An Adaptive-Grained Consistency Maintenance Scheme for Shared Data on Emergency and Rescue Applications

  • Authors:

  • Jyh-Biau Chang;Po-Cheng Chen;Ce-Kuen Shieh;Jia-Hao Yang;Sheng-Hung Hsieh

  • Affiliations:

  • Department of Digital Applications, University of Kang Ning, Tainan, Taiwan;Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan

  • Venue:
  • International Journal of Grid and High Performance Computing
  • Year:
  • 2013

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Abstract

Efficient information sharing is difficult to achieve in the scenario of emergency and rescue operations because there is no communication infrastructure at the disaster sites. In general, the network condition is relatively reliable in the intra-site environment but relatively unreliable in the inter-site environment. The network partitioning problem may occur between two sites. Although one can exploit the replication technique used in data grid to improve the information availability in emergency and rescue applications, the data consistency problem occurs between replicas. In this paper, the authors propose a middleware called "Seagull" to transparently manage the data availability and consistency issues of emergency and rescue applications. Seagull adopts the optimistic replication scheme to provide the higher data availability in the inter-site environment. It also adopts the pessimistic replication scheme to provide the stronger data consistency guarantee in the intra-site environment. Moreover, it adopts an adaptive consistency granularity strategy that achieves the better performance of the consistency management because this strategy provides the higher parallelism when the false sharing happens. Lastly, Seagull adopts the transparency data consistency management scheme, and thus the users do not need to modify their source codes to run on the Seagull.