Extending Paxos/LastVoting with an Adequate Communication Layer for Wireless Ad Hoc Networks

Borran, Fatemeh; Prakash, Ravi; Schiper, André

doi:10.1109/srds.2008.21

Cited by 13 publications

(10 citation statements)

References 16 publications

(36 reference statements)

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“…Current centralized scheduling methods jPinedo, 2008], usually require that the system has a clear idea about resources usage patterns whereas distributed scheduling methods [Liu et ah, 2008, Zhou et ah, 2010, Sharma et al, 2010 seldom provide guarantees to exclusive allocations during communication failures. Mutual exclusion use either token- [Chang et al, 1990, Naumann et al, 2002 or permissionbased [Maekawa, 1985, Wu et al, 2008, Borran et al, 2008a, Attiya et al, 2010 methods. Dynamic participation makes the management of tokens more challenging, while limited knowledge of the number of nodes prevents consensus in permission-based approaches.…”

Section: Same-time Eventsmentioning

confidence: 99%

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A Systematic Approach to Safe Coordination of Dynamic Participants in Real-Time Distributed Systems

Sin

2016

Complex Systems Design &Amp; Management Asia

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Section: Same-time Eventsmentioning

confidence: 99%

“…Another approach is to specifying upper lower bounds on entity numbers performing coor dination, for instance, Borran et al |2008a] assumes that the number of nodes is between an upper bound, n, and a lower bound, for their quorum based Last Voting algorithm.…”

Section: -Upper Lower-boundsmentioning

confidence: 99%

A Systematic Approach to Safe Coordination of Dynamic Participants in Real-Time Distributed Systems

Sin

2016

Complex Systems Design &Amp; Management Asia

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“…Borran et al [24] address consensus under the heard-of model (HO) [25], which permits a fine-grained specification of the patterns of message delivery allowed for the problem to be solvable. This work uses the HO model to express the Paxos algorithm [26] and extend it with a communication layer for wireless networks, which provides a leader election service.…”

Section: Related Workmentioning

confidence: 99%

“…In LOCK phases (φ i (mod 2) = 2) the proposal value v i is updated the following way (lines [22][23][24][25][26][27]: if there are more than n+f 2 messages of the form * , φ, v, * in V i with φ = φ i and the same value v, then v i is set to v (lines [23][24], otherwise it is set to a special value ⊥ / ∈ {0, 1} indicating a lack of preference (lines [25][26]. This step ensures that in the following phase φ i + 1 every node either proposes the same value v ∈ {0, 1} or ⊥.…”

Section: Turquois: Byzantine K-consensusmentioning

confidence: 99%

Byzantine Fault-Tolerant Consensus in Wireless Ad Hoc Networks

Moniz

Neves

Correia³

2013

IEEE Trans. on Mobile Comput.

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Abstract-Wireless ad hoc networks, due to their inherent unreliability, pose significant challenges to the task of achieving tight coordination amongst nodes. The failure of some nodes and momentary breakdown of communications, either of accidental or malicious nature, should not result in the failure of the entire system. This paper presents an asynchronous Byzantine consensus protocol -called Turquois -specifically designed for resource-constrained wireless ad hoc networks. The key to its efficiency is the fact that it tolerates dynamic message omissions, which allows an efficient utilization of the wireless broadcasting medium. The protocol also refrains from computationally expensive public-key cryptographic during its normal operation. The protocol is safe despite the arbitrary failure of f < n 3 nodes from a total of n nodes, and unrestricted message omissions. Progress is ensured in rounds where the number of omissions is σ ≤ n−t 2 (n − k − t) + k − 2, where k is the number of nodes required to terminate and t ≤ f is the number of nodes that are actually faulty. These characteristics make Turquois the first consensus protocol that simultaneously circumvents the FLP and the Santoro-Widmayer impossibility results, which is achieved through randomization. Finally, the protocol was prototyped and subject to a comparative performance evaluation against two well-known Byzantine fault-tolerant consensus protocols. The results show that, due to its design, Turquois outperforms the other protocols by more than an order of magnitude as the number of nodes in the system increases.

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“…As observed in [7] the models for wired networks are often strongly biased towards node failures to the detriment of link failures. Yet, mobile ad hoc networks -including opportunistic networks-require a model that admits both transient process and link faults, and that considers such faults as benign failures.…”

Section: Introductionmentioning

confidence: 98%

Solving Consensus in Opportunistic Networks

Benchi

Launay

Guidec

2015

Proceedings of the 16th International Conference on Distributed Computing and Networking

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International audienceOpportunistic networks are partially connected wireless ad hoc networks, in which pairwise unpredicted transient contacts between mobile devices are the only opportunities for these devices to exchange information or services. Ensuring the coordination of multiple parts of a distributed application in such conditions is a challenge. This paper presents a system that can solve consensus problems in an opportunis-tic network. This system combines an implementation of the One-Third Rule (OTR) algorithm with a communication layer that supports network-wide, content-driven message dissemination based on controlled epidemic routing. Experimental results obtained with a small flotilla of smartphones are also presented, that validate the system and demonstrate that consensus can be solved effectively in an opportunistic network

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Extending Paxos/LastVoting with an Adequate Communication Layer for Wireless Ad Hoc Networks

Abstract: Most papers addressing consensus in wireless ad

Cited by 13 publications

References 16 publications

A Systematic Approach to Safe Coordination of Dynamic Participants in Real-Time Distributed Systems

A Systematic Approach to Safe Coordination of Dynamic Participants in Real-Time Distributed Systems

Byzantine Fault-Tolerant Consensus in Wireless Ad Hoc Networks

Solving Consensus in Opportunistic Networks

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