Peter Robinson
I'm interested in designing new distributed and parallel algorithms, the distributed processing of big data, achieving faulttolerance in networks, and secure distributed computing in dynamic environments such as peertopeer networks and mobile adhoc networks.
News
 General Chair of ACM PODC 2019
 Program committee member of BGP 2017, SPAA 2016 and of SIROCCO 2016
 Giving a talk at a workshop on Dynamic Graphs in Distributed Computing (colocated with DISC 2016)
 Cochairing the program committee of ICDCN 2016
 Giving a talk at ADGA 2015, (4th Workshop on Advances in Distributed Graph Algorithms, colocated with DISC 2015 )
Keywords (Show all)
«Asynchrony» «Big Data» «Byzantine Failures» «Churn» «Communication Complexity» «Distributed Agreement» «Distributed Storage» «Dynamic Network» «FaultTolerance» «Gossip Communication» «Graph Algorithm» «Haskell» «Leader Election» «Machine Learning» «Mobile AdHoc Network» «Natural Language Processing» «P2P» «Secure Computation» «SelfHealing» «Symmetry Breaking»Publications tagged with "P2P" (Show all)
2016

DEX: SelfHealing Expanders
DOI
Gopal Pandurangan, Peter Robinson, Amitabh Trehan. Distributed Computing (DC).
Abstract...We present a fullydistributed selfhealing 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 allpowerful 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 selfhealing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes.
2015

Enabling Efficient and Robust Distributed Computation in Highly Dynamic Networks
DOI
John Augustine, Gopal Pandurangan, Peter Robinson, Scott Roche, Eli Upfal. 56th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2015).
Abstract...Motivated by the need for designing efficient and robust fullydistributed computation in highly dynamic networks such as PeertoPeer (P2P) networks, we study distributed protocols for constructing and maintaining dynamic network topologies with good expansion properties. Our goal is to maintain a sparse (bounded degree) expander topology despite heavy churn (i.e., nodes joining and leaving the network continuously over time). We assume that the churn is controlled by an 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. Our main contribution is a randomized distributed protocol that guarantees with high probability the maintenance of a constant degree graph with high expansion even under continuous high adversarial churn. Our protocol can tolerate a churn rate of up to $O(n/\text{polylog}(n))$ per round (where $n$ is the stable network size). Our protocol is efficient, lightweight, and scalable, and it incurs only $O(\text{polylog}(n))$ overhead for topology maintenance: only polylogarithmic (in $n$) bits needs to be processed and sent by each node per round and any node's computation cost per round is also polylogarithmic. The given protocol is a fundamental ingredient that is needed for the design of efficient fullydistributed algorithms for solving fundamental distributed computing problems such as agreement, leader election, search, and storage in highly dynamic P2P networks and enables fast and scalable algorithms for these problems that can tolerate a large amount of churn.
2014

DEX: SelfHealing Expanders
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DOI
Gopal Pandurangan, Peter Robinson, Amitabh Trehan. 28th IEEE International Parallel Distributed Processing Symposium (IPDPS 2014).
Abstract...We present a fullydistributed selfhealing 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 allpowerful 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 selfhealing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes. 
Distributed Agreement in Dynamic PeertoPeer Networks
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DOI
John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal. Journal of Computer and System Sciences, Elsevier. (JCSS).
2013

Search and Storage in Dynamic PeertoPeer Networks
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DOI
John Augustine, Anisur Molla, Ehab Morsy, Gopal Pandurangan, Peter Robinson, Eli Upfal. 25th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2013).
Abstract...We study robust and efficient distributed algorithms for searching, storing, and maintaining data in dynamic PeertoPeer (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 firstknown, fullydistributed 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.
2012

Towards Robust and Efficient Computation in Dynamic PeertoPeer Networks
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DOI
John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal. 23rd ACMSIAM Symposium on Discrete Algorithms (SODA 2012).
Abstract...Motivated by the need for robust and fast distributed computation in highly dynamic PeertoPeer (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 almosteverywhere 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 almosteverywhere 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 almosteverywhere 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 almosteverywhere agreement (regardless of the number of rounds), even under constant churn rate. \end{enumerate} Our algorithms are the firstknown, fullydistributed, 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 nontrivial distributed computing tasks in dynamic P2P networks.
Code
I'm interested in parallel and distributed programming and related technologies such as software transactional memory. Below is a (noncomprehensive) list of software that I have written.
 I extended 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 spaceoptimal.
 secret sharing: an implementation of a secret sharing scheme that provides informationtheoretic security.
 diceentropy: a library that provides cryptographically secure dice rolls implemented by bitefficient rejection sampling.
 TSkipList: a data structure with rangequery support for software transactional memory.
 stmiohooks: 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 partofspeech (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
 Conferences that I attended so far: PODC 2008 (Toronto, Canada); SSS 2008 (Detroit, USA); OPODIS 2009 (Nimes, France); ALGOSENSORS 2010 (Bordeaux, France); DISC 2010; (Boston, USA) IPDPS 2011 (Anchorage, USA); FOMC 2011 (San Jose, USA); SODA 2012 (Kyoto, Japan); SIROCCO 2012 (Reykjavik, Iceland); ICDCN 2013 (Mumbai, India); ICALP 2013 (Riga, Latvia); SPAA 2013 (Montreal, Canada); PODC 2013 (Montreal, Canada); Shonan Workshop (Shonan Village, Japan); DISC 2015 (Tokyo, Japan); ICDCN 2016 (Singapore); SPAA 2016 (Monterey, California); DISC 2016 (Paris, France).
 Program committee membership: BGP 2017, ICDCN 2016, SPAA 2016, SIROCCO 2016, ICDCN 2015, SIROCCO 2014, FOMC 2014
 DBLP entry.
 Google Scholar profile.
 Profile on StackExchange.