This paper proposes a novel updating technique, dynamically updating, for achieving extension or modification of functions in a distributed system. Usual updating technique requires synchronous suspension for multiple processes for avoiding unspecified reception caused by the conflict of different versions of processes. Thus, this technique needs very high overhead and it must restrict the types of distributed systems, to which it can be applied, to RPC (remote procedure call) type or client-server type. Using the proposed dynamically updating technique, updating management can be invoked asynchronously by each process with assurance of correct execution of the system, i.e., the system can cope with the effect of unspecified reception caused by mixture of different version processes. Therefore, low overhead updating can be achieved in partner type distributed systems, that is more general type including communications systems or computer networks. Dynamically updating technique is implemented by using a novel distributed algorithm that consists of group communication, checkpoint setting, and rollback recovery. By using the algorithm proposed in this paper, rollback recovery can be achieved with the lowest overhead, i.e., a set of checkpoint determines the last global state for consistent rollback recovery and a set of processes that need to rollback simultaneously is the smallest one. This paper also proves the correctness of the proposed algorithm.

This paper proposes a group-to-group communications algorithm that can extend the range of distributed systems where we can achieve active replication fault-tolerance to partner model distributed systems, in which all processes communicate with each other on an equal footing. Active replication approach, in which all replicated processes are active, can achieve fault-tolerance with low overhead because checkhpoint setting and rollback are not required for recovery from process failure. This algorithm guarantees that each replicated process in a process group has the same execution history and that communications between process groups keeps consistency even in the presence of process failure and message loss. The number of control messages that must be transmitted between processes for a communication between process groups is only a linear order of the number of replicated processes in each process group. Furthemore, this algorithm reduces the overhead for reconfiguration of a process group by keeping process failure and recovery information local to each process group.