Partially ordered distributed computations on asynchronous point-to-point networks

Asynchronous executions of a distributed algorithm differ from each other due to the nondeterminism in the order in which the messages exchanged are handled. In many situations of interest, the asynchronous executions induced by restricting nondeterminism are more efficient, in an application-specific sense, than the others. In this work, we define partially ordered executions of a distributed algorithm as the executions satisfying some restricted orders of their actions in two different frameworks, those of the so-called event- and pulse-driven computations. The aim of these restrictions is to characterize asynchronous executions that are likely to be more efficient for some important classes of applications. Also, an asynchronous algorithm that ensures the occurrence of partially ordered executions is given for each case. Two of the applications that we believe may benefit from the restricted nondeterminism are backtrack search, in the event-driven case, and iterative algorithms for systems of linear equations, in the pulse-driven case

The Role of Structural Reflection in Distributed Virtual Reality

The emergence of collaborative virtual world applications that run over the Internet has presented Virtual Reality (VR) application designers with new challenges. In an environment where the public internet streams multimedia data and is constantly under pressure to deliver over widely heterogeneous user-platforms, there has been a growing need that distributed virtual world applications be aware of and adapt to frequent variations in their context of execution. In this paper, we argue that in contrast to research efforts targeted at improvement of scalability, persistence and responsiveness capabilities, much less attempts have been aimed at addressing the flexibility, maintainability and extensibility requirements in contemporary Distributed VR applications. We propose the use of structural reflection as an approach that not only addresses these requirements but also offers added value in the form of providing a framework for scalability, persistence and responsiveness that is itself flexible, maintainable and extensible

VCube-PS: A Causal Broadcast Topic-based Publish/Subscribe System

In this work we present VCube-PS, a topic-based Publish/Subscribe system built on the top of a virtual hypercube-like topology. Membership information and published messages are broadcast to subscribers (members) of a topic group over dynamically built spanning trees rooted at the publisher. For a given topic, the delivery of published messages respects the causal order. VCube-PS was implemented on the PeerSim simulator, and experiments are reported including a comparison with the traditional Publish/Subscribe approach that employs a single rooted static spanning-tree for message distribution. Results confirm the efficiency of VCube-PS in terms of scalability, latency, number and size of messages.Comment: Improved text and performance evaluation. Added proof for the algorithms (Section 3.4

Survey on the Event Orderings Semantics Used for Distributed System

Event ordering in distributed system (DS) is disputable and proactive subject in DS particularly with the emergence of multimedia synchronization. According to the literature, different type of event ordering is used for different DS mode such as asynchronous or synchronous. Recently, there are several novel implementation of these types introduced to fulfill the demand for establishing a certain order according to a specific criterion in DS with lighter complexity.Comment: 9 page

Total order in opportunistic networks

Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.Peer ReviewedPostprint (author's final draft

Scalability approaches for causal multicast: a survey

The final publication is available at Springer via http://dx.doi.org/10.1007/s00607-015-0479-0Many distributed services need to be scalable: internet search, electronic commerce, e-government... In order to achieve scalability, high availability and fault tolerance, such applications rely on replicated components. Because of the dynamics of growth and volatility of customer markets, applications need to be hosted by adaptive, highly scalable systems. In particular, the scalability of the reliable multicast mechanisms used for supporting the consistency of replicas is of crucial importance. Reliable multicast might propagate updates in a pre-determined order (e.g., FIFO, total or causal). Since total order needs more communication rounds than causal order, the latter appears to be the preferable candidate for achieving multicast scalability, although the consistency guarantees based on causal order are weaker than those of total order. This paper provides a historical survey of different scalability approaches for reliable causal multicast protocols.This work was supported by European Regional Development Fund (FEDER) and Ministerio de Economia y Competitividad (MINECO) under research Grant TIN2012-37719-C03-01.Juan Marín, RD.; Decker, H.; Armendáriz Íñigo, JE.; Bernabeu Aubán, JM.; Muñoz Escoí, FD. (2016). Scalability approaches for causal multicast: a survey. Computing. 98(9):923-947. https://doi.org/10.1007/s00607-015-0479-0S923947989Adly N, Nagi M (1995) Maintaining causal order in large scale distributed systems using a logical hierarchy. In: IASTED Intnl Conf on Appl Inform, pp 214–219Aguilera MK, Chen W, Toueg S (1997) Heartbeat: a timeout-free failure detector for quiescent reliable communication. In: 11th Intnl Wshop on Distrib Alg (WDAG), Saarbrücken, pp 126–140Almeida JB, Almeida PS, Baquero C (2004) Bounded version vectors. In: 18th Intnl Conf Distrib Comput (DISC), Amsterdam, pp 102–116Almeida PS, Baquero C, Fonte V (2008) Interval tree clocks. In: 12th Intnl Conf Distrib Syst (OPODIS), Luxor, pp 259–274Almeida S, Leitão J, Rodrigues LET (2013) ChainReaction: a causal+ consistent datastore based on chain replication. In: 8th EuroSys Conf, Czech Republic, pp 85–98Álvarez A, Arévalo S, Cholvi V, Fernández A, Jiménez E (2008) On the interconnection of message passing systems. Inf Process Lett 105(6):249–254Amir Y, Stanton J (1998) The Spread wide area group communication system. Tech. rep., CDNS-98-4, The Center for Networking and Distributed Systems, The Johns Hopkins UnivAmir Y, Dolev D, Kramer S, Malki D (1992) Transis: a communication subsystem for high availability. In: 22nd Intnl Symp Fault-Tolerant Comp (FTCS), Boston, pp 76–84Anastasi G, Bartoli A, Spadoni F (2001) A reliable multicast protocol for distributed mobile systems: design and evaluation. IEEE Trans Parallel Distrib Syst 12(10):1009–1022Bailis P, Ghodsi A, Hellerstein JM, Stoica I (2013) Bolt-on causal consistency. In: Intnl Conf Mgmnt Data (SIGMOD), New York, pp 761–772Baldoni R, Raynal M, Prakash R, Singhal M (1996) Broadcast with time and causality constraints for multimedia applications. In: 22nd Intnl Euromicro Conf, Prague, pp 617–624Baldoni R, Friedman R, van Renesse R (1997) The hierarchical daisy architecture for causal delivery. In: 17th Intnl Conf Distrib Comput Syst (ICDCS), Maryland, pp 570–577Ban B (2002) JGroups—a toolkit for reliable multicast communication. http://www.jgroups.orgBaquero C, Almeida PS, Shoker A (2014) Making operation-based CRDTs operation-based. In: 14th Intnl Conf Distrib Appl Interop Syst (DAIS), Berlin, pp 126–140Benslimane A, Abouaissa A (2002) Dynamical grouping model for distributed real time causal ordering. Comput Commun 25:288–302Birman KP, Joseph TA (1987) Reliable communication in the presence of failures. ACM Trans Comput Syst 5(1):47–76Birman KP, Schiper A, Stephenson P (1991) Lightweigt causal and atomic group multicast. ACM Trans Comput Syst 9(3):272–314Cachin C, Guerraoui R, Rodrigues LET (2011) Introduction to reliable and secure distributed programming, 2nd edn. Springer, BerlinChandra P, Gambhire P, Kshemkalyani AD (2004) Performance of the optimal causal multicast algorithm: a statistical analysis. IEEE Trans Parall Distr 15(1):40–52Chandra TD, Toueg S (1996) Unreliable failure detectors for reliable distributed systems. J ACM 43(2):225–267de Juan-Marín R, Cholvi V, Jiménez E, Muñoz-Escoí FD (2009) Parallel interconnection of broadcast systems with multiple FIFO channels. In: 11th Intnl Symp on Distrib Obj, Middleware and Appl (DOA), Vilamoura, LNCS, vol 5870, pp 449–466Défago X, Schiper A, Urbán P (2004) Total order broadcast and multicast algorithms: taxonomy and survey. ACM Comput Surv 36(4):372–421Demers AJ, Greene DH, Hauser C, Irish W, Larson J, Shenker S, Sturgis HE, Swinehart DC, Terry DB (1987) Epidemic algorithms for replicated database maintenance. In: 6th ACM Symp on Princ of Distrib Comput (PODC), Canada, pp 1–12Du J, Elnikety S, Roy A, Zwaenepoel W (2013) Orbe: scalable causal consistency using dependency matrices and physical clocks. In: ACM Symp on Cloud Comput (SoCC), Santa Clara, pp 11:1–11:14Fernández A, Jiménez E, Cholvi V (2000) On the interconnection of causal memory systems. In: 19th Annual ACM Symp on Princ of Distrib Comput (PODC), Portland, pp 163–170Fidge CJ (1988) Timestamps in message-passing systems that preserve the partial ordering. In: 11th Australian Comput Conf, pp 56–66Friedman R, Vitenberg R, Chockler G (2003) On the composability of consistency conditions. Inf Process Lett 86(4):169–176Gilbert S, Lynch N (2002) Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33(2):51–59Gray J, Helland P, O’Neil PE, Shasha D (1996) The dangers of replication and a solution. In: SIGMOD Conf, pp 173–182Hadzilacos V, Toueg S (1993) Fault-tolerant broadcasts and related problems. In: Mullender S (ed) Distributed systems, chap 5, 2nd edn. ACM Press, pp 97–145Johnson S, Jahanian F, Shah J (1999) The inter-group router approach to scalable group composition. In: 19th Intnl Conf on Distrib Comput Syst (ICDCS), Austin, pp 4–14Kalantar MH, Birman KP (1999) Causally ordered multicast: the conservative approach. In: 19th Intnl Conf on Distrib Comput Syst (ICDCS), Austin, pp 36–44Kawanami S, Enokido T, Takizawa M (2004) A group communication protocol for scalable causal ordering. In: 18th Intnl Conf on Adv Inform Netw Appl (AINA), Fukuoka, pp 296–302Kawanami S, Nishimura T, Enokido T, Takizawa M (2005) A scalable group communication protocol with global clock. In: 19th Intnl Conf on Adv Inform Netw Appl (AINA), Taipei, pp 625–630Kshemkalyani AD, Singhal M (1998) Necessary and sufficient conditions on information for causal message ordering and their optimal implementation. Distrib Comput 11(2):91–111Kshemkalyani AD, Singhal M (2011) Distributed computing: principles, algorithms, and systems, 2nd edn. Cambridge University Press, New YorkLadin R, Liskov B, Shrira L, Ghemawat S (1992) Providing high availability using lazy replication. ACM Trans Comput Syst 10(4):360–391Lamport L (1978) Time, clocks, and the ordering of events in a distributed system. Commun ACM 21(7):558–565Laumay P, Bruneton E, de Palma N, Krakowiak S (2001) Preserving causality in a scalable message-oriented middleware. In: Intnl Conf on Distrib Syst Platf (Middleware), pp 311–328Liu N, Liu M, Cao J, Chen G, Lou W (2010) When transportation meets communication: V2P over VANETs. In: 30th Intnl Conf Distrib Comput Syst (ICDCS), GenovaLwin CH, Mohanty H, Ghosh RK (2004) Causal ordering in event notification service systems for mobile users. In: Intnl Conf Inform Tech: Coding Comput (ITCC), Las Vegas, pp 735–740Mahajan P, Alvisi L, Dahlin M (2011) Consistency, availability and covergence. Tech. rep., UTCS TR-11-22, The University of Texas at AustinMatos M, Sousa A, Pereira J, Oliveira R, Deliot E, Murray P (2009) CLON: overlay networks and gossip protocols for cloud environments. In: 11th Intnl Symp on Dist Obj, Middleware and Appl (DOA), Vilamoura, LNCS, vol 5870, pp 549–566Mattern F (1989) Virtual time and global states of distributed systems. In: Parallel and distributed algorithms, North-Holland, pp 215–226Mattern F, Fünfrocken S (1994) A non-blocking lightweight implementation of causal order message delivery. Lect Notes Comput Sci 938:197–213Meldal S, Sankar S, Vera J (1991) Exploiting locality in maintaining potential causality. In: 10th ACM Symp on Princ of Distrib Comp (PODC), Montreal, pp 231–239Meling H, Montresor A, Helvik BE, Babaoglu Ö (2008) Jgroup/ARM: a distributed object group platform with autonomous replication management. Softw Pract Exp 38(9):885–923Mosberger D (1993) Memory consistency models. Oper Syst Rev 27(1):18–26Mostéfaoui A, Raynal M (1993) Causal multicast in overlapping groups: towards a low cost approach. In: 4th Intnl Wshop on Future Trends of Distrib Comp Syst (FTDCS), Lisbon, pp 136–142Mostéfaoui A, Raynal M, Travers C, Patterson S, Agrawal D, El Abbadi A (2005) From static distributed systems to dynamic systems. In: 24th Symp on Rel Distrib Syst (SRDS), Orlando, pp 109–118Nishimura T, Hayashibara N, Takizawa M, Enokido T (2005) Causally ordered delivery with global clock in hierarchical group. In: ICPADS (2), Fukuoka, pp 560–564Parker DS Jr, Popek GJ, Rudisin G, Stoughton A, Walker BJ, Walton E, Chow JM, Edwards DA, Kiser S, Kline CS (1983) Detection of mutual inconsistency in distributed systems. IEEE Trans Softw Eng 9(3):240–247Pascual-Miret L (2014) Consistency models in modern distributed systems. An approach to eventual consistency. Master’s thesis, Depto. de Sistemas Informáticos y Computación, Univ. Politècnica de ValènciaPascual-Miret L, González de Mendívil JR, Bernabéu-Aubán JM, Muñoz-Escoí FD (2015) Widening CAP consistency. Tech. rep., IUMTI-SIDI-2015/003, Univ. Politècnica de València, ValenciaPeterson LL, Buchholz NC, Schlichting RD (1989) Preserving and using context information in interprocess communication. ACM Trans Comput Syst 7(3):217–246Pomares Hernández S, Fanchon J, Drira K, Diaz M (2001) Causal broadcast protocol for very large group communication systems. In: 5th Intnl Conf on Princ of Distrib Syst (OPODIS), Manzanillo, pp 175–188Prakash R, Baldoni R (2004) Causality and the spatial-temporal ordering in mobile systems. Mobile Netw Appl 9(5):507–516Prakash R, Raynal M, Singhal M (1997) An adaptive causal ordering algorithm suited to mobile computing environments. J Parallel Distrib Comput 41(2):190–204Raynal M, Schiper A, Toueg S (1991) The causal ordering abstraction and a simple way to implement it. Inf Process Lett 39(6):343–350Rodrigues L, Veríssimo P (1995a) Causal separators and topological timestamping: An approach to support causal multicast in large-scale systems. Tech. Rep. AR-05/95, Instituto de Engenharia de Sistemas e Computadores (INESC), LisbonRodrigues L, Veríssimo P (1995b) Causal separators for large-scale multicast communication. In: 15th Intnl Conf on Distrib Comput Syst (ICDCS), Vancouver, pp 83–91Schiper A, Eggli J, Sandoz A (1989) A new algorithm to implement causal ordering. In: 3rd Intnl Wshop on Distrib Alg (WDAG), Nice, pp 219–232Schiper N, Pedone F (2010) Fast, flexible and highly resilient genuine FIFO and causal multicast algorithms. In: 25th ACM Symp on Applied Comp (SAC), Sierre, pp 418–422Shapiro M, Preguiça NM, Baquero C, Zawirski M (2011) Convergent and commutative replicated data types. Bull EATCS 104:67–88Shen M, Kshemkalyani AD, Hsu TY (2015) Causal consistency for geo-replicated cloud storage under partial replication. In: Intnl Paral Distrib Proces Symp (IPDPS) Wshop, Hyderabad, pp 509–518Singhal M, Kshemkalyani AD (1992) An efficient implementation of vector clocks. Inf Process Lett 43(1):47–52Sotomayor B, Montero RS, Llorente IM, Foster IT (2009) Virtual infrastructure management in private and hybrid clouds. IEEE Internet Comput 13(5):14–22Stephenson P (1991) Fast ordered multicasts. PhD thesis, Dept. of Comp. Sc., Cornell Univ., IthacaStonebraker M (1986) The case for shared nothing. IEEE Database Eng Bull 9(1):4–9Vogels W (2009) Eventually consistent. Commun ACM 52(1):40–44Wischhof L, Ebner A, Rohling H (2005) Information dissemination in self-organizing intervehicle networks. IEEE Trans Intell Transp 6(1):90–101Yavatkar R (1992) MCP: a protocol for coordination and temporal synchronization in multimedia collaborative applications. In: 12th Intnl Conf on Distrib Comput Syst (ICDCS), Yokohama, pp 606–613Yen LH, Huang TL, Hwang SY (1997) A protocol for causally ordered message delivery in mobile computing systems. Mobile Netw Appl 2(4):365–372Zawirski M, Preguiça N, Duarte S, Bieniusa A, Balegas V, Shapiro M (2015) Write fast, read in the past: causal consistency for client-side applications. In: 16th Intnl Middleware Conf, VancouverZhou S, Cai W, Turner SJ, Lee BS, Wei J (2007) Critical causal order of events in distributed virtual environments. ACM Trans Mult Comp Commun Appl 3(3):1

Multimedia Multicast Transport Service for

Reliability carries different meanings for different applications. For example, in a replicated database setting, reliability means that messages are never lost, and that messages arrive in the same order at all sites. In order to guarantee this reliability property, it is acceptable to sacrifice real-time message delivery: some messages may be greatly delayed, and at certain periods message transmission may even be blocked. While this is perfectly acceptable behavior for a reliable database application, this behavior is intolerable for a reliable video server. For a continuous MPEG video player [20, 19], reliability means real-time message delivery, at a certain bandwidth; It is acceptable for some messages to be lost, as long as the available bandwidth complies with certain predetermined stochastic assumptions. Introducing database style reliability (i.e. message recovery and order constraints) may violate these assumptions, rendering the MPEG decoding algorithm incorrect. Many CSCW groupware and multimedia applications require quality of service multicast for most of their messages, and may greatly benefit from reliable multicast for a small portion of “critical ” messages. Furthermore, such applications often need to be fault-tolerant, and need to support smooth reconfiguration when parties join or leave

On Consistency and Network Latency in Distributed Interactive Applications: A Survey—Part I

This paper is the first part of a two-part paper that documents a detailed survey of the research carried out on consistency and latency in distributed interactive applications (DIAs) in recent decades. Part I reviews the terminology associated with DIAs and offers definitions for consistency and latency. Related issues such as jitter and fidelity are also discussed. Furthermore, the various consistency maintenance mechanisms that researchers have used to improve consistency and reduce latency effects are considered. These mechanisms are grouped into one of three categories, namely time management, Information management and system architectural management. This paper presents the techniques associated with the time management category. Examples of such mechanisms include time warp, lock step synchronisation and predictive time management. The remaining two categories are presented in part two of the survey