计算机科学 ›› 2023, Vol. 50 ›› Issue (4): 241-248.doi: 10.11896/jsjkx.211200194
裴翠1, 范贵生1,2, 虞慧群1, 岳一鸣1
PEI Cui1, FAN Guisheng1,2, YU Huiqun1, YUE Yiming1
摘要: 随着万物互联和5G时代的到来,移动用户需要处理的数据量与其处理数据能力不匹配。将大量任务卸载到有限的边缘服务器上执行势必会产生竞争,拍卖模型的引入可以解决用户之间对资源的竞争问题。目前大多基于拍卖的任务卸载工作忽略了任务的期限感知,普遍的任务卸载工作只单一考虑延迟敏感任务,并且未考虑到保证卸载过程的安全性。基于此,提出了一种基于拍卖的期限感知任务卸载(Auction Based Deadline-aware Task Offloading,ABDTO)策略,利用基于智能合约的拍卖机制实现期限感知任务(延迟敏感型任务和非延迟敏感型任务)到边缘服务器的最优分配,以总效用(即总利润)作为评价标准,实现移动用户和边缘服务器的共赢。利用启发式遗传算法进行仿真实验,相比TACD,UPPER和RND算法,ABDTO策略的整体效用更高,最后利用Remix和Ganache等建立以太坊私有区块链网络进行仿真,证明了所提策略的正确性和可行性。
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