Rational Fair Consensus in the GOSSIP Model

The \emph{rational fair consensus problem} can be informally defined as follows. Consider a network of $n$ (selfish) \emph{rational agents}, each of them initially supporting a \emph{color} chosen from a finite set $\Sigma$. The goal is to design a protocol that leads the network to a stable monochromatic configuration (i.e. a consensus) such that the probability that the winning color is $c$ is equal to the fraction of the agents that initially support $c$, for any $c \in \Sigma$. Furthermore, this fairness property must be guaranteed (with high probability) even in presence of any fixed \emph{coalition} of rational agents that may deviate from the protocol in order to increase the winning probability of their supported colors. A protocol having this property, in presence of coalitions of size at most $t$, is said to be a \emph{whp\,-$t$-strong equilibrium}. We investigate, for the first time, the rational fair consensus problem in the GOSSIP communication model where, at every round, every agent can actively contact at most one neighbor via a \emph{push$/$pull} operation. We provide a randomized GOSSIP protocol that, starting from any initial color configuration of the complete graph, achieves rational fair consensus within $O(\log n)$ rounds using messages of $O(\log^2n)$ size, w.h.p. More in details, we prove that our protocol is a whp\,-$t$-strong equilibrium for any $t = o(n/\log n)$ and, moreover, it tolerates worst-case permanent faults provided that the number of non-faulty agents is $\Omega(n)$. As far as we know, our protocol is the first solution which avoids any all-to-all communication, thus resulting in $o(n^2)$ message complexity.Comment: Accepted at IPDPS'1

Epidemic failure detection and consensus for extreme parallelism

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum’s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. Stochastic pinging is used to quickly detect failures during the execution of the algorithm, failures are then disseminated to all the fault-free processes in the system and consensus on the failures is detected using the three consensus techniques. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that the stochastic pinging detects all the failures in the system. In all the algorithms, the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient

Randition: Random Blockchain Partitioning for Write Throughput

This paper proposes to support dynamic runtime partitioning of Tendermint, which is an in-development state machine replication algorithm that uses the blockchain model to provide Byzantine-fault tolerance. We call this variation Randition. We incorporate recent research from blockchain consensus and replicated state machine partitioning to allow Randition users to partition their blockchain for improved write performance at the cost of some Byzantine fault tolerance. We conduct an experiment to compare the raw write throughput of Randition and Tendermint. Finally, we discuss the experiment results and discuss further improvements to Randition

Design and performance study of algorithms for consensus in sparse, mobile ad-hoc networks

PhD ThesisMobile Ad-hoc Networks (MANETs) are self-organizing wireless networks that consist of mobile wireless devices (nodes). These networks operate without the aid of any form of supporting infrastructure, and thus need the participating nodes to co-operate by forwarding each other’s messages. MANETs can be deployed when urgent temporary communications are required or when installing network infrastructure is considered too costly or too slow, for example in environments such as battlefields, crisis management or space exploration. Consensus is central to several applications including collaborative ones which a MANET can facilitate for mobile users. This thesis solves the consensus problem in a sparse MANET in which a node can at times have no other node in its wireless range and useful end-to-end connectivity between nodes can just be a temporary feature that emerges at arbitrary intervals of time for any given node pair. Efficient one-to-many dissemination, essential for consensus, now becomes a challenge: enough number of destinations cannot deliver a multicast unless nodes retain the multicast message for exercising opportunistic forwarding. Seeking to keep storage and bandwidth costs low, we propose two protocols. An eventually relinquishing (}RC) protocol that does not store messages for long is used for attempting at consensus, and an eventually quiescent (}QC) one that stops forwarding messages after a while is used for concluding consensus. Use of }RC protocol poses additional challenges for consensus, when the fraction, f n, of nodes that can crash is: 1 4 f n < 1 2 . Consensus latency and packet overhead are measured through simulation indicating that they are not too high to be feasible in MANETs. They both decrease considerably even for a modest increase in network density.Damascus University