Paper Survey of DHT Distributed Hash Table

Usages Directory service  Very little amount of information, such as URI, metadata, … Storage  Data, such as files, …  Immutable, just for download Database  Each entry is small, but large amount of entries  Mutable  Special operations for query

Challenges Immutable  Latency  Availability  Query Consistency Mutable  Object Consistency

Latency Query  Different routing architectures Chord, Tapestry, Pastry, Kademlia, Can, …  Recursive, interactive  Proximity Neighbor Route  Parallel  Routing table size Fetch  Transport Protocol  Proximity Neighbor Selections  Cache  Distributed Object

Query: Routing Architectures Routing Complexity  O (log n), O (d), O (1), … Principle  Each peer has a unique digest  Object with a digest  Put the object to the peer with the closed digest Famous ones are O (log n) O (1)  cache

Query: Recursive or Interactive Query is recursive forward  Faster 2 times than interactive theoretically  Primary parameters Base # of successor  Persistent problem

Query: Recursive or Interactive Query is interactively forward  Not very slow in practical  Primary parameters # of parallel query Routing table tree  Learning new neighbor easily  Exchange information with other peers  Flexible

Query: Proximity Neighbor Route Route by a node with smaller delay Small delay -> small timeout  TCP > Vivaldi > fixed

Query: Proximity Neighbor Route Measure methods  Global Sampling  Neighbor’s neighbors  Neighbor’s inverse  Recursive sampling

Query: others Parallel query  Faster  With partial PNS property  Persistent  More traffic Large routing table  Easy to find a closer node locally

Fetch: Cache Cache objects on nodes closer to the primary one # of nodes to cache is upon the popularity of the object Average query hops can be reduced to a constant number ( O (1) ) Hard to apply to mutable object Consider churn  more bandwidth consumption

Fetch: Distributed Object Split object to small pieces and put on different nodes Recover faster Download faster Hard to maintain Only for immutable data

Fetch: Transport Protocol Striped Transport Protocol  UDP  Window control  Retransmission

Availability Replicate  Reactive / Proactive  Eager / lazy repair Erasure coding Load balance is broken  High correlation between uptime and storage Maintenance traffic problem

Availability: Replicate Reactive  Duplicate when a copy is lost  Consume lots of bandwidth in short time  When churn is low, reactive is better Proactive  Duplicate continually  Consume constant and small bandwidth continually  Need avail. prediction and redundancy management  Bandwidth usage is predictable

Availability: Replicate Temporary / Permanent churn Availability Durability Achieve 100% availability or/and durability ? Eager repair Duplicate immediately Lazy repair Duplicate after timeout Need a good choice of timeout Reintegrating returning replicas

Availability: Erasure Coding Matter more on larger object Save storage and bandwidth For high churn, the bandwidth consumption is still not acceptable Complex maintenance Download latency is heterogeneous Only for immutable data

Query Consistency A digest-object mapping is existed, then the result of query must be it Weakly consistent KBR  Eventual consistency  Most of existed DHT Strongly consistent KBR  Causality consistency  Strong consistency Solution  Route by W-KBR to a group  S-KBR in a group

Mutable DHT Object stored in DHT is mutable  Insert, update, delete Churn -> Replica New Challenge …

Object Consistency For immutable data  For security issue, it may be there Merkle tree For mutable data  Consensus algorithm Distributed algorithm for data consistency  Quorum algorithm Read / write locks

Pitfalls Different kinds of p2p have different properties Lack of new real traces Standard simulation platform

References Efficient Replica Maintenance for Distributed Storage Systems Proactive replication for data durability On object Maintenance in Peer-to-Peer systems Enforcing Routing Consistency in Structured Peer-to-peer Overlays: Should We and Could We? High Availability in DHTs: Erasure Coding vs. Replication Toward Fault-tolerant Atomic Data Access in Mutable Distributed Hash Tables Kademlia: A Peer-to-peer Information System Based on the XOR Metric Total Recall: System Support for Automated Availability Management Designing a DHT for low latency and high throughput

References Fallacies in evaluating decentralized systems Anatomy of a P2P Content Distribution system with Network Coding Comparing the performance of distributed hash tables under churn EpiChord: Parallelizing the Chord Lookup Algorithm with Reactive Routing State management Bandwidth-efficient management of DHT routing tables Improving Lookup Performance over a Widely-Deployed DHT Failure Recovery for Structured P2P Networks: Protocol Design and Performance Evaluation Handling Churn in a DHT