摘要:
随着物联网、4G/5G无线网络技术的发展和普及应用,万物互联已成为现实.移动计算、智能手机、Pad和可穿戴等智能终端设备大量接入使网络边缘设备数量迅速增加，边缘设备所产生的数据呈指数增长.边缘计算面临大吞吐量、频繁交互、位置和延迟敏感等特征的实时业务服务需求挑战.充分发挥边缘计算节点智能、多样和灵活等特点，通过局部汇聚计算、存储、网络服务等共享方式实现边缘计算资源快速融合，构建可信协同服务系统是保障边缘计算QoS的一种有效方法.为了快速发现、动态组织、自主融合边缘节点进行协同服务，提出一种基于盟主的边缘计算协同服务(trust cooperative services for edge computing, TCSEC)模型.该模型基于信任度、影响力、容量、带宽、链路质量等表征节点特征属性，以任务驱动方式，由盟主节点根据策略和边缘节点的特征属性选择协同服务节点集，实现资源快速融合与计算迁移，为计算请求节点提供及时响应和可靠服务.仿真实验表明：TCSEC能有效提高边缘计算协同服务能力和服务质量.
Abstract:
With the development and widespread application of the Internet of things and 4G/5G wireless network technology, we have entered into the Internet of everything era. It is easier to connect the edge computing devices, such as mobile phones, PAD, etc., to the Internet. Thus, the number of data generated by edge computing devices is increasing significantly. However, the current network services cannot provide such demand, posed by edge computing, on high throughput, frequently connection, sensitive to location and latency. It is an efficient way to improve the quality of service by 1)considering the characteristics of the intelligence, diversity and flexibility of node at the edge of network, 2)locally aggregating computing, storage and network service resources, and 3)adaptively building trusted cooperative service system. The key to efficiently build a cooperative service system is quickly looking for and then dynamically organizing the edge computing nodes. In this paper, we propose a leaderbased trusted cooperative service for edge computing (TCSEC). The main idea is the leader node selects its cooperative service node set with a selfadjustable clustering, which takes into consideration the features of a node, e.g. trust degree, influence, volume, bandwidth, and quality of the link, and realizes the rapid resource aggregation and computing migration. Based on our approach, it is fast to respond to the computing request and provide reliable service. The simulation shows TCSEC can efficiently speed up the ability to construct a cooperative service system and improve the quality of service.
百度学术
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