Resources in a cloud can be identified using identifiers based on random numbers. When using a distributed hash table to resolve such identifiers to network locations, the straightforward approach is to store the network location directly in the hash table entry associated with an identifier. When a mobile host contains a large number of resources, this requires that all of the associated hash table entries must be updated when its network address changes. We propose an alternative approach where we store a host identifier in the entry associated with a resource identifier and the actual network address of the host in a separate host entry. This can drastically reduce the time required for updating the distributed hash table when a mobile host changes its network address. We also investigate under which circumstances our approach should or should not be used. We evaluate and confirm the usefulness of our approach with experiments run on top of OpenDHT.
Distributed hash tables, also called peer-to-peer structured overlay networks, are distributed systems which map a uniform distribution of identifiers to nodes in the system @cite_3 @cite_13 @cite_20 . Nodes act as peers, with no node having to play a special role, and a distributed hash table can continue operation even as nodes join or leave the system. Lookups and updates to a distributed hash table are scalable, typically taking time logarithmic to the number of nodes in the system. We experimentally evaluated our work using OpenDHT @cite_12 , which is a public distributed hash table service based on Bamboo @cite_5 .
@cite_3 @cite_5 @cite_13 @cite_12 @cite_20
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Distributed Hash Tables (DHTs) are very efficient distributed systems for routing, but at the same time vulnerable to disruptive nodes. Designers of such systems want them used in open networks, where an adversary can perform a sybil attack by introducing a large number of corrupt nodes in the network, considerably degrading its performance. We introduce a routing strategy that alleviates some of the effects of such an attack by making sure that lookups are performed using a diverse set of nodes. This ensures that at least some of the nodes queried are good, and hence the search makes forward progress. This strategy makes use of latent social information present in the introduction graph of the network. Mobile ad-hoc networks (MANETs) and distributed hash-tables (DHTs) share key characteristics in terms of self organization, decentralization, redundancy requirements, and limited infrastructure. However, node mobility and the continually changing physical topology pose a special challenge to scalability and the design of a DHT for mobile ad-hoc network. The mobile hash-table (MHT) [9] addresses this challenge by mapping a data item to a path through the environment. In contrast to existing DHTs, MHT does not to maintain routing tables and thereby can be used in networks with highly dynamic topologies. Thus, in mobile environments it stores data items with low maintenance overhead on the moving nodes and allows the MHT to scale up to several ten thousands of nodes.This paper addresses the problem of churn in mobile hash tables. Similar to Internet based peer-to-peer systems a deployed mobile hash table suffers from suddenly leaving nodes and the need to recover lost data items. We evaluate how redundancy and recovery technique used in the internet domain can be deployed in the mobile hash table. Furthermore, we show that these redundancy techniques can greatly benefit from the local broadcast properties of typical mobile ad-hoc networks. Distributed hash table (DHT) systems are an important class of peer-to-peer routing infrastructures. They enable scalable wide-area storage and retrieval of information, and will support the rapid development of a wide variety of Internet-scale applications ranging from naming systems and file systems to application-layer multicast. DHT systems essentially build an overlay network, but a path on the overlay between any two nodes can be significantly different from the unicast path between those two nodes on the underlying network. As such, the lookup latency in these systems can be quite high and can adversely impact the performance of applications built on top of such systems.In this paper, we discuss a random sampling technique that incrementally improves lookup latency in DHT systems. Our sampling can be implemented using information gleaned from lookups traversing the overlay network. For this reason, we call our approach lookup-parasitic random sampling (LPRS). LPRS is fast, incurs little network overhead, and requires relatively few modifications to existing DHT systems.For idealized versions of DHT systems like Chord, Tapestry and Pastry, we analytically prove that LPRS can result in lookup latencies proportional to the average unicast latency of the network, provided the underlying physical topology has a power-law latency expansion. We then validate this analysis by implementing LPRS in the Chord simulator. Our simulations reveal that LPRS-Chord exhibits a qualitatively better latency scaling behavior relative to unmodified Chord.Finally, we provide evidence which suggests that the Internet router-level topology resembles power-law latency expansion. This finding implies that LPRS has significant practical applicability as a general latency reduction technique for many DHT systems. This finding is also of independent interest since it might inform the design of latency-sensitive topology models for the Internet. Decentralized systems, such as structured overlays, are subject to the Sybil attack, in which an adversary creates many false identities to increase its influence. This paper describes a one-hop distributed hash table which uses the social links between users to strongly resist the Sybil attack. The social network is assumed to be fast mixing, meaning that a random walk in the honest part of the network quickly approaches the uniform distribution. As in the related SybilLimit system [25], with a social network of n honest nodes and m honest edges, the protocol can tolerate up to o(n log n) attack edges (social links from honest nodes to compromised nodes). The routing tables contain O(√m log m) entries per node and are constructed efficiently by a distributed protocol. This is the first sublinear solution to this problem. Preliminary simulation results are presented to demonstrate the approach's effectiveness.