📝 Trackerless BitTorrent DHT based (10 MCQs)
📖 From Data Communication and Networks • 29. Peer to Peer Paradigm • 10 questions available
What is Trackerless BitTorrent DHT based?
Trackerless BitTorrent uses a Distributed Hash Table to decentralize peer discovery, allowing clients to find each other and coordinate file sharing without relying on a central tracker, making the system more resilient and censorship-resistant.
📝 All Trackerless BitTorrent DHT based MCQs
Q1. In trackerless BitTorrent, what does the abbreviation DHT stand for?
📖 Explanation: The term DHT in a trackerless BitTorrent system refers to a Distributed Hash Table. It is a decentralized data structure that maps keys to values across participating peers, enabling lookup of torrent metadata without a central tracker. Understanding this definition is essential for grasping the core mechanism of trackerless operation.
Q2. If a peer receives a list of node IDs that are all behind symmetric NATs, what is the most likely impact on its ability to establish direct connections?
📖 Explanation: Symmetric NATs assign a unique external port for each destination, preventing predictable hole‑punching. When every candidate node is behind such NATs, the peer cannot predict a reachable address, so direct connections usually fail unless a relay (e.g., TURN) is used. This inference explains why the peer’s connectivity degrades dramatically.
Q3. Compared with a traditional centralized tracker, which statement best describes the scalability of a DHT‑based system?
📖 Explanation: A DHT distributes responsibility for storing and locating torrent metadata across all peers, so as more users join, the storage and lookup load is shared. This decentralized design avoids a single bottleneck, allowing the system to handle larger swarms more efficiently than a single tracker, which would become a performance choke point.
Q4. Which modification to the Kademlia XOR distance metric would most improve lookup efficiency in a highly churned swarm?
📖 Explanation: In a churn‑heavy environment, nodes that have been online longer are more reliable for routing queries. By incorporating recent uptime as a weight in the XOR distance calculation, the algorithm preferentially selects stable peers, reducing failed lookups and speeding up the overall discovery process.
Q5. Regarding NAT traversal, which statement is most accurate?
📖 Explanation: Hole punching relies on both ends being behind NATs that support predictable port mapping (e.g., full‑cone or restricted‑cone). When either side uses a symmetric NAT, the technique often fails, making it essential to recognize that successful direct connections depend on NAT compatibility.
Q6. What is a primary security implication of enabling Peer Exchange (PEX) in a trackerless swarm?
📖 Explanation: PEX allows peers to share lists of other peers, which can be exploited by an adversary to inject malicious nodes into the network. By controlling the peer list, an attacker can surround a target with compromised peers (an eclipse attack), making the correct answer the increased vulnerability.
Q7. Combining DHT with Peer Exchange (PEX) primarily aims to:
📖 Explanation: When DHT provides a decentralized lookup and PEX shares additional peer information, the combined effect can obscure the source of a peer’s discovery, making it harder for an observer to trace who introduced whom. This synergy enhances the anonymity of participants beyond what either mechanism offers alone.
Q8. If a malicious node injects false IP addresses into the DHT, what is the most likely immediate consequence for other peers?
📖 Explanation: Incorrect entries cause lookup queries to be routed toward bogus addresses, leading peers to waste time attempting connections that never succeed. This misdirection can degrade overall swarm performance and may facilitate targeted attacks, illustrating the direct impact of falsified routing information.
Q9. Which distinction best characterizes iterative versus recursive lookup in a Kademlia‑style DHT?
📖 Explanation: All Kademlia implementations use XOR distance to choose the next hop. The key difference lies in who forwards the query: iterative lookups have the requester contact each successive node, while recursive lookups let each node forward the request onward. This structural variance influences performance and resilience.
Q10. In a trackerless swarm, the probability that a newly joining peer discovers at least one seed within its first five DHT queries is best modeled by which distribution?
📖 Explanation: The discovery of rare events—such as finding a seed among many possible nodes—fits a Poisson model, where the expected number of successes in a fixed number of independent queries determines the probability. This statistical approach captures the random nature of early DHT lookups in a large peer population.