Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and\nsmart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart\ndevices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might\nbe lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for\ndelay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend\ncloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT\nservice delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm\nthat is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for\nmanaging and delegating user request in order to balance workload.Moreover, we propose algorithm to allocate resources to meet\nservice level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing.\nOur simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently,\noptimize big data distribution, and show better performance than other existing methods.
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