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The text states that additive increase is a necessary condition for a congestioncontrol mechanism to be stable. Outline a specific instability that might arise if all increases were exponential; that is, if TCP continued to use "slow" start after CongestionWindow increased beyond CongestionThreshold.

Short Answer

Expert verified
Exponential increase beyond the CongestionThreshold can overload the network, causing packet loss and congestion collapse.

Step by step solution

01

Understanding Additive Increase

Additive increase in congestion control means that the congestion window increases linearly over time, typically by one segment each round-trip time (RTT). This ensures a controlled increase in network traffic.
02

Understanding Exponential Increase

Exponential increase, such as used in TCP’s slow start phase, doubles the congestion window each RTT. This rapid growth means the window size can increase very quickly.
03

Importance of Stability

Stability in congestion control prevents abrupt changes in network traffic. Gradual increase ensures that the network does not become overloaded suddenly, which could lead to packet loss and reduced performance.
04

Instability with Exponential Increase

If the congestion window continued to increase exponentially beyond the CongestionThreshold, the network could rapidly become overwhelmed. This would lead to congestion collapse, where the network throughput decreases drastically as more packets are dropped or delayed.
05

Example Scenario

Imagine a network where the CongestionWindow is 20 and the CongestionThreshold is 15. If exponential increase is applied, the window might double from 20 to 40 in a single RTT, overwhelming the network and causing significant packet loss.
06

Impact on Network

This rapid increase could result in many packets being dropped, leading to retransmissions and possibly a drastic decrease in the effective throughput. The network would experience instability and poor performance.
07

Conclusion

Thus, continued exponential increase can cause instability by overloading the network, leading to significant packet loss and congestion collapse.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Additive Increase
Additive increase is fundamental in network congestion control. It means that the congestion window size increases by a fixed amount each round-trip time (RTT).
Typically, this increase is one packet per RTT.

The main advantage of additive increase is that it provides a controlled and gradual growth in the amount of data flowing through the network.

For example, if a network starts with a congestion window (CW) of 10 segments, with additive increase, it will be 11 in one RTT, 12 in the next, and so on.
This gradual approach ensures the network remains stable and doesn't get overwhelmed suddenly, avoiding packet loss and congestion.

Exponential Increase
Exponential increase in network congestion control, as seen in TCP's slow start phase, means the congestion window doubles every RTT.
This is useful for quickly utilizing available bandwidth when a connection starts, as it establishes the capacity of the network.

For instance, if the congestion window starts at 1 segment, in the next RTT it will be 2 segments, then 4, 8, and so on.

However, this rapid growth also has risks. If exponential increase continues beyond a certain point, it can lead to instability.
The network may become overloaded, causing packet loss and significant delays.
This rapid, unchecked growth is why exponential increase is usually limited to the initial phase of a connection.
After a certain threshold, a more controlled growth method, such as additive increase, is preferred.

Stability in Network Traffic
Stability in network traffic ensures smooth and efficient data flow.
It means avoiding sudden spikes or drops in the amount of data sent.

Stable traffic helps prevent congestion and packet loss, leading to better network performance.

One way to maintain stability is through the method of additive increase.
This steady, predictable growth allows networks to adjust to increasing loads without becoming overwhelmed.
Stability is crucial in avoiding congestion collapse, where network performance degrades drastically.
Ensuring gradual growth in data transmission helps maintain reliable and consistent network speeds.

Congestion Collapse
Congestion collapse occurs when network performance significantly decreases due to excessive packet loss.
This happens when the network is overloaded with too many packets at once.

For example, if the congestion window increases too rapidly through exponential growth, the network may become saturated.
The result is many packets being delayed or dropped, which leads to retransmissions.
Retransmissions further burden the network, creating a feedback loop of congestion.

This feedback loop can drastically reduce the effective throughput of the network, causing severe performance issues.
Congestion collapse highlights the importance of controlled growth strategies like additive increase after the initial exponential phase to prevent such scenarios.

TCP Slow Start
TCP Slow Start is a mechanism used to control the amount of data sent over a network connection.
When a TCP connection starts, the congestion window size is small.
This window size doubles each RTT (i.e., exponential increase) to quickly take advantage of available bandwidth.

However, this phase is only temporary.
Once the congestion window reaches a certain threshold, known as the CongestionThreshold, the growth method switches to additive increase.
This transition helps maintain stability in network traffic and prevents congestion collapse.

The purpose of slow start is to find the optimal transmission rate for the network early in the connection, but without risking sudden overload.
It balances rapid initial growth with the need to avoid excessive congestion.

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Most popular questions from this chapter

Suppose a router's drop policy is to drop the highest-cost packet whenever queues are full, where it defines the "cost" of a packet to be the product of its size by the time remaining that it will spend in the queue. (Note that in calculating cost it is equivalent to use the sum of the sizes of the earlier packets in lieu of remaining time.) (a) What advantages and disadvantages might such a policy offer, compared to tail drop? (b) Give an example of a sequence of queued packets for which dropping the highest-cost packet differs from dropping the largest packet. (c) Give an example where two packets exchange their relative cost ranks as time progresses.

Suppose you are downloading a large file over a 3-KBps phone link. Your software displays an average-bytes-per-second counter. How will TCP congestion control and occasional packet losses cause this counter to fluctuate? Assume that only a third, say, of the total RTT is spent on the phone link.

Consider a simple congestion-control algorithm that uses linear increase and multiplicative decrease but not slow start, that works in units of packets rather than bytes, and that starts each connection with a congestion window equal to one packet. Give a detailed sketch of this algorithm. Assume the delay is latency only, and that when a group of packets is sent, only a single ACK is returned. Plot the congestion window as a function of round-trip times for the situation in which the following packets are lost: \(9,25,30,38\), and 50 . For simplicity, assume a perfect timeout mechanism that detects a lost packet exactly 1 RTT after it is transmitted.

Assume that TCP implements an extension that allows window sizes much larger than \(64 \mathrm{~KB}\). Suppose that you are using this extended TCP over a 1-Gbps link with a latency of \(100 \mathrm{~ms}\) to transfer a \(10-\mathrm{MB}\) file, and the TCP receive window is \(1 \mathrm{MB}\). If TCP sends 1-KB packets (assuming no congestion and no lost packets): (a) How many RTTs does it take until slow start opens the send window to \(1 \mathrm{MB}\) ? (b) How many RTTs does it take to send the file? (c) If the time to send the file is given by the number of required RTTs multiplied by the link latency, what is the effective throughput for the transfer? What percentage of the link bandwidth is utilized?

Suppose a TCP connection has a window size of eight segments, an RTT of \(800 \mathrm{~ms}\), the sender sends segments at a regular rate of one every \(100 \mathrm{~ms}\), and the receiver sends ACKs back at the same rate without delay. A segment is lost, and the loss is detected by the fast retransmit algorithm on the receipt of the third duplicate \(\mathrm{ACK}\). At the point when the ACK of the retransmitted segment finally arrives, how much total time has the sender lost (compared to lossless transmission) if (a) the sender waits for the ACK from the retransmitted lost packet before sliding the window forward again? (b) the sender uses the continued arrival of each duplicate ACK as an indication it may slide the window forward one segment?

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