{"title":"Session details: Session 12","authors":"J. Sifakis","doi":"10.1145/3246726","DOIUrl":"https://doi.org/10.1145/3246726","url":null,"abstract":"","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114657846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Session 11","authors":"P. Kuznetsov","doi":"10.1145/3246725","DOIUrl":"https://doi.org/10.1145/3246725","url":null,"abstract":"","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121829665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A dual container has the property that when it is empty, the remove method will insert an explicit reservation (antidata) into the container, rather than returning an error flag. This convention gives the container explicit control over the order in which pending requests will be satisfied once data becomes available. The dual pattern also allows the method's caller to spin on a thread-local flag, avoiding memory contention. In this paper we introduce a new nonblocking construction that allows any nonblocking container for data to be paired with almost any nonblocking container for antidata. This construction provides a composite ordering discipline - e.g., it can satisfy pending pops from a stack in FIFO order, or satisfy pending dequeues in order of thread priority.
{"title":"Brief announcement: a generic construction for nonblocking dual containers","authors":"Joseph Izraelevitz, M. Scott","doi":"10.1145/2611462.2611510","DOIUrl":"https://doi.org/10.1145/2611462.2611510","url":null,"abstract":"A dual container has the property that when it is empty, the remove method will insert an explicit reservation (antidata) into the container, rather than returning an error flag. This convention gives the container explicit control over the order in which pending requests will be satisfied once data becomes available. The dual pattern also allows the method's caller to spin on a thread-local flag, avoiding memory contention. In this paper we introduce a new nonblocking construction that allows any nonblocking container for data to be paired with almost any nonblocking container for antidata. This construction provides a composite ordering discipline - e.g., it can satisfy pending pops from a stack in FIFO order, or satisfy pending dequeues in order of thread priority.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"360 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122728290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Session 10","authors":"P. Spirakis","doi":"10.1145/3246724","DOIUrl":"https://doi.org/10.1145/3246724","url":null,"abstract":"","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114294253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper considers how to use futures, a well-known mechanism to manage parallel computations, to improve the performance of long-lived, mutable shared data structures in large-scale multicore systems. We show that futures can enable type-specific optimizations such as combining and elimination, improve cache locality and reduce contention. To exploit these benefits in an effective way, however, it is important to define clear notions of correctness. We propose new extensions to linearizability appropriate for method calls that return futures as results. To illustrate the utility and trade-offs of these extensions, we describe implementations of three common data structures: stacks, queues, and linked lists, designed to exploit futures. Our experimental results show that optimizations enabled by futures lead to substantial performance improvements, in some cases up to two orders of magnitude, compared to well-known lock-free alternatives.
{"title":"The future(s) of shared data structures","authors":"Alex Kogan, M. Herlihy","doi":"10.1145/2611462.2611496","DOIUrl":"https://doi.org/10.1145/2611462.2611496","url":null,"abstract":"This paper considers how to use futures, a well-known mechanism to manage parallel computations, to improve the performance of long-lived, mutable shared data structures in large-scale multicore systems. We show that futures can enable type-specific optimizations such as combining and elimination, improve cache locality and reduce contention. To exploit these benefits in an effective way, however, it is important to define clear notions of correctness. We propose new extensions to linearizability appropriate for method calls that return futures as results. To illustrate the utility and trade-offs of these extensions, we describe implementations of three common data structures: stacks, queues, and linked lists, designed to exploit futures. Our experimental results show that optimizations enabled by futures lead to substantial performance improvements, in some cases up to two orders of magnitude, compared to well-known lock-free alternatives.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114619069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A t-ruling set of a graph G = (V, E) is a vertex-subset S ⊆ V that is independent and satisfies the property that every vertex v ∈ V is at a distance of at most t hops from some vertex in S. A maximal independent set (MIS) is a 1-ruling set. Extending results from Kothapalli et al. (FSTTCS 2012) this note presents a randomized algorithm for computing, with high probability, a t-ruling set in O(t ⋅ log1/(t-1)n) rounds for 2 < t ≤ √(log log n) and in (O(√(log log n))) rounds for t > √(log log n).
{"title":"Brief announcement: Super-fast t-ruling sets","authors":"Tushar Bisht, Kishore Kothapalli, S. Pemmaraju","doi":"10.1145/2611462.2611512","DOIUrl":"https://doi.org/10.1145/2611462.2611512","url":null,"abstract":"A t-ruling set of a graph G = (V, E) is a vertex-subset S ⊆ V that is independent and satisfies the property that every vertex v ∈ V is at a distance of at most t hops from some vertex in S. A maximal independent set (MIS) is a 1-ruling set. Extending results from Kothapalli et al. (FSTTCS 2012) this note presents a randomized algorithm for computing, with high probability, a t-ruling set in O(t ⋅ log1/(t-1)n) rounds for 2 < t ≤ √(log log n) and in (O(√(log log n))) rounds for t > √(log log n).","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122249846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent work established that some restricted-use objects, such as max registers, counters and atomic snapshots, admit polylogarithmic step-/complexity wait-free implementations using only reads and writes: when only polynomially-many updates are allowed, reading the object (by performing a ReadMax, CounterRead or Scan operation, depending on the object's type) incurs O(log N) steps (where N is the number of processes), which was shown to be optimal. But what about the step-/complexity of update operations? With these implementations, updating the object's state (by performing a WriteMax, Counter Increment or Update operation, depending on the object's type) requires Ω(log N) steps. The question that we address in this work is the following: are there read-optimal implementations of these restricted-use objects for which the asymptotic step-/complexity of update operations is sub-logarithmic? We present tradeoffs between the step-/complexity of read and update operations on these objects, establishing that updating a read-optimal counter or snapshot incurs Ω(log N) steps. These tradeoffs hold also if compare-and-swap (CAS) operations may be used, in addition to reads and writes. We also derive a tradeoff between the step-complexities of read and update operations of M-bounded max registers: if the step-/complexity of the Read-Max operation is O(f(min(N,M))), then the step-/complexity of the Write-Max operation is Ω(log log min(N,M)/log f(min(N,M))). It follows from this tradeoff that the step-/complexity of Write-Max in any read-/optimal implementation of a max register from read, write and CAS is Ω(log log min(N,M)). On the positive side, we present a wait-free implementation of an M-bounded max register from read, write and CAS for which the step complexities of Read-Max and Write-Max operations are O(1) and O(log min(N,M)), respectively.
{"title":"Complexity tradeoffs for read and update operations","authors":"Danny Hendler, V. Khait","doi":"10.1145/2611462.2611472","DOIUrl":"https://doi.org/10.1145/2611462.2611472","url":null,"abstract":"Recent work established that some restricted-use objects, such as max registers, counters and atomic snapshots, admit polylogarithmic step-/complexity wait-free implementations using only reads and writes: when only polynomially-many updates are allowed, reading the object (by performing a ReadMax, CounterRead or Scan operation, depending on the object's type) incurs O(log N) steps (where N is the number of processes), which was shown to be optimal. But what about the step-/complexity of update operations? With these implementations, updating the object's state (by performing a WriteMax, Counter Increment or Update operation, depending on the object's type) requires Ω(log N) steps. The question that we address in this work is the following: are there read-optimal implementations of these restricted-use objects for which the asymptotic step-/complexity of update operations is sub-logarithmic? We present tradeoffs between the step-/complexity of read and update operations on these objects, establishing that updating a read-optimal counter or snapshot incurs Ω(log N) steps. These tradeoffs hold also if compare-and-swap (CAS) operations may be used, in addition to reads and writes. We also derive a tradeoff between the step-complexities of read and update operations of M-bounded max registers: if the step-/complexity of the Read-Max operation is O(f(min(N,M))), then the step-/complexity of the Write-Max operation is Ω(log log min(N,M)/log f(min(N,M))). It follows from this tradeoff that the step-/complexity of Write-Max in any read-/optimal implementation of a max register from read, write and CAS is Ω(log log min(N,M)). On the positive side, we present a wait-free implementation of an M-bounded max register from read, write and CAS for which the step complexities of Read-Max and Write-Max operations are O(1) and O(log min(N,M)), respectively.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132061852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matteo Maffei, Giulio Malavolta, M. Reinert, Dominique Schröder
Cloud storage has rapidly acquired popularity among users, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. This technology, however, puts user data in the direct control of cloud service providers, which raises increasing security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. We present GORAM, a cryptographic system that protects the secrecy and integrity of the data outsourced to an untrusted server and guarantees the anonymity and unlinkability of consecutive accesses to such data. GORAM allows the database owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. Technically, GORAM builds on a combination of ORAM to conceal data accesses, attribute-based encryption to rule the access to outsourced data, and zero-knowledge proofs to prove read and write permissions in a privacy-preserving manner. We implemented GORAM and conducted an experimental evaluation to demonstrate its feasibility.
{"title":"Brief announcement: towards security and privacy for outsourced data in the multi-party setting","authors":"Matteo Maffei, Giulio Malavolta, M. Reinert, Dominique Schröder","doi":"10.1145/2611462.2611508","DOIUrl":"https://doi.org/10.1145/2611462.2611508","url":null,"abstract":"Cloud storage has rapidly acquired popularity among users, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. This technology, however, puts user data in the direct control of cloud service providers, which raises increasing security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. We present GORAM, a cryptographic system that protects the secrecy and integrity of the data outsourced to an untrusted server and guarantees the anonymity and unlinkability of consecutive accesses to such data. GORAM allows the database owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. Technically, GORAM builds on a combination of ORAM to conceal data accesses, attribute-based encryption to rule the access to outsourced data, and zero-knowledge proofs to prove read and write permissions in a privacy-preserving manner. We implemented GORAM and conducted an experimental evaluation to demonstrate its feasibility.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134551378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Backes, Fabian Bendun, Ashish Choudhury, Aniket Kate
Multiparty computation (MPC) among n parties can tolerate up to t < n/2 active corruptions in a synchronous communication setting; however, in an asynchronous communication setting, the resiliency bound decreases to only t < n/3 active corruptions. We improve the resiliency bound for asynchronous MPC (AMPC) to match synchronous MPC using non-equivocation. Non-equivocation is a message authentication mechanism to restrict a corrupted sender from making conflicting statements to different (honest) parties. It can be implemented using an increment-only counter and a digital signature oracle, realizable with trusted hardware modules readily available in commodity computers and smartphone devices. A non-equivocation mechanism can also be transferable and allows a receiver to verifiably transfer the authenticated statement to other parties. In this work, using transferable non-equivocation, we present an AMPC protocol tolerating t < n/2 faults. From a practical point of view, our AMPC protocol requires fewer setup assumptions than the previous AMPC protocol with t < n/2 by Beerliova-Trubiniova, Hirt and Nielsen [PODC 2010]: unlike their AMPC protocol, it does not require any synchronous broadcast round at the beginning of the protocol and avoids the threshold homomorphic encryption setup assumption. Moreover, our AMPC protocol is also efficient and provides a gain of Θ(n) in the communication complexity per multiplication gate, over the AMPC protocol of Beerliova-Trubiniova et al. In the process, using non-equivocation, we also define the first asynchronous verifiable secret sharing (AVSS) scheme with t < n/2, which is of independent interest to threshold cryptography.
{"title":"Asynchronous MPC with a strict honest majority using non-equivocation","authors":"M. Backes, Fabian Bendun, Ashish Choudhury, Aniket Kate","doi":"10.1145/2611462.2611490","DOIUrl":"https://doi.org/10.1145/2611462.2611490","url":null,"abstract":"Multiparty computation (MPC) among n parties can tolerate up to t < n/2 active corruptions in a synchronous communication setting; however, in an asynchronous communication setting, the resiliency bound decreases to only t < n/3 active corruptions. We improve the resiliency bound for asynchronous MPC (AMPC) to match synchronous MPC using non-equivocation. Non-equivocation is a message authentication mechanism to restrict a corrupted sender from making conflicting statements to different (honest) parties. It can be implemented using an increment-only counter and a digital signature oracle, realizable with trusted hardware modules readily available in commodity computers and smartphone devices. A non-equivocation mechanism can also be transferable and allows a receiver to verifiably transfer the authenticated statement to other parties. In this work, using transferable non-equivocation, we present an AMPC protocol tolerating t < n/2 faults. From a practical point of view, our AMPC protocol requires fewer setup assumptions than the previous AMPC protocol with t < n/2 by Beerliova-Trubiniova, Hirt and Nielsen [PODC 2010]: unlike their AMPC protocol, it does not require any synchronous broadcast round at the beginning of the protocol and avoids the threshold homomorphic encryption setup assumption. Moreover, our AMPC protocol is also efficient and provides a gain of Θ(n) in the communication complexity per multiplication gate, over the AMPC protocol of Beerliova-Trubiniova et al. In the process, using non-equivocation, we also define the first asynchronous verifiable secret sharing (AVSS) scheme with t < n/2, which is of independent interest to threshold cryptography.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127431032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linear sketching is a popular technique for computing in dynamic streams, where one needs to handle both insertions and deletions of elements. The underlying idea of taking randomized linear measurements of input data has been extremely successful in providing space-efficient algorithms for classical problems such as frequency moment estimation and computing heavy hitters, and was very recently shown to be a powerful technique for solving graph problems in dynamic streams [AGM'12]. Ideally, one would like to obtain algorithms that use one or a small constant number of passes over the data and a small amount of space (i.e. sketching dimension) to preserve some useful properties of the input graph presented as a sequence of edge insertions and edge deletions. In this paper, we concentrate on the problem of constructing linear sketches of graphs that (approximately) preserve the spectral information of the graph in a few passes over the stream. We do so by giving the first sketch-based algorithm for constructing multiplicative graph spanners in only two passes over the stream. Our spanners use ~O(n1+1/k) bits of space and have stretch 2k. While this stretch is larger than the conjectured optimal 2k-1 for this amount of space, we show for an appropriate k that it implies the first 2-pass spectral sparsifier with n1+o(1) bits of space. Previous constructions of spectral sparsifiers in this model with a constant number of passes would require n1+c bits of space for a constant c > 0. We also give an algorithm for constructing spanners that provides an additive approximation to the shortest path metric using a single pass over the data stream, also achieving an essentially best possible space/approximation tradeoff.
{"title":"Spanners and sparsifiers in dynamic streams","authors":"M. Kapralov, David P. Woodruff","doi":"10.1145/2611462.2611497","DOIUrl":"https://doi.org/10.1145/2611462.2611497","url":null,"abstract":"Linear sketching is a popular technique for computing in dynamic streams, where one needs to handle both insertions and deletions of elements. The underlying idea of taking randomized linear measurements of input data has been extremely successful in providing space-efficient algorithms for classical problems such as frequency moment estimation and computing heavy hitters, and was very recently shown to be a powerful technique for solving graph problems in dynamic streams [AGM'12]. Ideally, one would like to obtain algorithms that use one or a small constant number of passes over the data and a small amount of space (i.e. sketching dimension) to preserve some useful properties of the input graph presented as a sequence of edge insertions and edge deletions. In this paper, we concentrate on the problem of constructing linear sketches of graphs that (approximately) preserve the spectral information of the graph in a few passes over the stream. We do so by giving the first sketch-based algorithm for constructing multiplicative graph spanners in only two passes over the stream. Our spanners use ~O(n1+1/k) bits of space and have stretch 2k. While this stretch is larger than the conjectured optimal 2k-1 for this amount of space, we show for an appropriate k that it implies the first 2-pass spectral sparsifier with n1+o(1) bits of space. Previous constructions of spectral sparsifiers in this model with a constant number of passes would require n1+c bits of space for a constant c > 0. We also give an algorithm for constructing spanners that provides an additive approximation to the shortest path metric using a single pass over the data stream, also achieving an essentially best possible space/approximation tradeoff.","PeriodicalId":186800,"journal":{"name":"Proceedings of the 2014 ACM symposium on Principles of distributed computing","volume":"67 3-4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133750848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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