34 Questions
What is the main advantage of using edge nodes in a cloud-edge environment?
They offer low-latency, high-bandwidth services to users
Which of the following is NOT a common resource allocation technique in a collaborative cloud-edge environment?
Data replication
In a multi-edge-node scenario, what challenge arises in resource allocation?
The cloud and edge nodes must coordinate effectively
What factor does NOT influence cloud resource allocation strategies?
User location
What is a unique characteristic of a public cloud environment?
It offers different pricing modes for cloud services
Which of the following is NOT a benefit of using machine learning algorithms in a collaborative cloud-edge approach?
They can increase system complexity
What type of cloud is dedicated to a single organization?
Private cloud
In the user-edge-cloud model, where are resources allocated?
User devices, edge nodes, and cloud servers
What is the focus of collaborative cloud-edge approaches?
Optimizing system performance
Which type of cloud is shared by multiple organizations?
Public cloud
What does EL tailored to specific use cases allow for?
Evolve over time based on user demand and network conditions
Why are collaborative cloud-edge approaches considered more effective?
Better performance and efficiency
What method is used to obtain the value of ω in the context described?
Minimizing mean square error by gradient descent
In the context provided, what refers to the parameters of the value network and deterministic policy network at step t?
ωt and θt
What does yt represent in the given context?
Next state after taking a mixed action
What does the loss function of the value network aim to minimize?
Mean square error
What information does the input to the Cost-Efficient Resource Allocation algorithm contain?
User requests demands and spot instance unit cost in public cloud
What does the edge node first need to obtain at the beginning of each iteration in the context provided?
The state of the collaborative cloud-edge environment (st)
In P-DQN, what is the goal of finding the corresponding parameters θ when ω is fixed?
To estimate the parameter value xk(s)
What is the primary function of the determined policy network xk(·; θ): S → X k in P-DQN?
To estimate the parameter value xk(s)
What is the role of the neural network parameter ω in P-DQN?
To estimate the parameter value xk(s)
What does Q (s, k, xk) represent in P-DQN?
The target Q value estimation
Which component is used in P-DQN to estimate Q (s, k, xk) and find the corresponding parameters?
Deep neural network Q (s, k, xk; ω)
What does P-DQN aim to estimate through the determined policy network xk(·; θ): S → X k?
The parameter value xk(s)
At time slot (t = 1), how many VMs were allocated from the edge node?
12
What is the cost at the private cloud at time slot (t = 2)?
$26.97
How many VMs were available at the edge node at time slot (t = 2)?
59
What is the number of VMs waiting to be released at time slot (t = 2)?
21
How many VMs were allocated from the edge node at time slot (t = 3)?
4
What is the total cost at the public cloud at time slot (t = 3)?
$51.08
How many VMs were allocated from the cloud at time slot (t = 1)?
12
What is the cost at the edge node at time slot (t = 2)?
$5.97
How many VMs were remaining at the edge node at time slot (t = 3)?
76
What is the updated Allocation Record List H after time slot (t = 2)?
< h" , h& > : < 18, 1 , (3, 0) >
Learn about how collaborative cloud-edge approaches can enhance performance and efficiency in comparison to traditional cloud or edge methods. This lecture delves into tailoring edge learning to specific use cases and its evolution over time based on user demand and network conditions.
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