Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment
With the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is g...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/17/2156 |
| _version_ | 1797521547872698368 |
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| author | Svetlana Kim Jieun Kang YongIk Yoon |
| author_facet | Svetlana Kim Jieun Kang YongIk Yoon |
| author_sort | Svetlana Kim |
| collection | DOAJ |
| description | With the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is generating or on a nearby server. Previous studies have proposed offloading between IoT devices through local-edge collaboration from resource-constrained edge servers. However, they did not consider nearby edge servers in the same layer with computing resources. Consequently, quality of service (QoS) degrade due to restricted resources of edge computing and higher execution latency due to congestion. To handle offloaded tasks in a rapidly changing dynamic environment, finding an optimal target server is still challenging. Therefore, a new cooperative offloading method to control edge computing resources is needed to allocate limited resources between distributed edges efficiently. This paper suggests the LODO (linked-object dynamic offloading) algorithm that provides an ideal balance between edges by considering the ready state or running state. LODO algorithm carries out tasks in the list in the order of high correlation between data and tasks through linked objects. Furthermore, dynamic offloading considers the running status of all cooperative terminals and decides to schedule task distribution. That can decrease the average delayed time and average power consumption of terminals. In addition, the resource shortage problem can settle by reducing task processing using its distributions. |
| first_indexed | 2024-03-10T08:14:03Z |
| format | Article |
| id | doaj.art-d2eaa5dabfc64a49b09a487b0c371422 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T08:14:03Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-d2eaa5dabfc64a49b09a487b0c3714222023-11-22T10:30:46ZengMDPI AGElectronics2079-92922021-09-011017215610.3390/electronics10172156Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing EnvironmentSvetlana Kim0Jieun Kang1YongIk Yoon2Research & Business Development Foundation, Sookmyung Women’s University, Seoul 04310, KoreaDepartment of IT Engineering, Sookmyung Women’s University, Seoul 04310, KoreaDepartment of IT Engineering, Sookmyung Women’s University, Seoul 04310, KoreaWith the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is generating or on a nearby server. Previous studies have proposed offloading between IoT devices through local-edge collaboration from resource-constrained edge servers. However, they did not consider nearby edge servers in the same layer with computing resources. Consequently, quality of service (QoS) degrade due to restricted resources of edge computing and higher execution latency due to congestion. To handle offloaded tasks in a rapidly changing dynamic environment, finding an optimal target server is still challenging. Therefore, a new cooperative offloading method to control edge computing resources is needed to allocate limited resources between distributed edges efficiently. This paper suggests the LODO (linked-object dynamic offloading) algorithm that provides an ideal balance between edges by considering the ready state or running state. LODO algorithm carries out tasks in the list in the order of high correlation between data and tasks through linked objects. Furthermore, dynamic offloading considers the running status of all cooperative terminals and decides to schedule task distribution. That can decrease the average delayed time and average power consumption of terminals. In addition, the resource shortage problem can settle by reducing task processing using its distributions.https://www.mdpi.com/2079-9292/10/17/2156edge computingoffloading computationdistributed collaborationdata processingdynamic offloadingIoT |
| spellingShingle | Svetlana Kim Jieun Kang YongIk Yoon Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment Electronics edge computing offloading computation distributed collaboration data processing dynamic offloading IoT |
| title | Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment |
| title_full | Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment |
| title_fullStr | Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment |
| title_full_unstemmed | Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment |
| title_short | Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment |
| title_sort | linked object dynamic offloading lodo for the cooperation of data and tasks on edge computing environment |
| topic | edge computing offloading computation distributed collaboration data processing dynamic offloading IoT |
| url | https://www.mdpi.com/2079-9292/10/17/2156 |
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