# Integrating Decentralized Indoor Evacuation with Information Depositories in the Field
## 2 Related Work
### Decentralized Evacuation  
Advances in technology such as sensors and smartphones make decentralized spatial computing possible. Existing sensors can detect acoustic, chemical, electromagnetic, optical, thermal, or mechanical stimuli, and convert such environmental stimuli into digital signals to be processed by a computer [64]. Such sensors can measure environmental data such as humidity, \(CO_{2}\) concentration, temperature, or even location [65]. A number of these sensors can be found on-board of smartphones, and thus, smartphones can be considered a node in a mobile sensor network. A sensor node has a microcontroller for computing, a wireless radio for communication, and one or more sensors for capturing data about its environment. Mobile sensor networks are examples of decentralized systems. A decentralized system is a special case of a distributed system where no single component knows the entire system state and each node in a decentralized system acts independently and autonomously. In general, decentralized spatial computing is advantageous over centralized spatial computing in six aspects: energy constraints, information overload, scalability, sensor/actuator networks, latency, and information privacy [64]. [PERSON] et al. [3] proposed a decentralized system for collaborative evacuation. This system utilizes smartphones with their sensors and their capacity for peer-to-peer communication where computation is performed directly on the devices held by evacuees and guidance is provided by a mobile service. The advantage of peer-communication and -collaboration correlates positively with the density of evacuees in the environment: The more evacuees exist in a certain environment, the more opportunity exists for exchanging knowledge. However, a larger number of evacuees also implies an increased risk of congestions [58]. Similar work has been done by [PERSON] and [PERSON] [66]. They considered the opportunistic communication of mobile nodes in Mobile Opportunistic Networks (MONs), and assumed also a navigation service. Evacuees share disaster information by opportunistic encounter and short-range wireless communication. In their scenario the disaster information is finally gathered by a database server in the refuge and forwarded out of the disaster area by delay tolerant network technologies such as satellite-based communications. [PERSON] et al. [67] also introduced cooperation between evacuees with mobile sensor nodes. Each mobile node senses the environment and tries to navigate its evacuee by presenting an evacuation route. The mobile node estimates a road segment as blocked when it detects the difference between a recommended route and actual evacuation behavior. Then it recalculates an alternative evacuation route, which does not include the blocked road segments discovered. They focus specifically on reducing the network load. [PERSON] et al. [68] presented a method for decentralized evacuation, which considers evacuation as a distributed constraint optimization problem and estimates the location of evacuees so as to relieve congestion. Due to the fundamental property of opportunistic communication, all the wireless mobile sensor networks share a shortcoming that the effects of opportunistic communication become weaker when the number of users in the network is smaller. None of the previous work has addressed this issue. Thus, improving decentralized evacuation management for less occupied buildings is the object to be addressed in this paper. While static sensor networks can detect the extent of phenomena such as fires or concentrations of pollutants, and can delineate the boundaries of such regions, low-density in situ sensor networks may not suffice to estimate the boundaries, especially in evacuation situations where the sensor nodes are outside of these hazardous regions. [PERSON] [69] suggest adding mobile sensors with an intelligent and adaptive sampling strategy to collect the missing information for monitoring the boundaries of highly dynamic phenomena such as plumes.