The Computer Journal Advance Access originally published online on December 22, 2008
The Computer Journal 2009 52(4):499-509; doi:10.1093/comjnl/bxn069
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The Agreement Problem in Unreliable Scale-Free Networks
1 Department of Business Administration, Chaoyang University of Technology, 168 Gifeng E. Rd., Wufeng, Taichung County, Taiwan 413, Republic of China
2 Department of Industrial Engineering and Management, Chaoyang University of Technology, 168 Gifeng E. Rd., Wufeng, Taichung County, Taiwan 413, Republic of China
3 Department of Information Management, Chaoyang University of Technology, 168 Gifeng E. Rd., Wufeng, Taichung County, Taiwan 413, Republic of China
* Corresponding author: scwang{at}cyut.edu.tw
Received 4 March 2008; revised 8 November 2008
Generally, tasks in a distributed system must reach agreement. This requires a set of processors to agree on a common value even though some components may be corrupt. There have been several significant studies on this agreement problem in regularized network environments such as the fully connected, broadcast and multicast networks. Recently, many large complex networks have emerged displaying a scale-free feature that influences the system to reach a common value in a novel way. This unanimity problem is called Byzantine agreement (BA). The BA problem is one of the most significant problems in designing a fault-tolerant distributed system. Unfortunately, existing BA protocols cannot cope with the new network environment, and the BA problem thus must be revisited. In this paper, a new BA protocol is proposed that adapts to the scale-free network (SFN) environment and derives its limit of allowable faulty components while maintaining the minimum number of message exchanges. The correctness and complexity of this protocol have been proved. It is observed that an SFN in conjunction with the proposed agreement protocol can tolerate the maximum number of faulty components.
Key Words: distributed processing Byzantine agreement fault tolerance scale-free network complex network and random network