Logistic applications with wireless sensor networks

Becker, Markus; Wenning, Bernd-Ludwig; Görg, Carmelita; Jedermann, Reiner; Timm‐Giel, Andreas

doi:10.1145/1978642.1978650

Cited by 20 publications

(18 citation statements)

References 2 publications

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“…Applications such as e-health with wearable sensors (i.e., eldercare and well-being) [19], cargos containers [20], automotive industry or even airport logistics all share similar requirements, including mobile devices. Thus, the upcoming standards should consider the additional constraints due to the nodes movement within the operation of the network.…”

Section: Stability Of Topology: the Example Of Mobilitymentioning

confidence: 99%

Thorough IoT testbed characterization: From proof-of-concept to repeatable experimentations

et al. 2017

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In this paper, we explore the role of simulators and testbeds in the development procedure of protocols or applications for Wireless Sensor Networks (WSNs) and Internet of Things (IoT). We investigate the complementarity between simulation and experimentation studies by evaluating latest features available among open testbeds (e.g., energy monitoring, mobility). We show that monitoring tools and control channels of testbeds allow for identification of crucial issues (e.g., energy consumption, link quality) and we identify some opportunities to leverage those real-life obstacles. In this context, we insist on how simulations and experimentations can be efficiently and successfully coupled with each other in order to obtain reproducible scientific results, rather than sole proofs-of-concept. Indeed, we especially highlight the main characteristics of such evaluation tools that allow to run multiple instances of a same experimental setup over stable and finely controlled components of hardware and real-world environment. For our experiments, we used and evaluated the FIT IoT-LAB facility. Our results show that such open platforms, can guarantee a certain stability of hardware and environment components over time, thus, turning the unexpected failures and changing parameters into core experimental parameters and valuable inputs for enhanced performance evaluation.

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Section: Stability Of Topology: the Example Of Mobilitymentioning

confidence: 99%

Thorough IoT testbed characterization: From proof-of-concept to repeatable experimentations

et al. 2017

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“…Here we are assuming perfectly scheduled timeslots, but in the case of different superframes durations, it will follow the random incidence paradox [28,29] (12) perfectly scheduled and fixed superframes duration are assumed, so SC B = (S/2), where S is any superframe (S D , S C or S O ). In the case of the coordinator in the online state, the scanning and waiting time is dependent on the interval that is adjusted to transfer from the online to discovery state as in (6). The approximated scenario is to harness both the mobility metric (M m ) and density (D m ), which can be derived both based on [30,31] and [32] respectively, to determine the duration between each transfer.…”

Section: = × ×mentioning

confidence: 99%

“…However, default LLDN mode specifications cannot fit the requirement of all the addressed LL applications due to several constraints. Applications like automotive manufacturing, health applications (wearable sensors [5]), cargo containers [6], remote goods tracking [7], airport logistics and portable machine tools all encompass the mobility feature. Sensor nodes movement within a deployment field needs to be addressed carefully by ensuring two important parameters; (i) full area coverage to ensure the entire sensing area field is covered by multiple coordinators and to eliminate any coverage black holes, (ii) all the nodes must have a reliable, lightweight and fast mobility management scheme that minimizes the required time to associate with a new coordinator.…”

Section: Introductionmentioning

confidence: 99%

Tackling Mobility in Low Latency Deterministic Multihop IEEE 802.15.4e Sensor Network

2016

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“…Applications like health (wearable sensors) [3], cargos containers [4], automotive industry and airport logistics all share the aspect of also including mobile nodes. Therefore, the current standards and technologies must consider the overhead of node movement within the functionality of the network.…”

Section: Introductionmentioning

confidence: 99%

Impact of mobility on the IoT MAC infrastructure: IEEE 802.15.4e TSCH and LLDN platform

Al-Nidawi

Yahya

Kemp

2015

2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)

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Abstract-Realizing the target of high reliability and availability is a crucial concept in the IoT context. Different types of IoT applications introduce several requirements and obstacles. One of the important aspects degrading network performance is the node mobility inside the network. Without a solid and adaptive mechanism, node mobility can disrupt the network performance due to dissociations from the network. Hence, reliable techniques must be incorporated to tackle the overhead of node movement. In this paper, the overhead of mobility on both IEEE 802.15.4e timeslotted channel hopping (TSCH) and low latency deterministic (LLDN) modes is investigated. These two modes can be considered as the MAC layer of the IoT paradigm because of their importance and resilience to different network obstacles. In addition, the set of metrics and limitations that influence the network survivability will be identified to ensure efficient mobile node handling process. Both TSCH and LLDN have been implemented via the Contiki OS to determine their functionality. TSCH has been demonstrated to have better node connectivity due to the impact of frame collision in LLDN. In addition, by neglecting the overhead of collision, the LLDN has been shown to have better connectivity and low radio duty cycle (RDC).Index Terms-IEEE 802.15.4e, TSCH, LLDN, Node mobility, Contiki OS.

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Logistic applications with wireless sensor networks

Cited by 20 publications

References 2 publications

Thorough IoT testbed characterization: From proof-of-concept to repeatable experimentations

Thorough IoT testbed characterization: From proof-of-concept to repeatable experimentations

Tackling Mobility in Low Latency Deterministic Multihop IEEE 802.15.4e Sensor Network

Impact of mobility on the IoT MAC infrastructure: IEEE 802.15.4e TSCH and LLDN platform

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