Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT
The Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/18/3970 |
| _version_ | 1817991693125812224 |
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| author | Pascale Minet Yasuyuki Tanaka |
| author_facet | Pascale Minet Yasuyuki Tanaka |
| author_sort | Pascale Minet |
| collection | DOAJ |
| description | The Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its ability to meet three Key Performance Indicators (KPIs), namely a maximum acceptable end-to-end latency <i>L</i>, a targeted end-to-end reliability <i>R</i> and a minimum network lifetime <i>T</i>. The IoT network has to guarantee that at least <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> of messages generated by sensor nodes are delivered to the sink with a latency ≤<i>L</i>, whereas the network lifetime is at least equal to <i>T</i>. In this paper, we show how to provide the targeted end-to-end reliability <i>R</i> by means of retransmissions to cope with the unreliability of wireless links. We present two methods to compute the maximum number of transmissions per message required to achieve <i>R</i>. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula> is very easy to compute, whereas <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> minimizes the total number of transmissions necessary for a message to reach the sink. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> are then integrated into a TSCH network with a load-based scheduler to evaluate the three KPIs on a generic data-gathering application. We first consider a toy example with eight nodes where the maximum number of transmissions <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>a</mi> <mi>x</mi> <mi>T</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>s</mi> </mrow> </semantics> </math> </inline-formula> is tuned per link and per flow. Finally, a network of 50 nodes, representative of real network deployments, is evaluated assuming <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>a</mi> <mi>x</mi> <mi>T</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>s</mi> </mrow> </semantics> </math> </inline-formula> is fixed. For both TSCH networks, we show that <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> provides a better reliability and a longer lifetime than <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula>, which provides a shorter average end-to-end latency. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> provides more predictable end-to-end performances than Kausa, a KPI-aware, state-of-the-art scheduler. |
| first_indexed | 2024-04-14T01:16:38Z |
| format | Article |
| id | doaj.art-2c35c2a968e74f2da43b5e2e912784ba |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:16:38Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2c35c2a968e74f2da43b5e2e912784ba2022-12-22T02:20:50ZengMDPI AGSensors1424-82202019-09-011918397010.3390/s19183970s19183970Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoTPascale Minet0Yasuyuki Tanaka1Inria Research Center of Paris, 75012 Paris, FranceInria Research Center of Paris, 75012 Paris, FranceThe Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its ability to meet three Key Performance Indicators (KPIs), namely a maximum acceptable end-to-end latency <i>L</i>, a targeted end-to-end reliability <i>R</i> and a minimum network lifetime <i>T</i>. The IoT network has to guarantee that at least <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> of messages generated by sensor nodes are delivered to the sink with a latency ≤<i>L</i>, whereas the network lifetime is at least equal to <i>T</i>. In this paper, we show how to provide the targeted end-to-end reliability <i>R</i> by means of retransmissions to cope with the unreliability of wireless links. We present two methods to compute the maximum number of transmissions per message required to achieve <i>R</i>. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula> is very easy to compute, whereas <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> minimizes the total number of transmissions necessary for a message to reach the sink. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> are then integrated into a TSCH network with a load-based scheduler to evaluate the three KPIs on a generic data-gathering application. We first consider a toy example with eight nodes where the maximum number of transmissions <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>a</mi> <mi>x</mi> <mi>T</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>s</mi> </mrow> </semantics> </math> </inline-formula> is tuned per link and per flow. Finally, a network of 50 nodes, representative of real network deployments, is evaluated assuming <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>a</mi> <mi>x</mi> <mi>T</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>s</mi> </mrow> </semantics> </math> </inline-formula> is fixed. For both TSCH networks, we show that <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> provides a better reliability and a longer lifetime than <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>F</mi> <mi>a</mi> <mi>i</mi> <mi>r</mi> </mrow> </semantics> </math> </inline-formula>, which provides a shorter average end-to-end latency. <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>O</mi> <mi>p</mi> <mi>t</mi> </mrow> </semantics> </math> </inline-formula> provides more predictable end-to-end performances than Kausa, a KPI-aware, state-of-the-art scheduler.https://www.mdpi.com/1424-8220/19/18/3970IoTindustrial IoTreliabilityTSCHlatencyschedulingnetwork lifetimeIEEE802.15.4ePDRETXretransmissionprobabilistic guarantee |
| spellingShingle | Pascale Minet Yasuyuki Tanaka Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT Sensors IoT industrial IoT reliability TSCH latency scheduling network lifetime IEEE802.15.4e PDR ETX retransmission probabilistic guarantee |
| title | Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT |
| title_full | Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT |
| title_fullStr | Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT |
| title_full_unstemmed | Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT |
| title_short | Optimal Number of Message Transmissions for Probabilistic Guarantee of Latency in the IoT |
| title_sort | optimal number of message transmissions for probabilistic guarantee of latency in the iot |
| topic | IoT industrial IoT reliability TSCH latency scheduling network lifetime IEEE802.15.4e PDR ETX retransmission probabilistic guarantee |
| url | https://www.mdpi.com/1424-8220/19/18/3970 |
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