## Peter Robinson

I'm an Assistant Professor (UK Lecturer) at Royal Holloway, University of London. I'm interested in designing new distributed and parallel algorithms, the distributed processing of big data, achieving fault-tolerance in networks, and secure distributed computing in dynamic environments such as peer-to-peer networks and mobile ad-hoc networks.

## News

- General Chair of ACM PODC 2019
- Program committee member of PODC 2018, ICDCS 2018, BGP 2017, SPAA 2016
- Presentation at the workshop on Dynamic Graphs in Distributed Computing (co-located with DISC 2016)
- Program Committee Co-Chair of ICDCN 2016
- Presentation at ADGA 2015, (4th Workshop on Advances in Distributed Graph Algorithms, co-located with DISC 2015)

## Keywords (Show all)

Asynchrony Big Data Byzantine Failures Churn Communication Complexity Distributed Agreement Distributed Storage Dynamic Network Fault-Tolerance Gossip Communication Graph Algorithm Haskell Leader Election Machine Learning Mobile Ad-Hoc Network Natural Language Processing P2P Secure Computation Self-Healing Symmetry Breaking## Publications

2017

- Breaking the $\tilde \Omega(\sqrt{n})$ Barrier: Fast Consensus under a Late Adversary

Peter Robinson, Christian Scheideler, Alexander Setzer. (under review)

AbstractWe study the consensus problem in a synchronous distributed system of $n$ nodes under an adaptive adversary that has a slightly outdated view of the system and can block all incoming and outgoing communication of a constant fraction of the nodes in each round. Motivated by a result of Ben-Or and Bar-Joseph (1998), showing that any consensus algorithm that is resilient against a linear number of crash faults requires $\tilde \Omega(\sqrt{n})$ rounds in an $n$-node network against an adaptive adversary, we consider a late adaptive adversary, who has full knowledge of the network state at the beginning of the previous round and unlimited computational power, but is oblivious to the current state of the nodes. Our main contributions are randomized distributed algorithms that achieve consensus with high probability among all except a small constant fraction of the nodes (i.e., ``almost-everywhere'') against a late adaptive adversary who can block up to $\epsilon n$ nodes in each round, for a small constant $\epsilon >0$. Our first protocol achieves binary almost-everywhere consensus and also guarantees a decision on the majority input value, thus ensuring plurality consensus. We also present an algorithm that achieves the same time complexity for multi-value consensus. Both of our algorithms succeed in $O(\log n)$ rounds with high probability, thus breaking the known $\tilde\Omega(\sqrt{n})$ lower bound for fully adaptive adversaries. Our algorithms are scalable to large systems as each node contacts only an (amortized) constant number of peers in each communication round. We show that our algorithms are optimal up to constant (resp. sub-logarithmic) factors by proving that every almost-everywhere consensus protocol takes $\Omega(\log_d n)$ rounds in the worst case, where $d$ is an upper bound on the number of communication requests initiated per node in each round.

2016

- DEX: Self-Healing ExpandersDOI

Gopal Pandurangan, Peter Robinson, Amitabh Trehan. Distributed Computing (DC).

AbstractWe present a fully-distributed self-healing algorithm DEX, that maintains a constant degree expander network in a dynamic setting. To the best of our knowledge, our algorithm provides the first efficient distributed construction of expanders --- whose expansion properties hold deterministically --- that works even under an all-powerful adaptive adversary that controls the dynamic changes to the network (the adversary has unlimited computational power and knowledge of the entire network state, can decide which nodes join and leave and at what time, and knows the past random choices made by the algorithm). Previous distributed expander constructions typically provide only probabilistic guarantees on the network expansion which rapidly degrade in a dynamic setting; in particular, the expansion properties can degrade even more rapidly under adversarial insertions and deletions. Our algorithm provides efficient maintenance and incurs a low overhead per insertion/deletion by an adaptive adversary: only $O(\log n)$ rounds and $O(\log n)$ messages are needed with high probability ($n$ is the number of nodes currently in the network). The algorithm requires only a constant number of topology changes. Moreover, our algorithm allows for an efficient implementation and maintenance of a distributed hash table (DHT) on top of DEX, with only a constant additional overhead. Our results are a step towards implementing efficient self-healing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes.

2015

- Gracefully Degrading Consensus and k-Set Agreement in Directed Dynamic NetworksDOI

Martin Biely, Peter Robinson, Ulrich Schmid, Manfred Schwarz, Kyrill Winkler. 2nd International Conference on Networked Systems (NETYS 2015).

AbstractWe present the first consensus/k-set agreement algorithm for synchronous dynamic networks with unidirectional links, controlled by an omniscient message adversary, which automatically adapts to the actual network properties in a run: If the network is sufficiently well-connected, it solves consensus, while it degrades gracefully to general k-set agreement in less well-connected communication graphs. The actual number k of system-wide decision values is determined by the number of certain vertex-stable root components occurring in a run, which are strongly connected components without incoming links from outside. Related impossibility results reveal that our condition is reasonably close to the solvability border for k-set agreement.

2014

- DEX: Self-Healing ExpandersPDFDOI

Gopal Pandurangan, Peter Robinson, Amitabh Trehan. 28th IEEE International Parallel Distributed Processing Symposium (IPDPS 2014).

AbstractWe present a fully-distributed self-healing algorithm DEX, that maintains a constant degree expander network in a dynamic setting. To the best of our knowledge, our algorithm provides the first efficient distributed construction of expanders --- whose expansion properties hold deterministically --- that works even under an all-powerful adaptive adversary that controls the dynamic changes to the network (the adversary has unlimited computational power and knowledge of the entire network state, can decide which nodes join and leave and at what time, and knows the past random choices made by the algorithm). Previous distributed expander constructions typically provide only probabilistic guarantees on the network expansion which rapidly degrade in a dynamic setting; in particular, the expansion properties can degrade even more rapidly under adversarial insertions and deletions. Our algorithm provides efficient maintenance and incurs a low overhead per insertion/deletion by an adaptive adversary: only $O(\log n)$ rounds and $O(\log n)$ messages are needed with high probability ($n$ is the number of nodes currently in the network). The algorithm requires only a constant number of topology changes. Moreover, our algorithm allows for an efficient implementation and maintenance of a distributed hash table (DHT) on top of DEX, with only a constant additional overhead. Our results are a step towards implementing efficient self-healing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes. - Distributed Agreement in Dynamic Peer-to-Peer NetworksPDFDOI

John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal. Journal of Computer and System Sciences, Elsevier. (JCSS). - 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).

AbstractThis 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.

2013

- Fast Byzantine Agreement in Dynamic NetworksPDFDOI

John Augustine, Gopal Pandurangan, Peter Robinson 32nd ACM Symposium on Principles of Distributed Computing (PODC 2013).

AbstractWe study Byzantine agreement in dynamic networks where topology can change from round to round and nodes can also experience heavy churn (i.e., nodes can join and leave the network continuously over time). Our main contributions are randomized distributed algorithms that guarantee almost-everywhere Byzantine agreement with high probability even under a large number of Byzantine nodes and continuous adversarial churn in a number of rounds that is polylogarithmic in $n$ (where $n$ is the stable network size). We show that our algorithms are essentially optimal (up to polylogarithmic factors) with respect to the amount of Byzantine nodes and churn rate that they can tolerate by showing lower bound. In particular, we present the following results: \begin{enumerate} \item An $O(\log^3 n)$ round randomized algorithm that achieves almost-everywhere Byzantine agreement with high probability under a presence of up to $O(\sqrt{n}/\text{polylog}(n))$ Byzantine nodes and up to a churn of $O(\sqrt{n}/\text{polylog}(n))$ nodes per round. We assume that the Byzantine nodes have knowledge about the entire state of network at every round (including random choices made by all the nodes) and can behave arbitrarily. We also assume that an adversary controls the churn --- it has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power (but is oblivious to the topology changes from round to round). Our algorithm requires only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. \item We also present an $O(\log^3 n)$ round randomized algorithm that has same guarantees as the above algorithm, but works even when the churn and network topology is controlled by an adaptive adversary (that can choose the topology based on the current states of the nodes). However, this algorithm requires up to polynomial in $n$ bits to be processed and sent (per round) by each node. \item We show that the above bounds are essentially the best possible, if one wants fast (i.e., polylogarithmic run time) algorithms, by showing that any (randomized) algorithm to achieve agreement in a dynamic network controlled by an adversary that can churn up to $\Theta(\sqrt{ n \log n})$ nodes per round should take at least a polynomial number of rounds. \end{enumerate} Our algorithms are the first-known, fully-distributed, Byzantine agreement algorithms in highly dynamic networks. We view our results as a step towards understanding the possibilities and limitations of highly dynamic networks that are subject to malicious behavior by a large number of nodes. - Search and Storage in Dynamic Peer-to-Peer NetworksPDFDOI

John Augustine, Anisur Molla, Ehab Morsy, Gopal Pandurangan, Peter Robinson, Eli Upfal. 25th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2013).

AbstractWe study robust and efficient distributed algorithms for searching, storing, and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to guarantee, despite high node churn rate, that a large number of nodes in the network can store, retrieve, and maintain a large number of data items. Our main contributions are fast randomized distributed algorithms that guarantee the above with high probability even under high adversarial churn. In particular, we present the following main results: \begin{enumerate} \item A randomized distributed search algorithm that with high probability guarantees that searches from as many as $n - o(n)$ nodes ($n$ is the stable network size) succeed in ${O}(\log n )$-rounds despite ${O}(n/\log^{1+\delta} n)$ churn, for any small constant $\delta > 0$, per round. We assume that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). \item A storage and maintenance algorithm that guarantees, with high probability, data items can be efficiently stored (with only $\Theta(\log{n})$ copies of each data item) and maintained in a dynamic P2P network with churn rate up to ${O}(n/\log^{1+\delta} n)$ per round. Our search algorithm together with our storage and maintenance algorithm guarantees that as many as $n - o(n)$ nodes can efficiently store, maintain, and search even under ${O}(n/\log^{1+\delta} n)$ churn per round. Our algorithms require only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. \end{enumerate} To the best of our knowledge, our algorithms are the first-known, fully-distributed storage and search algorithms that provably work under highly dynamic settings (i.e., high churn rates per step). Furthermore, they are localized (i.e., do not require any global topological knowledge) and scalable. A technical contribution of this paper, which may be of independent interest, is showing how random walks can be provably used to derive scalable distributed algorithms in dynamic networks with adversarial node churn. - Robust Leader Election in a Fast-Changing World

John Augustine, Tejas Kulkarni, Paresh Nakhe, Peter Robinson. 9th International Workshop on Foundations of Mobile Computing (FOMC 2013).

AbstractWe consider the problem of electing a leader among nodes in a highly dynamic network where the adversary has unbounded capacity to insert and remove nodes (including the leader) from the network and change connectivity at will. We present a randomized algorithm that (re)elects a leader in $O(D\log n)$ rounds with high probability, where $D$ is a bound on the dynamic diameter of the network and $n$ is the maximum number of nodes in the network at any point in time. We assume a model of broadcast-based communication where a node can send only $1$ message of $O(\log n)$ bits per round and is not aware of the receivers in advance. Thus our results also apply to mobile wireless ad-hoc networks, improving over the optimal (for deterministic algorithms) $O(Dn)$ solution presented at FOMC 2011. We show that our algorithm is optimal by proving that any randomized algorithm takes at least $\Omega(D\log n)$ rounds to elect a leader with high probability, which shows that our algorithm yields the best possible (up to constants) termination time.

2012

- Towards Robust and Efficient Computation in Dynamic Peer-to-Peer NetworksPDFDOI

John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal. 23rd ACM-SIAM Symposium on Discrete Algorithms (SODA 2012).

AbstractMotivated by the need for robust and fast distributed computation in highly dynamic Peer-to-Peer (P2P) networks, we study algorithms for the fundamental distributed agreement problem. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to design fast algorithms (running in a small number of rounds) that guarantee, despite high node churn rate, that almost all nodes reach a stable agreement. Our main contributions are randomized distributed algorithms that guarantee stable almost-everywhere agreement with high probability even under high adversarial churn in a polylogarithmic number of rounds. In particular, we present the following results: \begin{enumerate} \item An $O(\log^2 n)$-round ($n$ is the stable network size) randomized algorithm that achieves almost-everywhere agreement with high probability under up to linear churn per round (i.e., $\epsilon n$, for some small constant $\epsilon > 0$), assuming that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). \item An $O(\log m\log^3 n)$-round randomized algorithm that achieves almost-everywhere agreement with high probability under up to $\epsilon \sqrt{n}$ churn per round (for some small $\epsilon > 0$), where $m$ is the size of the input value domain, that works even under an adaptive adversary (that also knows the past random choices made by the algorithm). \item We also show that no deterministic algorithm can guarantee almost-everywhere agreement (regardless of the number of rounds), even under constant churn rate. \end{enumerate} Our algorithms are the first-known, fully-distributed, agreement algorithms that work under highly dynamic settings (i.e., high churn rates per step). Furthermore, they are localized (i.e., do not require any global topological knowledge), simple, and easy to implement. These algorithms can serve as building blocks for implementing other non-trivial distributed computing tasks in dynamic P2P networks. - Agreement in Directed Dynamic NetworksPDFDOI

Martin Biely, Peter Robinson, Ulrich Schmid. 19th International Colloquium on Structural Information and Communication Complexity (SIROCCO 2012).

AbstractWe study distributed computation in synchronous dynamic networks where an omniscient adversary controls the unidirectional communication links. Its behavior is modeled as a sequence of directed graphs representing the active (i.e. timely) communication links per round. We prove that consensus is impossible under some natural weak connectivity assumptions and introduce vertex-stable root components as a means for circumventing this impossibility. Essentially, we assume that there is a short period of time during which an arbitrary part of the network remains strongly connected, while its interconnect topology may keep changing continuously. We present a consensus algorithm that works under this assumption and prove its correctness. Our algorithm maintains a local estimate of the communication graphs and applies techniques for detecting stable network properties and univalent system configurations. Our possibility results are complemented by several impossibility results and lower bounds for consensus and other distributed computing problems like leader election, revealing that our algorithm is asymptotically optimal.

2011

- Weak System Models for Fault-Tolerant Distributed Agreement Problems

Peter Robinson. PhD Thesis in Computer Science.

AbstractThis thesis investigates various aspects of weak system models for agreement problems in fault-tolerant distributed computing. In Part~I we provide an introduction to the context of this work, discuss related literature and describe the basic system assumptions. In Part~II of this thesis, we introduce the Asynchronous Bounded-Cycle (ABC) model, which is entirely time-free. In contrast to existing system models, the ABC model does not require explicit time-based synchrony bounds, but rather stipulates a graph-theoretic synchrony condition on the relative lengths of certain causal chains of messages in the space-time graph of a run. We compare the ABC model to other models in literature, in particular to the classic models by Dwork, Lynch, and Stockmeyer. Despite Byzantine failures, we show how to simulate lock-step rounds, and therefore make consensus solvable, and prove the correctness of a clock synchronization algorithm in the ABC model. We then present the technically most involved result of this thesis: We prove that any algorithm working correctly in the partially synchronous $\Theta$-Model by Le Lann and Schmid, also works correctly in the time-free ABC model. In the proof, we use a variant of Farkas' Theorem of Linear Inequalities and develop a non-standard cycle space on directed graphs in order to guarantee the existence of a certain message delay transformation for finite prefixes of runs. This shows that any time-free safety property satisfied by an algorithm in the $\Theta$-Model also holds in the ABC model. By employing methods from point-set topology, we can extend this result to liveness properties. In Part~III, we shift our attention to the borderland between models where consensus is solvable and the purely asynchronous model. To this end, we look at the $k$-set agreement problem where processes need to decide on at most $k$ distinct decision values. We introduce two very weak system models MAnti and MSink and prove that consensus is impossible in these models. Nevertheless, we show that $(n-1)$-set agreement is solvable in MAnti and MSink, by providing algorithms that implement the weakest failure detector $\mathcal{L}$. We also discuss how models MAnti and MSink relate to the $f$-source models by Aguilera et al. for solving consensus. In the subsequent chapter, we present a novel failure detector $\mathcal{L}(k)$ that generalizes $\mathcal{L}$, and analyze an algorithm for solving $k$-set agreement with $\mathcal{L}(k)$, which works even in systems without unique process identifiers. Moreover, We explore the relationship between $\mathcal{L}(k)$ and existing failure detectors for $k$-set agreement. Some aspects of $\mathcal{L}(k)$ relating to anonymous systems are also discussed. Next, we present a generic theorem that can be used to characterize the impossibility of achieving $k$-set agreement in various system models. This enables us to show that $(\Sigma_k,\Omega_k)$ is not sufficient for solving $k$-set agreement. Furthermore, we instantiate our theorem with a partially synchronous system model. Finally, we consider the $k$-set agreement problem in round-based systems. First, we introduce a novel abstraction that encapsulates the perpetual synchrony of a run, the so called stable skeleton graph, which allows us to express the solvability power of a system via graph-theoretic properties. We then present an approximation algorithm where processes output an estimate of their respective component of the stable skeleton graph. We define a class of communication predicates PSources(k) in this framework, and show that PSources(k) tightly captures the amount of synchrony necessary for $k$-set agreement, as $(k-1)$-set agreement is impossible with PSources(k). Based on the stable skeleton approximation, we present an algorithm that solves $k$-set agreement when PSources(k) holds. - Optimal Regional Consecutive Leader Election in Mobile Ad-Hoc NetworksPDFDOI

Hyun Chul Chung, Peter Robinson, Jennifer L. Welch. 7th ACM SIGACT/SIGMOBILE International Workshop on Foundations of Mobile Computing (part of FCRC 2011).

AbstractThe regional consecutive leader election (RCLE) problem requires mobile nodes to elect a leader within bounded time upon entering a specific region. We prove that any algorithm requires $\Omega(Dn)$ rounds for leader election, where D is the diameter of the network and $n$ is the total number of nodes. We then present a fault-tolerant distributed algorithm that solves the RCLE problem and works even in settings where nodes do not have access to synchronized clocks. Since nodes set their leader variable within $O(Dn)$ rounds, our algorithm is asymptotically optimal with respect to time complexity. Due to its low message bit complexity, we believe that our algorithm is of practical interest for mobile wireless ad-hoc networks. Finally, we present a novel and intuitive constraint on mobility that guarantees a bounded communication diameter among nodes within the region of interest. - Solving k-Set Agreement with Stable Skeleton GraphsPDFDOI

Martin Biely, Peter Robinson, Ulrich Schmid. 16th IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum (IPDPS 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).

AbstractDespite 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).

AbstractThis 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.

2010

- Regional Consecutive Leader Election in Mobile Ad-Hoc Networks

Hyun Chul Chung, Peter Robinson, Jennifer L. Welch. 6th ACM SIGACT/SIGMOBILE Workshop on Foundations of Mobile Computing (DIALM-POMC 2010).

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.

AbstractThis 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. Below is a (non-comprehensive) list of software that I have written.

- I extended Haskell's Cabal, for using a "world" file to keep track of installed packages. (Now part of the main distribution.)
- 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.
- In my master thesis I developed a system for automatically constructing events out of log files produced by various system programs. One of the core components of my work was a part-of-speech (POS) tagger, which assigns word classes (e.g. noun, verb) to the previously parsed tokens of the log file. To cope with noisy input data, I modeled the POS tagger as a hidden Markov model. I developed (and proved the correctness of) a variant of the maximum likelihood estimation algorithm for training the Markov model and smoothing the state transition distributions.

## Misc

- On program committee of: PODC 2018, BGP 2017, ICDCN 2016, SPAA 2016, SIROCCO 2016, ICDCN 2015, SIROCCO 2014, FOMC 2014.
- DBLP entry (Shows a subset of my publications.)
- Google scholar profile
- My profile on StackExchange