OMAHA (Opportunistic Message Aggregation for pHase-based Algorithms) is a message aggregation mechanism designed for phase-based algorithms, which are widely used in Cloud environments. In these settings, bandwidth is a critical resource, and managing small messages, which make up a large portion of network traffic, is a major challenge. OMAHA takes advantage of the predictable communication patterns of phase-based algorithms to group messages going to the same process. This reduces the total number of messages sent. Experiments show that OMAHA can save up to 30% of bandwidth while keeping latency increase below 5% when applied to the Paxos algorithm.
In distributed systems, reaching consensus on a decision or value is a complex problem, especially when processes have specific constraints. Systems like multi-agent setups (e.g., autonomous vehicles, schedule management, or robotics) and resource allocation systems must balance these constraints with a shared goal. Traditional consensus algorithms ignore such constraints, focusing only on proposed values. To handle faults, they rely on the majority, which means constraints from the minority are often disregarded. To address this, we proposed the f-Revocable Consensus. This approach ensures the chosen value respects the constraints of processes and allows decisions made by the majority to be revoked if they violate a minority process’s constraints.