A Block-Structured Optimization Approach for Data Sensing and Computing in Vehicle-Assisted Edge Computing Networks Article Swipe
Luan N. T. Huynh
,
Md. Delowar Hossain
,
Quoc‐Viet Pham
,
Yan Kyaw Tun
,
Eui‐Nam Huh
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/jsen.2023.3332230
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/jsen.2023.3332230
With the rapid development of Internet-of-things (IoT) applications and multiaccess edge computing (MEC) technology, massive amounts of sensing data can be collected and transmitted to MEC servers for rapid processing. On the other hand, as the number of IoT devices grows, the MEC server cannot perform tremendous computing tasks because of its limited computation capacity. This article introduces a vehicle-assisted MEC framework that leverages vehicles to provide computational services for IoT devices and overcome this challenge. The problem of latency minimization was formulated by optimizing the sensing data rate, offloading decisions, and resource allocation while considering energy consumption constraints. Nevertheless, achieving the global optimal solution in polynomial time is challenging because the formulated problem is mixed-integer nonlinear and nonconvex. This article provides an efficient algorithm that adopts the block coordinate descent technique to decompose the original problem into four subproblems. These subproblems can be solved using Lagrangian relaxation and the block successive upper bound minimization (BSUM) method. The superiority of the proposed approach in reducing latency compared with baseline schemes is evident from the simulation results.
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- Language
- en
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- OA Status
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https://openalex.org/W4388755269Canonical identifier for this work in OpenAlex
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https://doi.org/10.1109/jsen.2023.3332230Digital Object Identifier
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A Block-Structured Optimization Approach for Data Sensing and Computing in Vehicle-Assisted Edge Computing NetworksWork title
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articleOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
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2023-11-17Full publication date if available
- Authors
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Luan N. T. Huynh, Md. Delowar Hossain, Quoc‐Viet Pham, Yan Kyaw Tun, Eui‐Nam HuhList of authors in order
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https://doi.org/10.1109/jsen.2023.3332230Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://hdl.handle.net/2262/104226Direct OA link when available
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Block (permutation group theory), Computer science, Edge computing, Enhanced Data Rates for GSM Evolution, Distributed computing, Computational science, Telecommunications, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 1, 31, 35, 41, 85, 101, 111, 127, 134, 149, 160, 173 |
| abstract_inverted_index.was | 81 |
| abstract_inverted_index.This | 55, 119 |
| abstract_inverted_index.With | 0 |
| abstract_inverted_index.data | 18, 87 |
| abstract_inverted_index.edge | 10 |
| abstract_inverted_index.four | 138 |
| abstract_inverted_index.from | 172 |
| abstract_inverted_index.into | 137 |
| abstract_inverted_index.that | 62, 125 |
| abstract_inverted_index.this | 74 |
| abstract_inverted_index.time | 107 |
| abstract_inverted_index.with | 167 |
| abstract_inverted_index.(IoT) | 6 |
| abstract_inverted_index.(MEC) | 12 |
| abstract_inverted_index.These | 140 |
| abstract_inverted_index.block | 128, 150 |
| abstract_inverted_index.bound | 153 |
| abstract_inverted_index.hand, | 33 |
| abstract_inverted_index.other | 32 |
| abstract_inverted_index.rapid | 2, 28 |
| abstract_inverted_index.rate, | 88 |
| abstract_inverted_index.tasks | 48 |
| abstract_inverted_index.upper | 152 |
| abstract_inverted_index.using | 145 |
| abstract_inverted_index.while | 94 |
| abstract_inverted_index.(BSUM) | 155 |
| abstract_inverted_index.adopts | 126 |
| abstract_inverted_index.cannot | 44 |
| abstract_inverted_index.energy | 96 |
| abstract_inverted_index.global | 102 |
| abstract_inverted_index.grows, | 40 |
| abstract_inverted_index.number | 36 |
| abstract_inverted_index.server | 43 |
| abstract_inverted_index.solved | 144 |
| abstract_inverted_index.amounts | 15 |
| abstract_inverted_index.article | 56, 120 |
| abstract_inverted_index.because | 49, 110 |
| abstract_inverted_index.descent | 130 |
| abstract_inverted_index.devices | 39, 71 |
| abstract_inverted_index.evident | 171 |
| abstract_inverted_index.latency | 79, 165 |
| abstract_inverted_index.limited | 52 |
| abstract_inverted_index.massive | 14 |
| abstract_inverted_index.method. | 156 |
| abstract_inverted_index.optimal | 103 |
| abstract_inverted_index.perform | 45 |
| abstract_inverted_index.problem | 77, 113, 136 |
| abstract_inverted_index.provide | 66 |
| abstract_inverted_index.schemes | 169 |
| abstract_inverted_index.sensing | 17, 86 |
| abstract_inverted_index.servers | 26 |
| abstract_inverted_index.approach | 162 |
| abstract_inverted_index.baseline | 168 |
| abstract_inverted_index.compared | 166 |
| abstract_inverted_index.original | 135 |
| abstract_inverted_index.overcome | 73 |
| abstract_inverted_index.proposed | 161 |
| abstract_inverted_index.provides | 121 |
| abstract_inverted_index.reducing | 164 |
| abstract_inverted_index.resource | 92 |
| abstract_inverted_index.results. | 175 |
| abstract_inverted_index.services | 68 |
| abstract_inverted_index.solution | 104 |
| abstract_inverted_index.vehicles | 64 |
| abstract_inverted_index.achieving | 100 |
| abstract_inverted_index.algorithm | 124 |
| abstract_inverted_index.capacity. | 54 |
| abstract_inverted_index.collected | 21 |
| abstract_inverted_index.computing | 11, 47 |
| abstract_inverted_index.decompose | 133 |
| abstract_inverted_index.efficient | 123 |
| abstract_inverted_index.framework | 61 |
| abstract_inverted_index.leverages | 63 |
| abstract_inverted_index.nonlinear | 116 |
| abstract_inverted_index.technique | 131 |
| abstract_inverted_index.Lagrangian | 146 |
| abstract_inverted_index.allocation | 93 |
| abstract_inverted_index.challenge. | 75 |
| abstract_inverted_index.coordinate | 129 |
| abstract_inverted_index.decisions, | 90 |
| abstract_inverted_index.formulated | 82, 112 |
| abstract_inverted_index.introduces | 57 |
| abstract_inverted_index.nonconvex. | 118 |
| abstract_inverted_index.offloading | 89 |
| abstract_inverted_index.optimizing | 84 |
| abstract_inverted_index.polynomial | 106 |
| abstract_inverted_index.relaxation | 147 |
| abstract_inverted_index.simulation | 174 |
| abstract_inverted_index.successive | 151 |
| abstract_inverted_index.tremendous | 46 |
| abstract_inverted_index.challenging | 109 |
| abstract_inverted_index.computation | 53 |
| abstract_inverted_index.considering | 95 |
| abstract_inverted_index.consumption | 97 |
| abstract_inverted_index.development | 3 |
| abstract_inverted_index.multiaccess | 9 |
| abstract_inverted_index.processing. | 29 |
| abstract_inverted_index.subproblems | 141 |
| abstract_inverted_index.superiority | 158 |
| abstract_inverted_index.technology, | 13 |
| abstract_inverted_index.transmitted | 23 |
| abstract_inverted_index.applications | 7 |
| abstract_inverted_index.constraints. | 98 |
| abstract_inverted_index.minimization | 80, 154 |
| abstract_inverted_index.subproblems. | 139 |
| abstract_inverted_index.Nevertheless, | 99 |
| abstract_inverted_index.computational | 67 |
| abstract_inverted_index.mixed-integer | 115 |
| abstract_inverted_index.vehicle-assisted | 59 |
| abstract_inverted_index.Internet-of-things | 5 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8999999761581421 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.20635114 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |