μDDS: A Middleware for Real-time Wireless Embedded Systems

González, Apolinar; Mata, Walter; Villasenor, L.; Aquino, Raúl; Simó, José; Chávez, Marco A. Ávalos; Crespo, Alfons

doi:10.1007/s10846-011-9550-z

Cited by 12 publications

(8 citation statements)

References 15 publications

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“…Moreover, we consider the support for QoS and reliable data delivery service. Specifically, we select from this category the standard-based solutions [6], [7], [27] to mitigate the lack of standardization in WSN. In this section, we summarize the techniques that are related to the implementation of RTDDS and are standardbased pub/sub.…”

Section: Related Workmentioning

confidence: 99%

Reliable Middleware for Wireless Sensor-Actuator Networks

2019

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Many important and critical applications use wireless sensor/actuator networks (WSAN). These applications are spanning widely that range in several environments, including industrial, commercial, and residential. Most of these applications need a certain level of real-time communication in addition to reliable data delivery service. Data distribution service (DDS) is a known standard for supporting realtime distributed systems based on the publish/subscribe model. The DDS specification offers two disparate quality-of-service levels of data reliability, namely: best-effort and fully-reliable. TinyDDS is a lightweight and partial porting of DDS middleware to sensor-based platforms, specifically for platforms with limited resources. However, TinyDDS in its current form lacks the reliability support for data delivery. In this paper, we extended the DDS data reliability service and integrated it into TinyDDS, which resulted in Reliable TinyDDS. Moreover, we provide a prototype and comprehensive performance evaluation of the reliability functions taking into account: number of hops, number of publishers, and several other network parameters. The achieved results indicate that reliable data delivery in real-time for WSAN is possible with optimized system parameters, such as retransmission time-out value of 400ms and number of hops not exceeding 10 for an end-to-end delay ranging from 10 to 100s of milliseconds.

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Section: Related Workmentioning

confidence: 99%

Reliable Middleware for Wireless Sensor-Actuator Networks

2019

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“…The worst-case execution time (WCET) can be measured by task, from the time that a message is read until it is sent, estimating the worst case that can be chosen. In our previous works [38][39][40], a description has also been made of the hardware and software implemented, and a complete calculation of the computing time has been made, taking into account the aspects mentioned above, and used in the same research works, which allows us to estimate the computation time using the WiSe mote as [38] in the worst-case, as 0.03 s by task and 0.08 s in the smart agent node, similarly by task.…”

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

et al. 2016

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This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN), a real-time kernel with an earliest deadline first (EDF) scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS) that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi-loop control networks designed for multi-evaporator systems.

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“…In [30], the widely used mechanisms for reprogramming the sensor nodes : full image replacement and binary difference image replacement are proposed. In [32],Dynamic TinyOS is proposed for Modular and Transparent Incremental Code-Updates.…”

Section: Software Update Mechanisms In Wsnmentioning

confidence: 99%

“…Instead of distributing a new full system image the binary differences, deltas, between the modified and original binary can be distributed. This reduces the amount of data that needs to be transferred [30].Delta algorithms compress data by encoding one file in terms of another. This type of compression is useful in a number of situations: storing multiple versions of data, displaying differences, merging changes, distributing updates, storing backups, transmitting video sequences, and other [55].…”

Section: Diff-based Approachesmentioning

confidence: 99%

A Review on Run-Time Reconfigurations and Code Update Mechanisms in Wireless Sensor Networks

Sreenivas¹

2015

IJIRCCE

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ABSTRACT:The design of wireless sensor networks for distributed applications is the most challenging task due to the factors such as limited storage on nodes, variable data arrival rate and high energy cost of communication. In most Wireless Sensor Networks(WSN), the battery is the sole energy source of the sensor node. The Sensor nodes are expected to work on batteries for several months to a few years without replenishing. Thus, energy efficiency becomes a major issue in WSNs. Nowadays, it is desired to use the WSN in heterogeneous platform for multiple monitoring. The Software development for the sensor node is a tedious task due to the change in network topology. The present state of art has come up with different solutions to overcome the performance issues such as Memory overhead, Heterogeneity, Portability, Scalability, Cost and Quality of Service. An adaptive framework should minimize the resource consumption and provide an optimal solution for run-time Reconfiguration. This paper presents a detailed review on current state-of-the art in the Run-time Reconfigurations of Wireless Sensor Networks. An Analysis is made on the existing middleware approaches and an evaluation is done based on the parameters like Application Openness, Scalability, Heterogeneity, User Friendly Interface, Mobility and Power Efficiency. The paper identifies a few open research issues that must be addressed during the Run-Time Reconfigurations of Wireless Sensor Networks.

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μDDS: A Middleware for Real-time Wireless Embedded Systems

Cited by 12 publications

References 15 publications

Reliable Middleware for Wireless Sensor-Actuator Networks

Reliable Middleware for Wireless Sensor-Actuator Networks

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

A Review on Run-Time Reconfigurations and Code Update Mechanisms in Wireless Sensor Networks

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