Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li
{"title":"联合计算卸载和资源优化,最大限度降低超密集 MEC 网络的全网能耗","authors":"Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li","doi":"10.1109/JSYST.2024.3391811","DOIUrl":null,"url":null,"abstract":"In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1115-1126"},"PeriodicalIF":4.0000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint Computation Offloading and Resource Optimization for Minimizing Network-Wide Energy Consumption in Ultradense MEC Networks\",\"authors\":\"Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li\",\"doi\":\"10.1109/JSYST.2024.3391811\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.\",\"PeriodicalId\":55017,\"journal\":{\"name\":\"IEEE Systems Journal\",\"volume\":\"18 2\",\"pages\":\"1115-1126\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Systems Journal\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10509708/\",\"RegionNum\":3,\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Systems Journal","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10509708/","RegionNum":3,"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}
Joint Computation Offloading and Resource Optimization for Minimizing Network-Wide Energy Consumption in Ultradense MEC Networks
In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.
期刊介绍:
This publication provides a systems-level, focused forum for application-oriented manuscripts that address complex systems and system-of-systems of national and global significance. It intends to encourage and facilitate cooperation and interaction among IEEE Societies with systems-level and systems engineering interest, and to attract non-IEEE contributors and readers from around the globe. Our IEEE Systems Council job is to address issues in new ways that are not solvable in the domains of the existing IEEE or other societies or global organizations. These problems do not fit within traditional hierarchical boundaries. For example, disaster response such as that triggered by Hurricane Katrina, tsunamis, or current volcanic eruptions is not solvable by pure engineering solutions. We need to think about changing and enlarging the paradigm to include systems issues.