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📝 Traffic conditioners in DiffServ (12 MCQs)

📖 From Data Communication and Networks • 30. Quality of Service • 12 questions available

What is Traffic conditioners in DiffServ?

Traffic conditioners are edge devices in DiffServ networks that measure incoming traffic against service profiles and then mark, shape, police, or drop packets to ensure they conform to the agreed-upon behavior before entering the differentiated services domain.

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Easy
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Medium
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Hard

📝 All Traffic conditioners in DiffServ MCQs

Q1. How many primary color channels are used in a standard RGB color image?

A.One
B.Two
C.Three ✅
D.Four
💡 Difficulty: easy | ✅ Correct: C

📖 Explanation: An RGB image is built from three independent channels—red, green, and blue. Each channel carries intensity information for its respective primary color, so the image consists of exactly three channels. Therefore the correct answer is the option indicating three channels.

Q2. If a traffic conditioner reduces jitter by smoothing packet inter‑arrival times, what is the most likely effect on real‑time video quality?

A.Increase in latency
B.Reduction in buffering ✅
C.Higher frame drops
D.Lower resolution
💡 Difficulty: medium | ✅ Correct: B

📖 Explanation: Smoothing jitter creates more regular packet spacing, which helps the video decoder maintain a steady buffer. With fewer sudden spikes, the player can pre‑fetch data efficiently, reducing the need for large buffers and thus lowering buffering events. Consequently, viewers experience smoother playback with fewer interruptions.

Q3. Compare a token‑bucket traffic conditioner with a leaky‑bucket conditioner. Which statement best captures their difference in handling bursty traffic?

A.Token‑bucket permits bursts while leaky‑bucket smooths traffic ✅
B.Leaky‑bucket permits bursts while token‑bucket smooths traffic
C.Both behave identically
D.Neither handles bursts
💡 Difficulty: medium | ✅ Correct: A

📖 Explanation: A token‑bucket allows short bursts up to a defined token count before enforcing the average rate, making it tolerant of temporary spikes. In contrast, a leaky‑bucket releases packets at a constant rate, smoothing out bursts and preventing sudden surges. Hence the token‑bucket’s burst‑friendly nature distinguishes it from the leaky‑bucket’s smoothing behavior.

Q4. Given that each RGB channel has 56 intensity levels, what is the total number of bits required per pixel?

A.12 bits
B.16 bits
C.18 bits ✅
D.24 bits
💡 Difficulty: easy | ✅ Correct: C

📖 Explanation: 56 levels require log256=6\lceil\log_2 56\rceil = 6 bits per channel because 25=32<5626=642^5=32 < 56 \le 2^6=64. With three channels (R,G,B), the pixel needs 3×6=183 \times 6 = 18 bits. Therefore the correct answer is the option stating 18 bits per pixel.

Q5. A network engineer observes that after enabling a traffic conditioner, end‑to‑end latency increased slightly but packet loss decreased. What logical inference best explains this outcome?

A.The conditioner adds buffering, raising latency ✅
B.It drops packets, lowering loss
C.It compresses data, affecting latency
D.It expands bandwidth
💡 Difficulty: hard | ✅ Correct: A

📖 Explanation: Traffic conditioners often employ buffers to smooth traffic, which introduces a modest delay (added latency). By queuing packets instead of discarding them, the device reduces the likelihood of loss during congestion. Hence the observed increase in latency accompanied by a decrease in packet loss aligns with the buffering inference.

Q6. Evaluate the impact of raising the number of intensity levels per channel from 56 to 128 on the required storage for a 1920×1080 image. Which statement is most accurate?

A.Storage unchanged
B.Storage increases by ~8%
C.Storage doubles
D.Storage increases by ~17% ✅
💡 Difficulty: hard | ✅ Correct: D

📖 Explanation: 56 levels need 6 bits per channel; 128 levels need 7 bits. The per‑pixel bit count grows from 3×6=183 \times 6 = 18 to 3×7=213 \times 7 = 21 bits, a 2118=1.1667\frac{21}{18}=1.1667 factor, i.e., about a 16.7 % increase. Thus storage rises by roughly 17 %.

Q7. Synthesize how the bit depth per pixel influences both image quality and transmission bandwidth in a streaming scenario. Which relationship correctly describes this?

A.Higher bit depth improves quality but reduces bandwidth
B.Higher bit depth improves quality and increases bandwidth ✅
C.Higher bit depth degrades quality
D.Bit depth unrelated
💡 Difficulty: hard | ✅ Correct: B

📖 Explanation: Increasing bit depth adds more color precision, enhancing perceived image quality. However, each pixel now carries more bits, so the data volume per frame grows, demanding higher transmission bandwidth to maintain the same frame rate. Therefore higher bit depth simultaneously raises quality and bandwidth requirements.

Q8. What is the immediate cause when a traffic conditioner introduces a fixed delay to outgoing packets?

A.Increased jitter
B.Added latency ✅
C.Reduced throughput
D.Packet duplication
💡 Difficulty: easy | ✅ Correct: B

📖 Explanation: A fixed delay means each packet is held for a predetermined time before transmission. This holding period directly adds to the round‑trip time experienced by the packet, manifesting as additional latency. The delay does not inherently change jitter, throughput, or cause duplication, making added latency the correct cause.

Q9. Differentiate traffic shaping from traffic policing. Which pair correctly matches the technique with its typical enforcement action?

A.Shaping drops excess packets; policing buffers them
B.Shaping buffers; policing drops excess packets
C.Shaping buffers and delays; policing drops excess packets ✅
D.Shaping drops; policing delays
💡 Difficulty: medium | ✅ Correct: C

📖 Explanation: Traffic shaping smooths bursts by temporarily storing packets in a buffer and releasing them at the configured rate, thus delaying traffic. Traffic policing, on the other hand, enforces a rate limit by discarding packets that exceed the allowed threshold. Hence the correct pairing is shaping buffers and delays, policing drops excess packets.

Q10. Apply the formula DataRate=Bits per pixel×Pixels per frame×Frames per second8\text{DataRate} = \frac{\text{Bits per pixel} \times \text{Pixels per frame} \times \text{Frames per second}}{8} to a 10‑fps video with 18‑bit pixels at 640×480 resolution. What is the approximate data rate in megabytes per second?

A.5.5 MB/s
B.6.6 MB/s ✅
C.7.7 MB/s
D.8.8 MB/s
💡 Difficulty: medium | ✅ Correct: B

📖 Explanation: Pixels per frame = 640×480=307,200640 \times 480 = 307{,}200. Bits per frame = 18×307,200=5,529,60018 \times 307{,}200 = 5{,}529{,}600 bits. At 10 fps, bits per second = 5,529,600×10=55,296,0005{,}529{,}600 \times 10 = 55{,}296{,}000. Dividing by 8 yields 6,912,0006{,}912{,}000 bytes/s ≈ 6.6 MB/s. Therefore the correct answer is 6.6 MB/s.

Q11. If a traffic conditioner is misconfigured to allow unlimited burst size, what is the most probable consequence on network congestion?

A.Reduced jitter
B.Increased latency spikes
C.Lower throughput
D.Higher packet loss ✅
💡 Difficulty: medium | ✅ Correct: D

📖 Explanation: Allowing unlimited bursts lets large groups of packets arrive simultaneously, overwhelming downstream buffers and links. This sudden surge can cause queue overflows, leading to packet drops. While latency may also increase, the most direct symptom of congestion under such a misconfiguration is an elevated packet‑loss rate.

Q12. Analyze the trade‑off between increasing the bit depth from 6 bits to 8 bits per channel and the resulting file size for a 100‑MB image collection. Which outcome is most plausible?

A.File size unchanged
B.Size increases by ~33% ✅
C.Size doubles
D.Size decreases
💡 Difficulty: easy | ✅ Correct: B

📖 Explanation: Moving from 6 bits to 8 bits per channel raises the per‑pixel bit count from 3×6=183 \times 6 = 18 bits to 3×8=243 \times 8 = 24 bits, a factor of 24/18=4/324/18 = 4/3. Consequently, the total data volume grows by about one‑third, meaning the collection’s size would increase roughly 33 % over the original 100 MB.

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