CoNICE: Consensus in Intermittently-Connected Environments by Exploiting Naming with Application to Emergency Response

In many scenarios, information must be disseminated over intermittently-connected environments when network infrastructure becomes unavailable. Example scenarios include disasters in which first responders need to send updates about their critical tasks. If such updates pertain to a shared data set (e.g., pins on a map), their consistent dissemination is important. We can achieve this through causal ordering and consensus. Popular consensus algorithms, such as Paxos and Raft, are most suited for connected environments with reliable links. While some work has been done on designing consensus algorithms for intermittently-connected environments, such as the One-Third Rule (OTR) algorithm, there is need to improve their efficiency and timely completion. We propose CoNICE, a framework to ensure consistent dissemination of updates among users in intermittently-connected, infrastructure-less environments. It achieves efficiency by exploiting hierarchical namespaces for faster convergence, and lower communication overhead. CoNICE provides three levels of consistency to users' views, namely replication, causality and agreement. It uses epidemic propagation to provide adequate replication ratios, and optimizes and extends Vector Clocks to provide causality. To ensure agreement, CoNICE extends basic OTR to support long-term fragmentation and critical decision invalidation scenarios. We integrate the multilevel consistency schema of CoNICE, with a naming schema that follows a topic hierarchy-based dissemination framework, to improve functionality and performance. Performing city-scale simulation experiments, we demonstrate that CoNICE is effective in achieving its consistency goals, and is efficient and scalable in the time for convergence and utilized network resources.