Distributed algorithm engineering for networks of tiny artifacts

Baumgärtner, Tobias; Chatzigiannakis, Ioannis; Fekete, Sándor P.; Fischer, Stefan; Koninis, Christos; Kröller, Alexander; Kruger, Daniela; Mylonas, Georgios; Pfisterer, Dennis

doi:10.1016/j.cosrev.2010.09.006

Cited by 10 publications

(4 citation statements)

References 34 publications

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“…This approach provides a series of benefits like the ability to overcome obstacles in communication [69,70] and, most importantly, enhanced network security [71]. However, recent trials carried out in real-world wireless sensor networks have highlighted certain difficulties and limitations of the multi-hop, short-range connectivity paradigm [72]. Thus said, a series of alternative solutions was proposed specifically to mitigate these limitations, for instance deploying nodes with different transmission ranges [70], enforcing a hierarchical network structure [73] or using dedicated mobile nodes for managing the network [74].…”

Section: Deploying Low-power Long-range Networkmentioning

confidence: 99%

A Smart Water Metering Deployment Based on the Fog Computing Paradigm

Amaxilatis¹,

Chatzigiannakis

Tselios

et al. 2020

Applied Sciences

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In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system’s design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system.

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Section: Deploying Low-power Long-range Networkmentioning

confidence: 99%

A Smart Water Metering Deployment Based on the Fog Computing Paradigm

Amaxilatis¹,

Chatzigiannakis

Tselios

et al. 2020

Applied Sciences

Self Cite

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“…Apart from these technical considerations, there is also an urgent need to raise awareness of the potential benefits of SDL for IoT systems development. For example, SDL is not mentioned in the 2011 survey [16], though this does include ns-2, which was used in conjunction with SDL [17]. Also there is no mention of SDL in [18].…”

Section: What Is Needed To Make Sdl the Language Of Choice For Iot Symentioning

confidence: 99%

SDL - The IoT Language

Sherratt

Ober

Gaudin³

et al. 2015

SDL 2015: Model-Driven Engineering for Smart Cities

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Interconnected smart devices constitute a large and rapidly growing element of the contemporary Internet. A smart thing can be as simple as a web-enabled device that collects and transmits sensor data to a repository for analysis, or as complex as a web-enabled system to monitor and manage a smart home. Smart things present marvellous opportunities, but when they participate in complex systems, they challenge our ability to manage risk and ensure reliability. SDL, the ITU Standard Specification and Description Language, provides many advantages for modelling and simulating communicating agents --- such as smart things --- before they are deployed. The potential for SDL to enhance reliability and safety is explored with respect to existing smart things below. But SDL must advance if it is to become the language of choice for developing the next generation of smart things. In particular, it must target emerging IoT platforms, it must support simulation of interactions between pre-existing smart things and new smart things, and it must facilitate deployment of large numbers of similar things. Moreover, awareness of the potential benefits of SDL must be raised if those benefits are to be realized in the current and future Internet of Things.publishersversio

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“…Such a multi-path approach provides certain benefits, such as the capability to overcome communication obstacles [3,4], and the overall improvement of security of the network [5]. Experimentation over real-world wireless sensor networks has highlighted the difficulties and limitations of the multi-hop short-range paradigm [6]. In order to overcome these technical difficulties, several alternative solutions have been proposed, for example, by varying the transmission range of the nodes [4], providing hierarchical network structures [7] or even employing mobile nodes to facilitate network management [8].…”

Section: Introduction Related Work and Our Approachmentioning

confidence: 99%

Design and Analysis of Adaptive Hierarchical Low-Power Long-Range Networks

Amaxilatis

Chatzigiannakis

2018

JSAN

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A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications.

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Distributed algorithm engineering for networks of tiny artifacts

Cited by 10 publications

References 34 publications

A Smart Water Metering Deployment Based on the Fog Computing Paradigm

A Smart Water Metering Deployment Based on the Fog Computing Paradigm

SDL - The IoT Language

Design and Analysis of Adaptive Hierarchical Low-Power Long-Range Networks

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