Posted on by Tactical Systemsin
Our modern data infrastructure has become very effective at getting the information you need, when you need it. This infrastructure has become so effective that we rely on having instant access to information in many aspects of our lives. Unfortunately, there are still situations in which the data infrastructure cannot meet our needs due to various limitations at the tactical edge, which is a term used to describe hostile environments with limited resources, from war zones in Afghanistan to disaster relief in countries like Haiti and Japan. This blog post describes our ongoing research in the Advanced Mobile Systems initiative at the SEI on edge-enabled tactical systems to address problems at the tactical edge.
At the tactical edge, the people that need the information the most--warfighters, first responders, or other emergency personnel--depend on timely and valuable information to perform their tasks, or even survive. Unfortunately, the access to the information they need can be extremely hard to achieve, for the following reasons:
The remainder of this posting describes how we are tackling the information overload and information obscurity aspects of this problem by developing context-aware mobile applications.
A Different Approach to Context-Aware Mobile Applications
Context awareness in the mobile environment is not a new field of research. Most mobile devices come preloaded with applications that use location or time to account for user context. There is certainly no shortage of similar applications available for download. We decided, therefore, to explore alternative sources of data that would not only push the limit of what could be done with user context, but also focus on the extremely challenging environment at the tactical edge.
Our "eureka" moment came when we realized that when warfighters or first responders are at the tactical edge, they are almost never operating alone. As a result, the most important contextual information to warfighters or first responders is the context of the people in the group, and how they relate to that context. This realization drove us to explore group context-aware mobile applications. These applications would, if built correctly, first consider individual user context and then relate that information to the group context, thereby helping users understand both their own state, as well as the state of the group in which they participate.
Group context-aware mobile applications clearly have value at the tactical edge. For example, warfighters are well served by having access to positions of friends and foes on the battlefield (position data being a simple case). They could also benefit from supportive applications that monitor resources, such as food, ammunition, or vital signs. With sufficient data and processing power, these applications could even use historical trends to determine dynamically if a squad is walking into a possible ambush situation.
In less deadly (yet still hostile) environments, such as tsunami disaster areas, the ability to share information about resource needs, dangerous situations, or health emergencies in a structured way can also be valuable. Such applications could tailor information to managers, construction workers, doctors, and other emergency personnel to help coordinate an effective emergency response.
An extensive literature review on context awareness yielded relatively little research on the topic of group context. Much of the prior work cites the basic context model developed by Anind Dey, but does not expand the model past the individual, choosing instead to tailor the model to a particular domain. Our research project, called Information Security to the Edge (ISE), explores the structure, applications, and implementation of a context model that includes group information. We have constructed a prototype application on the Android platform that implements the essential components needed by group context-aware mobile applications, as discussed next.
App Architecture - Logic and Data
The ISE prototype application follows the common model-view-controller (MVC) pattern, which decomposes an application into the following parts:
Consistent with the MVC pattern, the ISE prototype has a central control mechanism (which forms the "brains" of the application) that manages data flow through the application. In practice, this means that the central controller coordinates data flow and processing through the following primary application elements:
The sensor and communications manager architecture consolidates all sensor and communication concerns into a single location. This consolidation approach enabled us to build a standardized interface that simplifies integration an arbitrary sensor (for example, a radiation sensor) or an arbitrary communication mechanism (for example, a line-of-sight radio that communicates with UAVs) with the application. We tested this feature through a collaboration with Joao Sousa of George Mason University. This testing resulted in the development of an alternative communication mechanism that integrates with the prototype with only a few weeks of effort, instead of months or years. We anticipate leveraging these standardized interfaces to collaborate with a variety of external groups and organizations as new sensor technologies and communication mechanisms become available.
App Architecture - User Interface (UI)
The ISE app, through the use of Android UI screens called Activities, reflects the view part of the MVC Pattern. There are currently only three supported UIs in ISE:
We are upgrading the ISE architecture to support any UI that subscribes to standardized updates from the data services.
One challenge we face involves accounting for the lack of network infrastructure. In particular, limited bandwidth exists for the available communication channels. We are building atop of communication capacities that other organizations are field testing in Afghanistan to tailor our solution to practical field situations.
A second challenge involves providing warfighter access to backend data sources. Soldiers told us that important information is available in such sources, but they can't readily find the relevant information. Moreover, they can't access the database in the field. Other Advanced Mobile Systems work is investing ways to provide access to critical data through the use of cloudlets.
A third challenge involves reducing the user's cognitive load by limiting the amount of interaction and attention required of the user. Residents in a metropolitan area can use their smart phones without undue concern for being in a distracted state, as long as they are not engaging in tasks that demand undivided attention. A soldier in Haiti, on the other hand, must be cognizant of crumbling buildings, while a warfighter on the ground in Afghanistan might need to digest information while taking enemy fire. Our goal is to use hardware that allows the warfighter to capture and process information seamlessly, without sacrificing valuable time and resources.
We are also addressing the challenge of resource scarcity. Resources are limited at the tactical edge and warfighters are typically limited to the power and bandwidth of whatever devices they can carry. We are therefore exploring resource optimization based upon our expanded model of context. For example, if a warfighter's assignment involves driving through a known safe area, it may not be necessary for the smartphone to activate the GPS capability. By optimizing the system to use sensors only when needed, warfighters can save battery power, CPU cycles, and communication bandwidth that can be used to support other mission-critical needs.
Finally, our work will not have the desired impact if we cannot meet the challenge of relevance. Warfighters made it clear to us that if a device or application is not directly useful to their immediate task, it will be ignored. In any given day, a warfighter in Afghanistan may be asked to determine if a particular individual is a threat, sweep a village to establish identities of residents, deliver food to children, or check for a weapons cache. These different missions impact the type of information that interests soldiers and the type of information a software application should consider. Solving this problem requires a deep understanding of the needs of soldiers and the missions in which they engage. We are leveraging this domain knowledge so our ISE application can tailor information processing to a particular mission, thereby ensuring relevance to the current mission and the ability to change mission parameters as needed.
The ISE prototype is just one part of our strategy to address the problems of information overload, information obscurity, and resource scarcity. The Advanced Mobile Systems initiative is also engaged in the Edge-Enabled Programming project as well as the Resource Optimization for Mobile Platforms at the Edge project. Each project attacks the three problems of information overload, information obscurity, and resource scarcity from different perspectives. We intend to integrate each project together after they have matured, thereby providing an end-to-end solution to warfighters and first responders at the tactical edge.
For more information on the MVC pattern, consult the Documenting Software Architectures: Views and Beyond and the Pattern-Oriented Software Architecture: Volume 1 books.
Visit the SEI Digital Library for other publications by Marc