{"title":"Breakout Local Search Solution to the Offloading Decision Problem in a Multi-Access Edge Computing Cloud-Enabled Network","authors":"Mina Kato;Tiago Koketsu Rodrigues;Nei Kato","doi":"10.1109/TETC.2025.3598369","DOIUrl":null,"url":null,"abstract":"Cloud offloading is an important technique for Internet of Things systems, as it allows devices with limited capabilities to access the powerful resources in the cloud when executing their applications. However, relying solely on the remote cloud is problematic, as the long access time from the far distance to the server makes real-time applications impossible to be executed. Multi-access edge computing addresses this by deploying cloud servers near the devices. The issue then becomes how to allocate devices between either remote cloud and multi-access edge computing, based on the device requirements. In this paper, we propose a Breakout Local Search-based solution that, given our designed binary integer linear programming model of the offloading problem, finds a near-optimal configuration for allocating devices between the two cloud types. The proposal is based on iterating between exploiting the local optimum found so far and perturbation of the current solution to explore more the search space. A comparison study shows that our proposal is better than baseline and conventional algorithms, speeding up the total service delay of tasks by at least 30 ms.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"13 3","pages":"1328-1338"},"PeriodicalIF":5.4000,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Emerging Topics in Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11130662/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Cloud offloading is an important technique for Internet of Things systems, as it allows devices with limited capabilities to access the powerful resources in the cloud when executing their applications. However, relying solely on the remote cloud is problematic, as the long access time from the far distance to the server makes real-time applications impossible to be executed. Multi-access edge computing addresses this by deploying cloud servers near the devices. The issue then becomes how to allocate devices between either remote cloud and multi-access edge computing, based on the device requirements. In this paper, we propose a Breakout Local Search-based solution that, given our designed binary integer linear programming model of the offloading problem, finds a near-optimal configuration for allocating devices between the two cloud types. The proposal is based on iterating between exploiting the local optimum found so far and perturbation of the current solution to explore more the search space. A comparison study shows that our proposal is better than baseline and conventional algorithms, speeding up the total service delay of tasks by at least 30 ms.
期刊介绍:
IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.