LDHT: Locality-aware Distributed Hash Tables

Wu, Wei; Chen, Yang; Zhang, Xinyi; Shi, Xiaohui; LinCong,; Deng, Bangming; Li, Xing

doi:10.1109/icoin.2008.4472811

Cited by 28 publications

(16 citation statements)

References 4 publications

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“…For instance, Zhao et al proposed Tapestry [22], a DHT in which the time to reach a key is proportional to the distance to reach the node storing the key. The same idea was used by Wu et al [25], Rowstron et al [20] or by Locher et al [23]. Yalagandula et al [21] point out that routing locality is not sufficient, and they propose a DHT providing path convergence.…”

Section: B Handling Churnmentioning

confidence: 99%

Data Location Management Protocol for Object Stores in a Fog Computing Infrastructure

Confais

Parrein

Lèbre

2019

IEEE Trans. Netw. Serv. Manage.

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Fog Computing infrastructures have been proposed as an alternative to Cloud Computing to provide low latency computing for the Internet of Things (IoT). But no storage solutions have been proposed to work specifically in this environment. Existing solutions, relying on a distributed hash table to locate the data, are not efficient because location record may be placed far away from the object replicas. In this paper, we propose to use a tree-based approach to locate the data, inspired by the Domain Name System (DNS) protocol. In our protocol, servers look for the location of an object by requesting successively their ancestors in a tree built with a modified version of the Dijkstra's algorithm applied to the physical topology. Location records are replicated close to the object replicas to limit the network traffic when requesting an object. We evaluate our approach on the Grid'5000 testbed using micro experiments with simple network topologies and a macro experiment using the topology of the French National Research and Education Network (RENATER). In this macro benchmark, we show that the time to locate an object in our approach is less than 15 ms on average which is around 20% shorter than using a traditional Distributed Hash Table (DHT).

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Section: B Handling Churnmentioning

confidence: 99%

Data Location Management Protocol for Object Stores in a Fog Computing Infrastructure

Confais

Parrein

Lèbre

2019

IEEE Trans. Netw. Serv. Manage.

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“…However, the lookup traffic matrix is unknown and hard to estimate in practice. To decrease resolution latencies, several DHT systems such as LDHT [38], and LChord [16] construct locality-aware overlay network using hierarchical identifiers. This is not consistent with our goals.…”

Section: Related Workmentioning

confidence: 99%

Towards locality-aware DHT for fast mapping service in future Internet

Wang

Lan

et al. 2015

Computer Communications

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“…These related searches [9][10][11][12][13][14][15][16][17][18][19][20] can be classified into three categories according what the locality information of nodes are used. The first class [9][10][11][12][13][14] is based on some selected land marks.…”

Section: Introductionmentioning

confidence: 99%

“…• AS{lPS)-based methods [15][16][17]: The nodes's locality can not be distinguished in an AS (or ISP) which may contains a large number of nodes, even over 10000 nodes [21].…”

Section: Introductionmentioning

confidence: 99%

“…The locality of nodes play an important role to solve the consistent problem. Many researches [9][10][11][12][13][14][15][16][17][18][19][20] make efforts to improve the searching latency by building topology aware overlay networks with the assistance of nodes's locality. But some disadvantages described above still exist due to the lack of more precise locality information of nodes.…”

Section: Introductionmentioning

confidence: 99%

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Network locality positioning system in P2P networks

Wang

2010

2010 Second International Conference on Ubiquitous and Future Networks (ICUFN)

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In this paper, we propose a network locality po sitioning system (NLPS) to provide precise locality information of nodes in networks instead of designing new P2P systems. It can not only be used to solve the consistent problem whatever the P2P systems are unstructured or structured but also provide how to select the best candidates for downloading the desired resource from the searching result. The nodes in P2P system can be classified into logical clusters and assigned the same locality code to define their locality by the proposed NLPS. The approximate distance between two nodes is embedded in locality codes. To evaluate the performance of NLPS, DHT-based P2P systems cooperating with NLPS are simulated. The locality code of a node is associated with its DHT-based identifier (ID).The searching process is performed as normal operation in DHT based P2P system, then searching results will include the locality code of each node which owns the desired resource. Therefore, best candidate node(s) can be selected from the searching result by their associated locality codes. Extended simulation resultsshow that DHT-based P2P system cooperating with NLPS has better performance than the others DHT-based P2P systems.

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LDHT: Locality-aware Distributed Hash Tables

Cited by 28 publications

References 4 publications

Data Location Management Protocol for Object Stores in a Fog Computing Infrastructure

Data Location Management Protocol for Object Stores in a Fog Computing Infrastructure

Towards locality-aware DHT for fast mapping service in future Internet

Network locality positioning system in P2P networks

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