I'm an Assistant Professor in the Computer Science Department of the City University of Hong Kong. My research focuses on designing new distributed and parallel algorithms, the distributed processing of big data, achieving fault-tolerance in communication networks against adversarial attacks, and developing robust protocols that work in highly dynamic environments such as peer-to-peer Blockchain networks and mobile ad-hoc networks.

My research has been supported by the General Research Fund (Hong Kong), the Natural Sciences and Engineering Research Council (Canada), IBM Research, and the London Mathematical Society.

News

Publications

2020
  • Latency, Capacity, and Distributed Minimum Spanning Tree.
    John Augustine, Seth Gilbert, Fabian Kuhn, Peter Robinson, Suman Sourav. 40th IEEE International Conference on Distributed Computing Systems (ICDCS 2020).
2019
  • Slow Links, Fast Links, and the Cost of Gossip.DOI
    Seth Gilbert, Peter Robinson, Suman Sourav. IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS).
  • On the Hardness of the Strongly Dependent Decision Problem.
    Martin Biely and Peter Robinson. 20th International Conference on Distributed Computing and Networking (ICDCN 2019).
    Abstract
    We present necessary and sufficient conditions for solving the strongly dependent decision (SDD) problem in various distributed systems. Our main contribution is a novel characterization of the SDD problem based on point-set topology. For partially synchronous systems, we show that any algorithm that solves the SDD problem induces a set of executions that is closed with respect to the point-set topology. We also show that the SDD problem is not solvable in the asynchronous system augmented with any arbitrarily strong failure detectors.
2018
  • Slow Links, Fast Links, and the Cost of GossipDOI
    Seth Gilbert, Peter Robinson, Suman Sourav. 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018).
    Abstract
    Consider the classical problem of information dissemination: one (or more) nodes in a network have some information that they want to distribute to the remainder of the network. In this paper, we study the cost of information dissemination in networks where edges have latencies, i.e., sending a message from one node to another takes some amount of time. We first generalize the idea of conductance to weighted graphs, defining $\phi_*$ to be the ``weighted conductance'' and $\ell_*$ to be the ``critical latency.'' One goal of this paper is to argue that $\phi_*$ characterizes the connectivity of a weighted graph with latencies in much the same way that conductance characterizes the connectivity of unweighted graphs. We give near tight upper and lower bounds on the problem of information dissemination, up to polylogarithmic factors. Specifically, we show that in a graph with (weighted) diameter $D$ (with latencies as weights), maximum degree $\Delta$, weighted conductance $\phi_*$ and critical latency $\ell_*$, any information dissemination algorithm requires at least $\Omega(\min(D+\Delta, \ell_*/\phi_*))$ time. We show several variants of the lower bound (e.g., for graphs with small diameter, graphs with small max-degree, etc.) by reduction to a simple combinatorial game. We then give nearly matching algorithms, showing that information dissemination can be solved in $O(\min((D + \Delta)\log^3{n}), (\ell_*/\phi_*)\log(n))$ time. % $O(\min(D\log^3(n), \ell_*\log(n)/\phi_*))$. The algorithm consists of two sub-algorithms: This is achieved by combining two cases. When nodes do not know the latency of the adjacent edges, we show that the classical push-pull algorithm is (near) optimal when the diameter or maximum degree is large. For the case where the diameter and maximum degree are small, we give an alternative strategy in which we first discover the latencies and then use an algorithm for known latencies based on a weighted spanner construction. (Our algorithms are within polylogarithmic factors of being tight both for known and unknown latencies.)
2014
  • The Generalized Loneliness Detector and Weak System Models for k-Set AgreementPDFDOI
    Martin Biely, Peter Robinson, Ulrich Schmid. IEEE Transactions on Parallel and Distributed Systems, vol. 25(4), 1078-1088 (IEEE TPDS).
    Abstract
    This paper presents two weak partially synchronous system models MAnti[n-k] and MSink[n-k], which are just strong enough for solving $k$-set agreement: We introduce the generalized $(n-k)$-loneliness failure detector $\mathcal{L}(k)$, which we first prove to be sufficient for solving $k$-set agreement, and show that $\mathcal{L}(k)$ but not $\mathcal{L}(k-1)$ can be implemented in both models. MAnti[n-k] and MSink[n-k] are hence the first message passing models that lie between models where $\Omega$ (and therefore consensus) can be implemented and the purely asynchronous model. We also address $k$-set agreement in anonymous systems, that is, in systems where (unique) process identifiers are not available. Since our novel $k$-set agreement algorithm using $\mathcal{L}(k)$ also works in anonymous systems, it turns out that the loneliness failure detector $\mathcal{L}=\mathcal{L}(n-1)$ introduced by Delporte et al. is also the weakest failure detector for set agreement in anonymous systems. Finally, we analyze the relationship between $\mathcal{L}(k)$ and other failure detectors suitable for solving $k$-set agreement.
2011
  • Easy Impossibility Proofs for k-Set Agreement in Message Passing SystemsPDFDOI
    Martin Biely, Peter Robinson, Ulrich Schmid. 15th International Conference On Principles Of Distributed Systems (OPODIS 2011).
    Abstract
    Despite of being quite similar agreement problems, distributed consensus ($1$-set agreement) and general $k$-set agreement require surprisingly different techniques for proving their impossibility in asynchronous systems with crash failures: Rather, than the relatively simple bivalence arguments as in the impossibility proof for consensus in the presence of a single crash failure, known proofs for the impossibility of $k$-set agreement in shared memory systems with $f\geq k>1$ crash failures use algebraic topology or a variant of Sperner's Lemma. In this paper, we present a generic theorem for proving the impossibility of $k$-set agreement in various message passing settings, which is based on a reduction to the consensus impossibility in a certain subsystem resulting from a partitioning argument. We demonstrate the broad applicability of our result by exploring the possibility/impossibility border of $k$-set agreement in several message passing system models: (i) asynchronous systems with crash failures, (ii) partially synchronous processes with (initial) crash failures, and, most importantly, (iii) asynchronous systems augmented with failure detectors. Furthermore, by extending the algorithm for initial crashes of Fisher, Lynch and Patterson (1985) to general $k$-set agreement, we show that the impossibility border of (i) is tightly matched. The impossibility proofs in cases (i), (ii), and (iii) are instantiations of our main theorem. Regarding (iii), applying our technique reveals the exact border for the parameter $k$ where $k$-set agreement is solvable with the failure detector class $(\Sigma_k,\Omega_k)_{1\le k\le n-1}$ of Bonnet and Raynal. As $\Sigma_k$ was shown to be necessary for solving $k$-set agreement, this result yields new insights on the quest for the weakest failure detector
  • The Asynchronous Bounded-Cycle ModelPDFDOI
    Peter Robinson and Ulrich Schmid. Theoretical Computer Science 412 (2011) 5580–5601. (TCS).
    Abstract
    This paper shows how synchrony conditions can be added to the purely asynchronous model in a way that avoids any reference to message delays and computing step times, as well as any global constraints on communication patterns and network topology. Our Asynchronous Bounded-Cycle (ABC) model just bounds the ratio of the number of forward- and backward-oriented messages in certain ''relevant'' cycles in the space-time diagram of an asynchronous execution. We show that clock synchronization and lock-step rounds can easily be implemented and proved correct in the ABC model, even in the presence of Byzantine failures. Furthermore, we prove that any algorithm working correctly in the partially synchronous $\Theta$-Model also works correctly in the ABC model. In our proof, we first apply a novel method for assigning certain message delays to asynchronous executions, which is based on a variant of Farkas' theorem of linear inequalities and a non-standard cycle-space of graphs. Using methods from point-set topology, we then prove that the existence of this delay assignment implies model indistinguishability for time-free safety and liveness properties. Finally, we introduce several weaker variants of the ABC model and relate our model to the existing partially synchronous system models, in particular, the classic models of Dwork, Lynch and Stockmayer. Furthermore, we discuss aspects of the ABC model's applicability in real systems, in particular, in the context of VLSI Systems-on-Chip.
2009
  • Weak Synchrony Models and Failure Detectors for Message Passing k-Set AgreementDOI
    Martin Biely, Peter Robinson, Ulrich Schmid. 13th International Conference On Principles Of Distributed Systems (OPODIS 2009).
2008
  • The Asynchronous Bounded-Cycle ModelDOI
    Peter Robinson and Ulrich Schmid. 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS 2008). Best Paper Award.
    Abstract
    This paper shows how synchrony conditions can be added to the purely asynchronous model in a way that avoids any reference to message delays and computing step times, as well as any global constraints on communication patterns and network topology. Our Asynchronous Bounded-Cycle (ABC) model just bounds the ratio of the number of forward- and backward-oriented messages in certain ''relevant'' cycles in the space-time diagram of an asynchronous execution. We show that clock synchronization and lock-step rounds can easily be implemented and proved correct in the ABC model, even in the presence of Byzantine failures. Furthermore, we prove that any algorithm working correctly in the partially synchronous $\Theta$-Model also works correctly in the ABC model. In our proof, we first apply a novel method for assigning certain message delays to asynchronous executions, which is based on a variant of Farkas' theorem of linear inequalities and a non-standard cycle-space of graphs. Using methods from point-set topology, we then prove that the existence of this delay assignment implies model indistinguishability for time-free safety and liveness properties. Finally, we introduce several weaker variants of the ABC model and relate our model to the existing partially synchronous system models, in particular, the classic models of Dwork, Lynch and Stockmayer. Furthermore, we discuss aspects of the ABC model's applicability in real systems, in particular, in the context of VLSI Systems-on-Chip.

Code

I'm interested in parallel and distributed programming and related technologies such as software transactional memory and the actor-model. Recently, I have been working on implementing a simulation environment for distributed algorithms in Elixir/Erlang, and implementing non-blocking data structures in Haskell suitable for multi-core machines. Below is a (non-comprehensive) list of software that I have written.
  • concurrent hash table: a thread-safe hash table that scales to multicores.
  • data dispersal: an implementation of an (m,n)-threshold information dispersal scheme that is space-optimal.
  • secret sharing: an implementation of a secret sharing scheme that provides information-theoretic security.
  • tskiplist: a data structure with range-query support for software transactional memory.
  • stm-io-hooks: An extension of Haskell's Software Transactional Memory (STM) monad with commit and retry IO hooks.
  • Mathgenealogy: Visualize your (academic) genealogy! A program for extracting data from the Mathematics Genealogy project.
  • I extended Haskell's Cabal, for using a "world" file to keep track of installed packages. (Now part of the main distribution.)

Teaching

  • Computer Networks, Fall 2020, 2019.
  • Database Systems, Spring 2020.
  • Distributed Computing, Spring 2019.
  • Randomized Algorithms, Fall 2018: Intro slides. Part 1 on Concentration Bounds.
  • Advanced Distributed Systems, Fall 2016, 2017.
  • Computation with Data, Fall 2016.
  • Internet and Web Technologies, Spring 2016.

Misc