Risk Assessment Edge Contract for Efficient Resource Allocation Article Swipe
Minghui Sheng
,
Hui Wang
,
Maode Ma
,
Yiying Sun
,
Run Zhou
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12070983
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12070983
The rapid growth of edge devices and mobile applications has driven the adoption of edge computing to handle computing tasks closer to end-users. However, the heterogeneity of edge devices and their limited computing resources raise challenges in the efficient allocation of computing resources to complete services with different characteristics and preferences. In this paper, we delve into an edge scenario comprising multiple Edge Computing Servers (ECSs), multiple Device-to-Device (D2D) Edge Nodes (ENs), and multiple edge devices. In order to address the resource allocation challenge among ECSs, ENs, and edge devices in high-workload environments, as well as the pricing of edge resources within the resource market framework, we propose a Risk Assessment Contract Algorithm (RACA) based on risk assessment theory. The RACA enables ECSs to assess risks associated with local users by estimating their future revenue potential and updating the contract autonomously at present and in the future. ENs acquire additional resources from ECSs to efficiently complete local users’ tasks. Simultaneously, ENs can also negotiate reasonable resource requests and pricing with ECSs by a Stackelberg game algorithm. Furthermore, we prove the unique existence of Nash equilibrium in the established game, implying that equilibrium solutions can stably converge through computational methods in heterogeneous environments. Finally, through simulation experiments on the dataset, we demonstrate that risk assessment can better enhance the overall profit capability of the system. Moreover, through multiple experiments, we showcase the stability of the contract’s autonomous update capability. The RACA exhibits better utility in terms of system profit capabilities, stability in high-workload environments, and energy consumption. This work provides a more dynamic and effective solution to the resource allocation problem in edge systems under high-workload environments.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math12070983
- https://www.mdpi.com/2227-7390/12/7/983/pdf?version=1711445772
- OA Status
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- References
- 35
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- 10
- OpenAlex ID
- https://openalex.org/W4393187252
All OpenAlex metadata
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https://openalex.org/W4393187252Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/math12070983Digital Object Identifier
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Risk Assessment Edge Contract for Efficient Resource AllocationWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-03-26Full publication date if available
- Authors
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Minghui Sheng, Hui Wang, Maode Ma, Yiying Sun, Run ZhouList of authors in order
- Landing page
-
https://doi.org/10.3390/math12070983Publisher landing page
- PDF URL
-
https://www.mdpi.com/2227-7390/12/7/983/pdf?version=1711445772Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-7390/12/7/983/pdf?version=1711445772Direct OA link when available
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Resource allocation, Enhanced Data Rates for GSM Evolution, Business, Computer science, Computer network, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.and | 6, 29, 49, 72, 87, 136, 143, 167, 253, 262 |
| abstract_inverted_index.can | 161, 193, 214 |
| abstract_inverted_index.has | 9 |
| abstract_inverted_index.the | 11, 24, 37, 80, 96, 102, 138, 145, 179, 186, 207, 217, 222, 230, 233, 266 |
| abstract_inverted_index.ECSs | 122, 152, 170 |
| abstract_inverted_index.ENs, | 86 |
| abstract_inverted_index.Edge | 62, 69 |
| abstract_inverted_index.Nash | 183 |
| abstract_inverted_index.RACA | 120, 239 |
| abstract_inverted_index.Risk | 109 |
| abstract_inverted_index.This | 256 |
| abstract_inverted_index.also | 162 |
| abstract_inverted_index.edge | 4, 14, 27, 58, 74, 88, 99, 271 |
| abstract_inverted_index.from | 151 |
| abstract_inverted_index.game | 174 |
| abstract_inverted_index.into | 56 |
| abstract_inverted_index.more | 260 |
| abstract_inverted_index.risk | 116, 212 |
| abstract_inverted_index.that | 190, 211 |
| abstract_inverted_index.this | 52 |
| abstract_inverted_index.well | 94 |
| abstract_inverted_index.with | 46, 127, 169 |
| abstract_inverted_index.work | 257 |
| abstract_inverted_index.(D2D) | 68 |
| abstract_inverted_index.ECSs, | 85 |
| abstract_inverted_index.Nodes | 70 |
| abstract_inverted_index.among | 84 |
| abstract_inverted_index.based | 114 |
| abstract_inverted_index.delve | 55 |
| abstract_inverted_index.game, | 188 |
| abstract_inverted_index.local | 128, 156 |
| abstract_inverted_index.order | 77 |
| abstract_inverted_index.prove | 178 |
| abstract_inverted_index.raise | 34 |
| abstract_inverted_index.rapid | 1 |
| abstract_inverted_index.risks | 125 |
| abstract_inverted_index.tasks | 19 |
| abstract_inverted_index.terms | 244 |
| abstract_inverted_index.their | 30, 132 |
| abstract_inverted_index.under | 273 |
| abstract_inverted_index.users | 129 |
| abstract_inverted_index.(ENs), | 71 |
| abstract_inverted_index.(RACA) | 113 |
| abstract_inverted_index.assess | 124 |
| abstract_inverted_index.better | 215, 241 |
| abstract_inverted_index.closer | 20 |
| abstract_inverted_index.driven | 10 |
| abstract_inverted_index.energy | 254 |
| abstract_inverted_index.future | 133 |
| abstract_inverted_index.growth | 2 |
| abstract_inverted_index.handle | 17 |
| abstract_inverted_index.market | 104 |
| abstract_inverted_index.mobile | 7 |
| abstract_inverted_index.paper, | 53 |
| abstract_inverted_index.profit | 219, 247 |
| abstract_inverted_index.stably | 194 |
| abstract_inverted_index.system | 246 |
| abstract_inverted_index.tasks. | 158 |
| abstract_inverted_index.unique | 180 |
| abstract_inverted_index.update | 236 |
| abstract_inverted_index.within | 101 |
| abstract_inverted_index.(ECSs), | 65 |
| abstract_inverted_index.Servers | 64 |
| abstract_inverted_index.acquire | 148 |
| abstract_inverted_index.address | 79 |
| abstract_inverted_index.devices | 5, 28, 89 |
| abstract_inverted_index.dynamic | 261 |
| abstract_inverted_index.enables | 121 |
| abstract_inverted_index.enhance | 216 |
| abstract_inverted_index.future. | 146 |
| abstract_inverted_index.limited | 31 |
| abstract_inverted_index.methods | 198 |
| abstract_inverted_index.overall | 218 |
| abstract_inverted_index.present | 142 |
| abstract_inverted_index.pricing | 97, 168 |
| abstract_inverted_index.problem | 269 |
| abstract_inverted_index.propose | 107 |
| abstract_inverted_index.revenue | 134 |
| abstract_inverted_index.system. | 223 |
| abstract_inverted_index.systems | 272 |
| abstract_inverted_index.theory. | 118 |
| abstract_inverted_index.through | 196, 203, 225 |
| abstract_inverted_index.utility | 242 |
| abstract_inverted_index.Contract | 111 |
| abstract_inverted_index.Finally, | 202 |
| abstract_inverted_index.However, | 23 |
| abstract_inverted_index.adoption | 12 |
| abstract_inverted_index.complete | 44, 155 |
| abstract_inverted_index.contract | 139 |
| abstract_inverted_index.converge | 195 |
| abstract_inverted_index.dataset, | 208 |
| abstract_inverted_index.devices. | 75 |
| abstract_inverted_index.exhibits | 240 |
| abstract_inverted_index.implying | 189 |
| abstract_inverted_index.multiple | 61, 66, 73, 226 |
| abstract_inverted_index.provides | 258 |
| abstract_inverted_index.requests | 166 |
| abstract_inverted_index.resource | 81, 103, 165, 267 |
| abstract_inverted_index.scenario | 59 |
| abstract_inverted_index.services | 45 |
| abstract_inverted_index.showcase | 229 |
| abstract_inverted_index.solution | 264 |
| abstract_inverted_index.updating | 137 |
| abstract_inverted_index.users’ | 157 |
| abstract_inverted_index.Algorithm | 112 |
| abstract_inverted_index.Computing | 63 |
| abstract_inverted_index.Moreover, | 224 |
| abstract_inverted_index.challenge | 83 |
| abstract_inverted_index.computing | 15, 18, 32, 41 |
| abstract_inverted_index.different | 47 |
| abstract_inverted_index.effective | 263 |
| abstract_inverted_index.efficient | 38 |
| abstract_inverted_index.existence | 181 |
| abstract_inverted_index.negotiate | 163 |
| abstract_inverted_index.potential | 135 |
| abstract_inverted_index.resources | 33, 42, 100, 150 |
| abstract_inverted_index.solutions | 192 |
| abstract_inverted_index.stability | 231, 249 |
| abstract_inverted_index.Assessment | 110 |
| abstract_inverted_index.additional | 149 |
| abstract_inverted_index.algorithm. | 175 |
| abstract_inverted_index.allocation | 39, 82, 268 |
| abstract_inverted_index.assessment | 117, 213 |
| abstract_inverted_index.associated | 126 |
| abstract_inverted_index.autonomous | 235 |
| abstract_inverted_index.capability | 220 |
| abstract_inverted_index.challenges | 35 |
| abstract_inverted_index.comprising | 60 |
| abstract_inverted_index.end-users. | 22 |
| abstract_inverted_index.estimating | 131 |
| abstract_inverted_index.framework, | 105 |
| abstract_inverted_index.reasonable | 164 |
| abstract_inverted_index.simulation | 204 |
| abstract_inverted_index.Stackelberg | 173 |
| abstract_inverted_index.capability. | 237 |
| abstract_inverted_index.demonstrate | 210 |
| abstract_inverted_index.efficiently | 154 |
| abstract_inverted_index.equilibrium | 184, 191 |
| abstract_inverted_index.established | 187 |
| abstract_inverted_index.experiments | 205 |
| abstract_inverted_index.Furthermore, | 176 |
| abstract_inverted_index.applications | 8 |
| abstract_inverted_index.autonomously | 140 |
| abstract_inverted_index.consumption. | 255 |
| abstract_inverted_index.contract’s | 234 |
| abstract_inverted_index.experiments, | 227 |
| abstract_inverted_index.preferences. | 50 |
| abstract_inverted_index.capabilities, | 248 |
| abstract_inverted_index.computational | 197 |
| abstract_inverted_index.environments, | 92, 252 |
| abstract_inverted_index.environments. | 201, 275 |
| abstract_inverted_index.heterogeneity | 25 |
| abstract_inverted_index.heterogeneous | 200 |
| abstract_inverted_index.high-workload | 91, 251, 274 |
| abstract_inverted_index.Simultaneously, | 159 |
| abstract_inverted_index.characteristics | 48 |
| abstract_inverted_index.Device-to-Device | 67 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5039712178 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I135237710 |
| citation_normalized_percentile.value | 0.87358154 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |