cloud Publish/Subscribe, ICDCS 2017, Atlanta, USA [Preprint] [Presentation Slides]

Abstract: Topic-based pub/sub is a widely used communication mechanism in distributed systems for targeted information dissemination between loosely coupled entities. To scale dynamically depending on the current communication demands, pub/services can be conveniently deployed in the cloud. To provide fast dissemination, the service can be distributed across multiple cloud regions. The architectural design and run-time deployment of such a middleware is tricky, though, as it can have a significant effect on communication latency and cloud-based cost. In this paper, we propose MultiPub, a flexible pub/sub middleware for latency-constrained, world-wide distributed applications that dynamically reconfigures the communication layer to ensure a predefined maximum latency for publication dissemination while minimizing cloud-based costs. This is achieved by routing publications either through a single or across multiple cloud regions. We demonstrate the effectiveness of MultiPub by presenting a set of experiments that report on the achieved communication latency and cost savings compared to traditional approaches, as well as a performance evaluation.