Edge-cloud heterogeneity-oriented multi-level transaction scheduling allocation strategy

Abstract

The invention provides an edge-cloud heterogeneity-oriented multi-level transaction scheduling allocation strategy, which comprises the following implementation steps that firstly, information of alltransactions generated at all data sources is collected, and the information of the transactions comprises the data size of the transactions, the size of transaction calculation amount, the size of received data, the data sources, the size of sent data, the data direction and the like; Secondly, arranging the transaction information to form a complete transaction dependency graph, and representingthe complete transaction dependency graph with a directed acyclic graph; And then, whether the transaction is processed at a cloud end or an edge server is judged, the priority of the transaction isjudged by utilizing a reasonable transaction priority heuristic algorithm, and a transaction queue with the priority from high to low is formed. And finally, determining the resource node for executing the transaction according to the load balance, the transaction waiting time, the transaction emergency degree and the resource node power consumption among the resource nodes, and finding out an optimal resource allocation scheme, thereby achieving the purpose of improving the system efficiency.

Description

technical field [0001] The invention belongs to the field of wide-area network architecture, and in particular relates to a multi-level transaction scheduling and allocation strategy for edge-cloud heterogeneity. Background technique [0002] With the continuous development of Internet technology, the era of big data is also coming. At the same time, the rapid development of Internet of Things technology and the promotion of cloud services have made the cloud computing model unable to solve the current problems well. According to the forecast of Cisco Global Cloud Index, by 2019, there will be nearly 50 billion things connected to the Internet in the world, and the total data traffic of global data centers is expected to reach 10.4ZB. In this highly informatized era, the Internet is facing multiple severe challenges: massive data redundancy, cloud processing capacity entering the bottleneck, network bandwidth reaching the upper limit, transaction processing efficiency decre...

AI Technical Summary

Problems solved by technology

However, edge computing also has the following disadvantages: edge computing nodes lack the powerful computing performance of the cloud computing model, and do not have enough resources to deal with complex and huge data sets and computing transactions; the edge computing model is also difficult to be compatible with heterogeneous transactions, that is, It is impossible to integrate a variety of intelligent information processing methods in an edge computing resource node; edge processing reduces the load and power consumption of cloud processing transactions, and at the same time brings load imbalance among edge nodes

To be able to model and simulate scenarios with strategies aimed at optimizing data placement in Fog and IoT contexts, optimize transaction execution time and memory utilization, but the study ignores the interdependencies between transactions

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