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SkipNet: A Scalable Overlay Network with Practical Locality Properties Nicholas J. A. Harvey, Michael B. Jones, Stefan Saroiu, Marvin Theimer, and Alec Wolman Presented by Koji Yatani Problem DHTs cannot control where data is stored. It may be far from the users. It may be outside the administrative domain to which it belongs. SkipNet A scalable overlay network integrating two locality properties Content locality Path locality Content locality The ability to explicitly place data on specific nodes or distribute it across nodes within a given organization Path locality The ability to guarantee that message traffic between two nodes within the same organization is routed within that organization only. Locality Properties of SkipNet Content and routing path locality Content locality: Incorporating a node’s name ID into content name john.microsoft.com/doc-name Routing path locality: Sharing a prefix in the “reversed” name IDs com.microsoft.john com.microsoft.alice com.microsoft.bob Locality Properties of SkipNet Constrained load balancing (CLB) The name of data has two parts. The CLB domain: it specifies the set of nodes over which DHT load balancing should be performed The CLB suffix: it is used as input to the DHT’s hash function Example: msn.com/DataCenter!TopStories.html Experimental Evaluation Basic routing costs Constrained load balancing Network proximity Effect of locality of data placement Fault tolerance SkipNet shows significant performance improvements and great fault tolerance as the locality of data reference increases. Discussions What is the reason why CLB in SkipNet was not so great? Did it hit the theoretical limit? Was there something wrong with the assumptions for the simulation? How could we overcome the problem? Discussions Is there any other good way to evaluate SkipNet (or a P2P system in general)? What kind of evaluations would make our paper stronger? Taxonomy in the paper we looked at last week Decentralization Architecture Lookup Protocol System Parameters Routing Performance Routing State Peers Join and Leave Security Reliability Discussions Is there any other useful guarantee/functionality in a P2P system? Untraceable identities (Winny) Clustering Detection of fake/virus files Anything else? Discussions Could we apply the SkipNet structure to a social networking system? People would belong to many different organizations. The “main” organization might be dynamically changed. Day -> “CS grad students at UofT” Night -> “Residents in Graduate House” Would SkipNet improve the performance of a social networking system? How? Discussions What kind of guarantees/improvements would we need for a social network? We would not want a message to be routed through an unfamiliar/outside node. We would want to connect a node outside the organization more effectively. Discussions Could we explore other enhancements on SkipNet with a social networking? A better way to construct and maintain P-table CLB with a more flexible subset of the network Clustering A collaborative uploading/downloading Thank you. Any other discussion? Distributed Hash Table (DHT) A nodeID is assigned to each node. Data is placed deterministically with an identifier called key which is determined by a hash function. Each peer maintains information on its neighborhood nodeIDs and IP addresses. Queries are forwarded so that it can get closer to the key in the identifier space. Theoretically, a DHT-based system can guarantee that any date can be located in O(logN) hops. DHT Disadvantage: the system cannot know where the desired data is. It may be far from the users. It may be outside the administrative domain to which it belongs. Routing over SkipNet Analogy to Skip List A sorted linked list in which some nodes are supplemented with pointers that skip over many list elements Routing over SkipNet Skip List A perfect Skip List: The height of a i-th node can be determined as the exponent of the largest power-oftwo that divides i. A probabilistic Skip List: The height of each node can be chosen with the probability with (½)^h. The SkipNet Structure D M O A T Z R-table V X Level Clockwise Anti-clockwise Level Clockwise Anti-clockwise 2 T T 2 D D 1 M X 1 Z O 0 D Z 0 X T The SkipNet Structure Numeric ID Its first h bits determine ring membership. M D 110 010 O 101 A 000 001 100 Z 011 X 111 V T The SkipNet Structure Routing by Numeric ID Node A wants to send a message to node 1011. M D 1100 0100 O 1001 A 0000 0001 1000 Z 0101 X 1101 V T Locality Properties of SkipNet Limitation of CLB in the SkipNet It does not support load balancing over an arbitrary subset of the nodes. Only over any naming subtree of the SkipNet Transparent remapping to a different load balancing domain is not possible. The CLB domain is encoded in the name of a data object. SkipNet Enhancement Sparse and dense routing table Using non-binary digits for the numeric IDs Decreasing the total number of pointers in the R-table Increasing the routing hops to a specific node SkipNet Enhancement Network proximity The problem: A message my be routed through a node which is located at a distant place. USA UK aaa.com/nodeA bbb.com/nodeB ccc.com/nodeC SkipNet Enhancement Network proximity The second routing table: P-table Inspired by Pastry’s proximity-aware routing tables Experimental Evaluation Relative Delay Penalty (RDP): The ratio of the latency of the overlay network path between to two nodes to the latency of the IP-level path between them. Basic routing costs Constrained load balancing Network proximity Physical network hops Effect of locality of data placement Numbers of failed lookups Fault tolerance Experimental Evaluation Basic routing costs Basic SkipNet and Chord: do not support proximity- aware rooting Full SkipNet and Pastry: do support proximity-aware rooting Experimental Evaluation Absolute latency for lookups as a function of data access locality SkipNet was not so great here. Inter-domain links had the same cost as intra-domain links. Experimental Evaluation Fault tolerance SkipNet showed a great fault tolerance. Locality Properties of SkipNet Constrained load balancing SkipNet was not so great again… why? Is there any good way to evaluate the performance of CLB? Experimental Evaluation Network proximity Density parameter k: controls the density of P-table pointers. Choosing k=8 provides a good performance with a reasonable number of pointers.