Adaptive Middleware for Data Replication

Dynamically adaptive systems sense their environment and adjust themselves to accommodate to changes in order to maximize performance. Depending on the type of change (e.g., modifications of the load, the type of workload, the available resources, the client distribution, etc.), different adjustments have to be made. Coordinating them is already difficult in a centralized system. Doing so in the currently prevalent component-based distributed systems is even more challenging. In this paper, we present an adaptive distributed middleware for data replication that is able to adjust to changes in the amount of load submitted to the different replicas and to the type of workload submitted. Its novelty lies in combining load-balancing techniques with feedback driven adjustments of multiprogramming levels (number of transactions that are allowed to execute concurrently). An extensive performance analysis shows that the proposed adaptive replication solution can provide high throughput, good scalability, and low response times for changing loads and workloads with little overhead.

[1]  Gerhard Weikum,et al.  Integrating Snapshot Isolation into Transactional Federation , 2000, CoopIS.

[2]  Gerhard Weikum,et al.  Performance Evaluation of an Adaptive and Robust Load Control Method for the Avoidance of Data-Contention Thrashing , 1992, VLDB.

[3]  Gustavo Alonso,et al.  Are quorums an alternative for data replication? , 2003, TODS.

[4]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[5]  Emmanuel Cecchet,et al.  RAIDb: Redundant Array of Inexpensive Databases , 2004, ISPA.

[6]  Henry F. Korth,et al.  Replication and consistency: being lazy helps sometimes , 1997, PODS.

[7]  Gustavo Alonso,et al.  Exploiting atomic broadcast in replicated databases , 1997 .

[8]  Sushil Jajodia,et al.  An adaptive data replication algorithm , 1997, TODS.

[9]  Alan L. Cox,et al.  Distributed Versioning: Consistent Replication for Scaling Back-End Databases of Dynamic Content Web Sites , 2003, Middleware.

[10]  Gustavo Alonso,et al.  Don't Be Lazy, Be Consistent: Postgres-R, A New Way to Implement Database Replication , 2000, VLDB.

[11]  Pedro Vicente,et al.  Strong Replication in the GlobData Middleware , 2002 .

[12]  Hans-Ulrich Heiß,et al.  Adaptive Load Control in Transaction Processing Systems , 1991, VLDB.

[13]  Gustavo Alonso,et al.  Ganymed: Scalable Replication for Transactional Web Applications , 2004, Middleware.

[14]  Mark Garland Hayden,et al.  The Ensemble System , 1998 .

[15]  Gustavo Alonso,et al.  A new approach to developing and implementing eager database replication protocols , 2000, TODS.

[16]  Avishai Wool,et al.  Replication, consistency, and practicality: are these mutually exclusive? , 1998, SIGMOD '98.

[17]  Dennis Shasha,et al.  The dangers of replication and a solution , 1996, SIGMOD '96.

[18]  Patrick Valduriez,et al.  Distributed and parallel database systems , 1996, CSUR.

[19]  Esther Pacitti,et al.  Replica Consistency in Lazy Master Replicated Databases , 2001, Distributed and Parallel Databases.

[20]  Miron Livny,et al.  Towards Automated Performance Tuning for Complex Workloads , 1994, VLDB.

[21]  G. Weikum,et al.  Integrating Snapshot Isolation Into Transactional Federations , 2000 .

[22]  Gustavo Alonso,et al.  Non-intrusive, parallel recovery of replicated data , 2002, 21st IEEE Symposium on Reliable Distributed Systems, 2002. Proceedings..

[23]  Asser N. Tantawi,et al.  Performance management for cluster-based web services , 2005, IEEE Journal on Selected Areas in Communications.

[24]  Yair Amir,et al.  From total order to database replication , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[25]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE , 2002, Lecture Notes in Computer Science.

[26]  Divyakant Agrawal,et al.  The performance of database replication with group multicast , 1999, Digest of Papers. Twenty-Ninth Annual International Symposium on Fault-Tolerant Computing (Cat. No.99CB36352).

[27]  Asser N. Tantawi,et al.  Performance management for cluster based Web services , 2003 .

[28]  AlonsoGustavo,et al.  A new approach to developing and implementing eager database replication protocols , 2000 .

[29]  Santosh K. Shrivastava,et al.  Component replication in distributed systems: a case study using Enterprise Java Beans , 2003, 22nd International Symposium on Reliable Distributed Systems, 2003. Proceedings..

[30]  Gustavo Alonso,et al.  Scalable Replication in Database Clusters , 2000, DISC.

[31]  Alan L. Cox,et al.  Scaling and Availability for Dynamic Content Web Sites , 2002 .

[32]  Rachid Guerraoui,et al.  Exploiting Atomic Broadcast in Replicated Databases , 1998, Euro-Par.