摘要(英) |
Along with the appearances of various IoT services, original centralized Cloud Computing hasn’t been able to satisfy every kinds of demands. For solving this problem, the new type of cloud computing structure -Edge Computing is presented. Its main concept is that setting up the computing server on edge network (especially base station) instead of centralized computing server in cloud center on backbone network, and utilizing the characteristic closing to UE to reduce the transmission delay and the load on backbone network.
Comparing with traditional cloud computing with edge computing, the computing capacity of edge computing server is not powerful enough. Moreover, the number of mobile devices keep increasing, expecting that the edge computing system can accepts all offload requests of computing tasks is unrealistic. In fact, many devices have own small computing capacity so the edge computing system should be able to reject the offload requests of non-essential tasks. As noted above, the way how to achieve most efficient task-offloading decision and resource allocation is a popular research topic in this field.
In this thesis, we propose Load-Adaptive Algorithm of Joint Resource Allocation(LAJRA) for adaptive load of edge computing system. The algorithm can reserve resources for the essential/critical tasks while the high system load, and it can also accept some offload requests of non-essential tasks for reducing the waste of resource while the low system load. Because the edge computing server is set up in base station, we integrate specially upload bandwidth and computing resource allocation in this algorithm to expect it will be more suitable in practice comparing with other methods. |
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