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

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

Identifying At-Risk Students: An Assessment Instrument for Distributed Learning Courses in Higher Education

The current period of rapid technological change, particularly in the area of mediated communication, has combined with new philosophies of education and market forces to bring upheaval to the realm of higher education. Technical capabilities exceed our knowledge of whether expenditures on hardware and software lead to corresponding gains in student learning. Educators do not yet possess sophisticated assessments of what we may be gaining or losing as we widen the scope of distributed learning. The purpose of this study was not to draw sweeping conclusions with respect to the costs or benefits of technology in education. The researcher focused on a single issue involved in educational quality: assessing the ability of a student to complete a course. Previous research in this area indicates that attrition rates are often higher in distributed learning environments. Educators and students may benefit from a reliable instrument to identify those students who may encounter difficulty in these learning situations. This study is aligned with research focused on the individual engaged in seeking information, assisted or hindered by the capabilities of the computer information systems that create and provide access to information. Specifically, the study focused on the indicators of completion for students enrolled in video conferencing and Web-based courses. In the final version, the Distributed Learning Survey encompassed thirteen indicators of completion. The results of this study of 396 students indicated that the Distributed Learning Survey represented a reliable and valid instrument for identifying at-risk students in video conferencing and Web-based courses where the student population is similar to the study participants. Educational level, GPA, credit hours taken in the semester, study environment, motivation, computer confidence, and the number of previous distributed learning courses accounted for most of the predictive power in the discriminant function based on student scores from the survey

Wireless industrial monitoring and control networks: the journey so far and the road ahead

While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks