autorzy:
Adam Kozłowski^a, Janusz Sosnowski^a

(^aTRONIX sp. z o.o., ul. Wrzosowa 37A, Zielonka 05-220, Poland
^aInstitute of Computer Science, Warsaw University of Technology, ul. Nowowiejska 15/18, Warsaw 00-665, Poland)

Abstract
Planning the transmission routing and scheduling is a challenging issue in industrial wireless networks (IWN) due to high quality of service (QoS) requirements. Moreover, in many applications we face the problem of node mobility, changes of transmission conditions, node resource and powering limitations. This paper initially formulates the problem of searching optimal network configuration covering the outlined features and subsequently proposes an effective solution. It is designed for typical industrial FDMA and TDMA networks with horizontal communication. The goal of our studies is to find IWN configuration (routing, time slot and channel allocation) that maximizes the number of successfully concluded contracts. The presented method is compatible with the ISA100.11a standard and integrates relevant QoS requirements for different periodic and aperiodic contracts. Our approach is based on original deterministic algorithms for planning the traffic. They are optimized with a genetic algorithm and facilitate the adaptation to changing operation conditions of network nodes. Extensive simulation experiments have been used in the development and evaluation of the proposed algorithms. The introduced test environment and benchmarks confirmed the advantages of our approach and revealed drawbacks of other approaches.

Keywords

Industrial wireless networks, network configuration, transmission scheduling, quality of service, simulation schemes

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autorzy: Adam Kozłowski^a, Janusz Sosnowski^a

(^aInstitute of Computer Science, Warsaw University of Technology, ul. Nowowiejska 15/18, Warsaw 00-665, Poland)

Abstract
Wireless network nodes working in industrial environment or mounted on mobile machines are exposed to frequent and unpredictable temperature changes, which impact local clock accuracy resulting in synchronization problems (time offset). These issues have to be taken into account when optimizing the network to avoid higher energy consumption and traffic congestion. The time offset problem can be alleviated using temperature driven compensation. In the paper we propose an efficient algorithm to resolve this problem taking into account slow and rapid temperature fluctuations. It combines the physical model of the node oscillator with an original prediction method based on the linear regression. It can be embedded in low cost microcontrollers with limited resources. Our approach needed some experimental studies of oscillator features and microcontroller capabilities. The implemented prototype nodes and performed tests proved high clock resilience for industrial environment as compared with other approaches.

Keywords

Industrial wireless networksSynchronization resiliencyTime offset compensationOffset predictionEnergy savings

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autorzy:
 Adam Kozłowski^a, Janusz Sosnowski^a

(^aInstitute of Computer Science, Warsaw University of Technology, ul. Nowowiejska 15/18, Warsaw 00-665, Poland)

Abstract
Energy consumption has become dominant issue for wireless internet of things (IoT) networks with battery-powered nodes. The prevailing mechanism allowing to reduce energy consumption is duty-cycling. In this technique the node sleeps most of the time and wakes up only at selected moments to extend the lifespan of nodes up to 5–10 years. Unfortunately, the scheduled duty-cycling technique is always a trade-of between energy consumption and delay in delivering data to the target node. The delay problem can be alleviated with an additional wake-up radio (WuR) channel. In the paper we present original power consumption models for various duty-cycling schemes. They are the basis for checking whether WuR approach is competitive with scheduled duty-cycling techniques. We determine the maximum energy level that an additional wake-up radio can consume to become a reasonable alternative of widely used duty-cycling techniques for typical IoT networks.

Keywords
Duty-cycling, Wake-up radio (WuR), Energy consumption, Wireless sensornetworks (WSNs), Internet of things (IoT)

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autorzy:
 Adam Kozłowski^a, Janusz Sosnowski^a

(^aInstitute of Computer Science, Warsaw University of Technology, ul. Nowowiejska 15/18, Warsaw 00-665, Poland)

Abstract
Practical proliferation of Internet of Things (IoT) concept depends upon communication efficiency in the related network. In the paper we outline basic features of wireless communication protocols used in IoT and concentrate on analysing communication overheads. In particular, we discuss the impact of IPv6 packet length on 6LoWPAN network operation with physical and MAC layer defined by IEEE 802.15.4 standard. The presented analysis methodology is useful in estimation of the total goodput (throughput at the application level) and energy consumptions within the whole traffic model which are the crucial features of IoT networks.

Keywords
Personal area network, IoT, transmission overhead, 6LoWPAN, IEEE 802.15.4

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autorzy: Adam Kozłowski^a, Janusz Sosnowski^a

(^aInstitute of Computer Science, Warsaw University of Technology, ul. Nowowiejska 15/18, Warsaw 00-665, Poland)

Abstract
Fast growing market related to Internet of Things creates new demands for wireless sensor networks. Here we face the problem of optimizing energy consumption in many miniature electronic devices powered from local batteries and requested long life span of nodes up to 5-10 years. The transmission processes constitute the primary source of energy consumption in the node, however complex data processing can also contribute a non negligible component. Optimizing energy consumption we can use various energy saving schemes, e.g. bringing the nodes in a sleeping mode and waking them periodically. In the paper we analyse in detail time and power components influencing energy consumption profiles. The derived original parameters are helpful to create power consumption models for specific applications. The presented methodology has been verified experimentally within (TI) CC1310F128 chip.

Keywords IoT, energy consumption, wireless sensor networks, software defined network

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