Checkpointing distributed applications on mobile computers

Acharya, Arup; Badrinath, B. R.

doi:10.1109/pdis.1994.331730

Cited by 131 publications

(110 citation statements)

References 19 publications

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“…For example, in mobile computing systems, due to vulnerability of Mobile Hosts (MHs) to catastrophic failures, e.g., loss, theft, or physical damage, the disk storage on an MH cannot be considered stable storage. A reasonable solution [1] is to utilize the stable storages at Mobile Support Stations (MSSs) to store checkpoints of MHs. Thus, to take a checkpoint, an MH has to transfer a large amount of data to its local MSS over the wireless network.…”

Section: Discussionmentioning

confidence: 99%

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On coordinated checkpointing in distributed systems

Singhal

1998

IEEE Trans. Parallel Distrib. Syst.

110

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Abstract-Coordinated checkpointing simplifies failure recovery and eliminates domino effects in case of failures by preserving a consistent global checkpoint on stable storage. However, the approach suffers from high overhead associated with the checkpointing process. Two approaches are used to reduce the overhead: First is to minimize the number of synchronization messages and the number of checkpoints, the other is to make the checkpointing process nonblocking. These two approaches were orthogonal in previous years until the Prakash-Singhal algorithm [18] combined them. In other words, the Prakash-Singhal algorithm forces only a minimum number of processes to take checkpoints and it does not block the underlying computation. However, we found two problems in this algorithm. In this paper, we identify these problems and prove a more general result: There does not exist a nonblocking algorithm that forces only a minimum number of processes to take their checkpoints. Based on this general result, we propose an efficient algorithm that neither forces all processes to take checkpoints nor blocks the underlying computation during checkpointing. Also, we point out future research directions in designing coordinated checkpointing algorithms for distributed computing systems.

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Section: Discussionmentioning

confidence: 99%

“…5, we make two observations: OBSERVATION 1. It is not necessary to take checkpoint C 1,2 even though m4 exists, since P 0 does not transitively z-depend on P 1 during the zeroth checkpoint interval of P 0 .…”

Section: Enhanced Schemementioning

confidence: 99%

On coordinated checkpointing in distributed systems

Singhal

1998

IEEE Trans. Parallel Distrib. Syst.

110

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“…These protocols have either to exchange messages during the creation of an application checkpoint (Chandy and Lamport, 1985) (Plank, 1993), or during recovery to collect stored information (Johnson and Zwaenepoel, 1990). Protocols previously proposed for mobile computing have relied on the foreign agent for storing the checkpoint (Acharya and Badrinath, 1994) (Pradhan et al, 1996). Previous protocols also have not adapted their behavior to the characteristics of the current network connection.…”

Section: Introductionmentioning

confidence: 99%

Dependable Distributed and Mobile Computing — Utilizing Time to Enhance Recovery from Failures

Fuchs

Neves

Ssu

2000

Dependable Network Computing

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Mobile computing allows ubiquitous and continuous access to computing resources while users travel or work at a client's site. The flexibility introduced by mobile computing brings new challenges to dependability and fault tolerance. Failures that were rare with fixed hosts become common, and host disconnections make fault detection and message coordination difficult. This chapter describes checkpointing and failure recovery procedures that are well adapted to both distributed and mobile environments. The protocols use time to indirectly coordinate the creation of new global states and thereby avoid message exchanges. The mobile protocol uses two different types of checkpoints to adapt to network characteristics. Procedures for integrating adaptive mobile checkpointing with storage management are also described.

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“…Distributed mobile computing environments have been addressed in hardware entities by many papers in the literature [1,15]. In mobile distributed computing, much of the action takes place in the middleware level.…”

Section: Mobile Architecturementioning

confidence: 99%

“…Rearranging the above equation yields Equation (1). After engaging the moment generating property of the Laplace transform [6], E(R …”

Section: Execution Time and Average Effectiveness Without Checkpointingmentioning

confidence: 99%