What is the role of the DHT in the implementation of applications?

The DHT can act as an outsourced service [6], [7] for easing the implementation of applications, which can inherit the scalability and robustness of the DHT.

How does Squid use a space-filling curve?

Squid uses a space-filling curve (SFC) [27] to map objects with multiple attributes to peers and processes range queries by searching SFC clusters recursively.

What is the average delay of a query?

The average query delay is less than logNand the maximum delay is less than 2 logN , independent ofthe size of query space and specific queries.

What is the simplest way to forward a range query?

When some peers in the query path fail, Armada can make use of the fault-tolerant routing mechanism of the underlying DHT [5] to forward the query messages.

What is the average delay of PIRA?

the size of queried range increases, the average delay ofDCF-CAN increases remarkably, while PIRA is delay-bounded: its average delay is always less than logN ,regardless of the range size.

What is the main reason for the limitations of the existing DHT?

As the capability of the existing DHT is limited, many services may be built on the same DHT infrastructure to support different applications, and these services should be designed without modifying the underlying DHT.

What is the message cost of PIRA and MIRA?

tuFrom Theorem 4, it can be inferred that both PIRA and MIRA are delay-bounded because they can return all query results within 2 logN hops, regardless of the size of the query space or the specific range queried, and their delays both reach the lower bound OðlogNÞ.

What is the tuple of the multiple-attribute space?

The multiple-attribute value space, called multiple-attribute space, is an m-dimensional subspace and denoted by a tuple ! ¼ , where ri is a subinterval of the value of attribute Ai (e.g., ri ¼ ðxi; yi ).

How can The authoruse the partition tree to reduce the number of peers searched during the range query?

It can also be effective to utilize the query condition of each attribute to reduce the number of peers searched during the range query processing.

Open AccessJournal Article10.1109/TKDE.2008.99

Efficient Range Query Processing in Peer-to-Peer Systems

Dongsheng Li, +3 more

- 01 Jan 2009

- IEEE Transactions on Knowledge and Data ...

- Vol. 21, Iss: 1, pp 78-91

TL;DR: Armada is the first delay-bounded general range query scheme on constant-degree DHTs, and can return the results for any range query within 2logN hops in a P2P system with N peers.

Abstract: With the increasing popularity of the peer-to-peer (P2P) computing paradigm, many general range query schemes for distributed hash table (DHT)-based P2P systems have been proposed. Although those schemes can provide range query capability without modifying the underlying DHTs, they have the query delay depending on both the scale of the system and the size of the query space or the specific query, and thus cannot guarantee to return the query results in a bounded delay. In this paper, we propose Armada, an efficient range query processing scheme to support delay-bounded single-attribute and multiple-attribute range queries. It is the first delay-bounded general range query scheme on constant-degree DHTs, and can return the results for any range query within 2logN hops in a P2P system with N peers. Results of analysis and simulations show that the average delay in Armada is less than logN, and the average message cost of single-attribute range queries is about logN+2n 2 (n is the number of peers that intersect with the query). These results are very close to the lower bounds on delay and message cost of range queries over constant-degree DHTs.

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Most frequently asked questions

1. What are the contributions in "Efficient range query processing in peer-to-peer systems" ?

In this paper, the authors propose Armada, an efficient range query processing scheme to support delay-bounded single-attribute and multiple-attribute range queries.. The authors first describe the order-preserving naming algorithms for assigning adjoining ObjectIDs to objects with close attribute values.. Then, the authors present the design of the forwarding tree to efficiently match the search paths of range queries to the underlying DHT topology.

2. What mechanism is used to balance load across peers?

Armada uses two mechanisms to balance load across peers: 1) ObjectID balancing: a Probability-based lOad Balancing Mechanism (POBM) is used to generate uniform ObjectIDs when the distribution of attribute values is known in advance and 2) runtime balancing: each peer in Armada houses multiple virtual servers and the load is balanced by transferring virtual servers from heavily loaded peers to lightly loaded peers.

3. What mechanisms have been proposed to improve load balancing of DHTs?

Many mechanisms, such as ID selection [37], virtual servers [38], and item balancing [39], have been proposed to improve load balancing of DHTs.

4. What is the underlying mechanism for a peer failure?

If a peer fails, the underlying FissionE DHT automatically ensures that other peers in the overlay takes over the responsibility for the failed peer and provides graceful fail-over by using replication or other mechanisms.

Fig. 15. The load balancing property of Armada.

Fig. 4. Partition tree P ð2; 4Þ for attribute-value interval [0, 1].

Fig. 11. The impact of range size on query delay.

Fig. 14. The impact of network size on message cost. (a) Number of messages. (b) Parameters about message cost of PIRA.

Citations

•Journal Article•10.1109/TPDS.2012.144

Dynamic Optimization of Multiattribute Resource Allocation in Self-Organizing Clouds

Sheng Di, +1 more

- 01 Mar 2013

- IEEE Transactions on Parallel and Distri...

TL;DR: A fully distributed, VM-multiplexing resource allocation scheme to manage decentralized resources to achieve maximized resource utilization using the proportional share model (PSM), but also delivers provably and adaptively optimal execution efficiency.

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Journal Article•10.1016/J.FUTURE.2011.08.005

Internet-based Virtual Computing Environment

Xicheng Lu, +4 more

- 01 Jan 2013

- Future Generation Computer Systems

TL;DR: The concept of an Internet-based Virtual Computing Environment (iVCE), which aims to provide Cloud services by a dynamic combination of data centers and other multi-scale computing resources on the Internet, is introduced.

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•Journal Article•10.1109/TKDE.2009.47

LIGHT: A Query-Efficient Yet Low-Maintenance Indexing Scheme over DHTs

Yuzhe Tang, +2 more

- 01 Jan 2010

- IEEE Transactions on Knowledge and Data ...

TL;DR: This paper proposes LIGhtweight Hash Tree (LIGHT)-a query-efficient yet low-maintenance indexing scheme that employs a novel naming mechanism and a tree summarization strategy for graceful distribution of its index structure and shows through analysis that it can support various complex queries with near-optimal performance.

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•Journal Article•10.1109/TPDS.2010.200

Fast and Cost-Effective Online Load-Balancing in Distributed Range-Queriable Systems

Ioannis Konstantinou, +2 more

- 01 Aug 2011

- IEEE Transactions on Parallel and Distri...

TL;DR: This work detects the two basic methodologies used to achieve load-balancing: Iterative key redistribution between neighbors and node migration and proposes NIXMIG, a hybrid method that adaptively utilizes these two extremes to achieve both fast and cost-effective load- Balancing in distributed systems that support range queries.

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Large-scale virtual machines provisioning in clouds: challenges and approaches

Zhaoning Zhang, +2 more

- 01 Feb 2016

- Frontiers of Computer Science

TL;DR: This paper systematically review the existing VM provisioning schemes and classify them in three main categories, and discusses the features and research status of each category, and introduces two recent solutions, VMThunder and VMThunder+, both of which can provision hundreds of VMs in seconds.

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References

Journal Article•10.1145/361002.361007

Multidimensional binary search trees used for associative searching

Jon Louis Bentley

- 01 Sep 1975

- Communications of The ACM

TL;DR: The multidimensional binary search tree (or k-d tree) as a data structure for storage of information to be retrieved by associative searches is developed and it is shown to be quite efficient in its storage requirements.

...read moreread less

8.2K

•Book Chapter•10.1007/3-540-45518-3_18

Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems

Antony Rowstron, +1 more

- 12 Nov 2001

- Lecture Notes in Computer Science

TL;DR: Pastry as mentioned in this paper is a scalable, distributed object location and routing substrate for wide-area peer-to-peer ap- plications, which performs application-level routing and object location in a po- tentially very large overlay network of nodes connected via the Internet.

...read moreread less

•Proceedings Article•10.1145/383059.383072

A scalable content-addressable network

Sylvia Ratnasamy, +4 more

- 27 Aug 2001

TL;DR: The concept of a Content-Addressable Network (CAN) as a distributed infrastructure that provides hash table-like functionality on Internet-like scales is introduced and its scalability, robustness and low-latency properties are demonstrated through simulation.

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7.2K

Journal Article•10.1109/TNET.2002.808407

Chord: a scalable peer-to-peer lookup protocol for Internet applications

Ion Stoica, +6 more

- 01 Feb 2003

- IEEE ACM Transactions on Networking

TL;DR: Results from theoretical analysis and simulations show that Chord is scalable: Communication cost and the state maintained by each node scale logarithmically with the number of Chord nodes.

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3.6K

•Journal Article•10.1109/JSAC.2003.818784

Tapestry: a resilient global-scale overlay for service deployment

Ben Y. Zhao, +5 more

- 07 Jan 2004

- IEEE Journal on Selected Areas in Commun...

TL;DR: Experimental results show that Tapestry exhibits stable behavior and performance as an overlay, despite the instability of the underlying network layers, illustrating its utility as a deployment infrastructure.

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...

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Efficient Range Query Processing in Peer-to-Peer Systems

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AI Agents for this Paper

Most frequently asked questions

1. What are the contributions in "Efficient range query processing in peer-to-peer systems" ?

2. What mechanism is used to balance load across peers?

3. What mechanisms have been proposed to improve load balancing of DHTs?

4. What is the underlying mechanism for a peer failure?

5. What is the role of the DHT in the implementation of applications?

6. How does Squid use a space-filling curve?

7. What is the average delay of a query?

8. What is the simplest way to forward a range query?

9. What is the average delay of PIRA?

10. What is the main reason for the limitations of the existing DHT?

11. What is the message cost of PIRA and MIRA?

12. What is the tuple of the multiple-attribute space?

13. How can The authoruse the partition tree to reduce the number of peers searched during the range query?

Figures

Citations

Dynamic Optimization of Multiattribute Resource Allocation in Self-Organizing Clouds

Internet-based Virtual Computing Environment

LIGHT: A Query-Efficient Yet Low-Maintenance Indexing Scheme over DHTs

Fast and Cost-Effective Online Load-Balancing in Distributed Range-Queriable Systems

Large-scale virtual machines provisioning in clouds: challenges and approaches

References

Multidimensional binary search trees used for associative searching

Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems

A scalable content-addressable network

Chord: a scalable peer-to-peer lookup protocol for Internet applications

Tapestry: a resilient global-scale overlay for service deployment

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