Octav Chipara, William G. Griswold, Anders N. Plymoth, Ricky Huang, Fang Liu, Per Johansson, Ramesh Rao, Theodore C. Chan, Colleen Buono
This paper describes the design, deployment, and empirical evaluation of WIISARD -- a novel emergency response system that provides reliable communication in dynamic wireless environments without extensive communication infrastructure. The main contribution of this paper is an in-depth empirical study of network properties that emerge during a drill in which WIISARD is deployed with minimal infrastructure support. The drill involves 19 first responders and 41 victims. The properties of links established among first responders vary between phases of the drill and depend upon the responder's role in the drill. The rescue phase -- in which responders are highly mobile as they triage victims -- poses significant challenges to reliable communication. During this phase, the contacts between responders are short-lived; however, they are reestablished within minutes. Once a contact between responders is established, the quality of the link between those responders is usually high. The connectivity graph observed during the rescue phase is usually connected and has a small diameter although there are times when it has a large diameter or it is partitioned. While mobility increases network dynamics, we also observe that the mobility patterns characteristic of the emergency response workflow can be leveraged to disseminate data efficiently through data muling. WIISARD employs a gossip-based protocol and supports data dissemination through local communication and data muling to achieve 98% reliability during the drill exercise.These results indicate the feasibility of providing reliable communication in emergency response with minimal infrastructure in spite of network dynamics.
Public Review uploaded by MattWelsh:
Public review prepared by Matt Welsh
Wireless technology has tremendous potential to solve hard, real-world
problems in emergency response, especially in cases where many
patients may need to be rapidly triaged and transported for treatment.
With limited first responder resources, rapidly identifying the
patients that require critical care, and coordinating the response
across the chain of command, is essential for saving lives. This paper
is one of the first studies of the performance of a wireless
communications platform, bsed on ad-hoc 802.11 networking, during
a simulated disaster drill with 41 "victims" and 19 first responders.
The WIISARD system is based on a simple gossip-based protocol over
802.11 called with WIISARD Communication Protocol, or WCP. The goal of
the system is to rapidly propagate reports from individual first
responder devices to all other devices in the field. It uses a delay
tolerant networking approach, given that disconnections between
devices are expected to be frequent as first responders move around.
The paper's chief weakness is that the results are closely linked to
the physical layout of the disaster drill setting, as well as the
specific devices and network protocol used. Because of the nature of
the study, it is hard to generalize much beyond the results presented here.
It is also difficult to justify the use of multihop 802.11 in this
application at all, given that there are better radio technologies
more suited to long-range broadcast communication.
One critical piece missing from the evaluation is that of data
consistency, although there is some discussion of this issue.
Delayed updates could have serious implications in this
application: for example, if a first responder erroneously marks a
victim as "morgue" and then corrects the state to "still alive",
the inconsistent information could lead to delayed triage and loss of
life. This problem underscores the importance of considering the whole
application, not just the networking components, when designing a
system such as this.
This paper presents one of the first empirical studies of communication during an emergency response. Our system -- WIISARD -- uses delay-tolerant techniques to achieve high reliability even in the presence of significant network dynamics and partitions. The paper makes two contributions: (1) We provide a detailed characterization of the communication challenges observed during a real deployment of an emergency response. (2) The study complements existing work on human mobility models by showcasing an application in which responders collaborate to rescue victims according to the Incident Command Structure. The public review points to three limitations of the paper: technology choice, generalizability of results, and consistency.
Technology choice: The choice of 802.11 in WIISARD is the result of our desire to integrate with the systems currently used by San Diego Fire. Longer range communication system are attractive since they could support a simple client-server architecture; however, such systems usually have low throughput and require infrastructure. We believe that integrating 802.11 and long-range communication systems is a design choice worth exploring.
Generalizability of results: The study shows the superiority of delay tolerant techniques over multi-hop routing approaches that have been traditionally used in emergency response systems. This is a general result that we expect to impact the design of future emergency response systems. Moreover, our study shows that the Incident Command Structure used in emergency responses shapes the mobility patterns of responders and explains the performance benefits of data muling. While we don’t have data from multiple emergency responses to draw a definite conclusion, we are the first to highlight the importance of this property, and now, this claim can be further evaluated by us and other research groups.
Data Consistency: The problem of consistency is a fundamental challenge in delay-tolerant systems that require users to share data. The paper evaluates the delay of disseminating data blocks, however, the impact of this delay on the application performance is indeed not fully evaluated. We are in the process of developing new metrics for WIISARD that measure the impact of data inconsistency.