Vol. 71, n° 3-4, March-April 2016
Content available on Springerlink

Guest editors

Gordon Blair, Lancaster University, Lancaster, UK
Douglas Schmidt, Vanderbilt University, Nashville, TN, USA
Chantal Taconet, Télécom SudParis, Évry, France

 

Editorial introduction

Middleware for Internet distribution in the context of cloud computing and the Internet of Things

Gordon Blair¹, Douglas Schmidt², Chantal Taconet³

(1) Lancaster University, Lancaster, UK
(2) Vanderbilt University, Nashville, TN, USA
(3) Télécom SudParis, Évry, France

 

A simulation as a service cloud middleware

Shashank Shekhar, Hamzah Abdel-Aziz, Michael Walker, Faruk Caglar, Aniruddha Gokhale, Xenofon Koutsoukos

Vanderbilt University, Nashville, TN, USA

Abstract Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.

Keywords Cloud computing – Middleware – Linux container – Simulation-as-a-Service

 

NERD—middleware for IoT human machine interfaces

Thaddeus Czauski¹, Jules White², Yu Sun³, Hamilton Turner¹, Sean Eade⁴

(1) Virginia Tech, Blacksburg, VA, USA
(2) Vanderbilt University, Nashville, TN, USA
(3) Polytechnic University, Pomona, CA, USA
(4) Siemens, Princeton, NJ, USA

Abstract Industrial control systems (ICS), such as smart grid systems, are frequently composed of hundreds of devices distributed over a large geographic area. While mobile applications have been used with good success in managing ICSs, traditional methods of distributing applications (e.g., app stores) are not well suited to the task of discovering, distributing, and building human machine interfaces (HMIs) for ICS, as the highly individualized and often proprietary individual components of ICSs have vastly different interfaces leading to a need to download hundreds of applications. We propose the No Effort Rapid Development (NERD) middleware framework to address the challenges of in-field HMI discovery, provisioning, communication, and co-evolution with related ICSs. Middleware services offer the ability to simplify on-demand HMI distribution and operation of ICSs. NERD leverages existing ICS device-markers (e.g., QR-codes or RFID tags) or Bluetooth low-energy protocols for rapid cyber-physical discovery and provisioning of HMIs in the field. Device-markers and Bluetooth low-energy protocols have a very limited data capacity and transmission speed, and to achieve on-device storage of HMIs, we propose using a compact data-driven domain-specific language that emphasizes data sources and sinks between the HMI and IC.

Keywords Internet of things – Industrial internet – Middleware – Human machine interfaces – Domain-specific language

 

Enhancing context data distribution for the internet of things using QoC-awareness and attribute-based access control

Léon Lim¹, Pierrick Marie, Denis Conan¹, Sophie Chabridon¹, Thierry Desprats, Atif Manzoor¹

(1) Télécom SudParis, Évry, France
(2) Université de Toulouse, France

Abstract The Internet of Things (IoT) enables producers of context data like sensors to interact with remote consumers of context data like smart pervasive applications in an entirely decoupled way. However, two important issues are faced by context data distribution, namely providing context information with a sufficient level of quality—i.e. quality of context (QoC)—while preserving the privacy of context owners. This article presents the solutions provided by the INCOME middleware framework for addressing these two potentially contradictory issues while hiding the complexity of context data distribution in heterogeneous and large-scale environments. Context producers and consumers not only express their needs in context contracts but also the guarantees they are ready to fulfil. These contracts are then translated into advertisement and subscription filters to determine how to distribute context data. Our experiments on a first open source prototype show that QoC-based filtering and privacy protection using attributed-based access control can be performed at a reasonable cost.

Keywords IoT – Middleware – Distributed event-based systems – Quality of context – Privacy – Access control policy – Attribute-based access control

 

CIRUS: an elastic cloud-based framework for Ubilytics

Linh Manh Pham, Ahmed El-Rheddane, Didier Donsez, Noel de Palma

University of Grenoble Alpes, France

Abstract The Internet of Things (IoT) has become a reality with the availability of chatty embedded devices. The huge amount of data generated by things must be analysed with models and technologies of the “Big Data Analytics”, deployed on cloud platforms. The CIRUS project aims to deliver a generic and elastic cloud-based framework for Ubilytics (ubiquitous big data analytics). The CIRUS framework collects and analyses IoT data for Machine to Machine services using Component-off-the-Shelves (COTS) such as IoT gateways, Message brokers or Message-as-a-Service providers and big data analytics platforms deployed and reconfigured dynamically with Roboconf. In this paper, we demonstrate and evaluate the genericity and elasticity of CIRUS with the deployment of a Ubilytics use case using a real dataset based on records originating from a practical source.

Keywords Big data analytics – Cloud computing – Elasticity – Internet of Things – Middleware Ubilytics

 

Model-driven interoperability: engineering heterogeneous IoT systems

Paul Grace, Brian Pickering, Mike Surridge

University of Southampton, UK

Abstract Interoperability remains a significant burden to the developers of Internet of Things systems. This is because resources and APIs are dynamically composed; they are highly heterogeneous in terms of their underlying communication technologies, protocols and data formats, and interoperability tools remain limited to enforcing standards-based approaches. In this paper, we propose model-based engineering methods to reduce the development effort towards ensuring that complex software systems interoperate with one another. Lightweight interoperability models can be specified in order to monitor and test the execution of running software so that interoperability problems can be quickly identified, and solutions put in place. A graphical model editor and testing tool are also presented to highlight how a visual model improves upon textual specifications. We show using case-studies from the FIWARE Future Internet Service domain that the software framework can support non-expert developers to address interoperability challenges.

Keywords Model driven engineering – Interoperability –Cloud computing – Internet of things

 

Open Topics

Performance analysis of a MIMO-RFID system in Nakagami-m fading channels

Kiattisak Maichalernnukul^1,2, Feng Zheng², Thomas Kaiser²

(1) Rangsit University, Pathumthani, Thailand
(2) University of Duisburg- Essen, Germany

Abstract We analyze the bit error rate (BER) performance of a multiple-input multiple-output (MIMO) radio-frequency-identification (RFID) system employing orthogonal space-time block codes when the forward and backward channels exhibit independent but not necessarily identically distributed Nakagami-m fading. A closed-form upper bound on the BER performance is derived, and the corresponding diversity order is quantified. Numerical results provide some insight into the impact of several different parameters on the system performance.

Keywords Bit error rate (BER) – Multiple-input multiple-output (MIMO) – Radio frequency identification (RFID) – Space-time block codes

 

MIMO slotted ALOHA systems with collision resolution and truncated HARQ transmission and combining

Nejah Missaoui¹, Ines Kammoun¹, Mohamed Siala²

Abstract In this paper, we investigate throughput and delay enhancement for two multi-user multiple-input multiple-output (MIMO) systems one with space-time block coding (STBC), the other with spatial multiplexing (SM) at the transmitter. Users operate using the slotted ALOHA (SA) protocol to access the wireless channel resulting in a high probability of collision. For both systems, we consider the uplink scenario, and we propose to recover the collided packets with spatial successive interference cancelation (SSIC) and a protocol for retransmission and combining of unsuccessfully received collided packets applying a truncated Hybrid Automatic Repeat reQuest (HARQ) scheme. For the first system, we propose to use channel realizations of collided packets as different signatures to separate them. Moreover, we propose a solution for the problem when the received powers are comparable. For this system, we note that the orthogonality of the STBC matrix allows the use of a simple linear processing step for the initialization of SSIC. For the SM multi-user system, the separation of collided packets is based on V-BLAST processing and SSIC. We also propose how to combine retransmitted packets. For both systems, we evaluate the block error rate, the throughput, and the delay. A comparison is done with the single-user case and with other receivers proposed in the literature.

Keywords Multi-user detection – Slotted ALOHA – Space-time coding – Successive interference canceller – Spatial multiplexing – Throughput