James R. Michaelis

Analyzing the applicability of Internet of Things to the battlefield environment

As the Internet of Things (IoT) matures in commercial sectors, the promise of diverse new technologies such as data-driven applications, intelligent adaptive systems, and embedded optimized automation will be realized in every environment. An immediate research question is whether contemporary IoT concepts can be applied also to military battlefield environments and can realize benefits similar to those in industry. Military environments, especially those that depend on tactical communications, are much more challenging than commercial environments. Thus it is likely many commercial IoT architectures and technologies may not translate into the military domain and others will require additional research to enable deployment and efficient implementation. This paper investigates these issues and describes potential military operational activities that could benefit from commercial IoT technologies, including logistics, sensing/surveillance, and situation awareness. In addition, the paper lays out a roadmap for future research necessary to leverage IoT and apply it to the tactical battlefield environment.

Software-defined and value-based information processing and dissemination in IoT applications

In the near term, a multitude of IoT applications are expected, each taking advantage of heterogeneous device collections ranging from environmental sensors to smartphones. However, approaches taken in many IoT systems - based on the paradigm of Cloud computing - face challenges of both high latency and network utilization. A clear demand now exists for new paradigms to facilitate IoT application usage of computational resources at the edge of the network for data analysis purposes, as well as smart dissemination solutions to deliver information to consumers. This paper presents SPF (Sieve, Process, and Forward), a Software Defined Networking (SDN) solution for creating and managing IoT applications and services. By leveraging programmable information processors deployed at the Internet/IoT edge, the SDN approach introduced by SPF represents a promising architecture for future urban computing applications.

Leveraging Internet of Things within the military network environment — Challenges and solutions

The widespread adoption of IoT technologies will significantly affect many aspects of military operations. A growing number of battlefield assets will soon become networked entities, thanks to capillary and high density personal and environment sensors systems. The accurate and fine-grained information gathered could significantly benefit military intelligence, surveillance, and reconnaissance operations, facilitate automated supply chain logistics, and facilitate urban operations in mega-city environments. To achieve these goals, research has to address several issues, such as reconciling the differences between commercial IoT architectural patterns and military network architectures, interoperability between different IoT systems, data processing and information management, and realization of resource-efficient IoT middleware solutions. The resource constrained tactical networking environment makes this research agenda particularly challenging but also pressing in terms of the need for novel middleware solutions.

SPF: An SDN-based middleware solution to mitigate the IoT information explosion

Managing the extremely large volume of information generated by Internet-of-Things (IoT) devices, estimated to be in excess of 400 ZB per year by 2018, is going to be an increasingly relevant issue. Most of the approaches to IoT information management proposed so far, based on the collection of IoT-generated raw data for storage and processing in the Cloud, place a significant burden on both communications and computational resources, and introduce significant latency. IoT applications would instead benefit from new paradigms to enable definition and deployment of dynamic IoT services and facilitate their use of computational resources at the edge of the network for data analysis purposes, and from smart dissemination solutions to deliver the processed information to consumers. This paper presents SPF (as in “Sieve, Process, and Forward”), an SDN solution which extends the reference ONF architecture replacing the Data Plane with an Information Processing and Dissemination Plane. By leveraging programmable information processors deployed at the Internet/IoT edge and disruption tolerant information dissemination solutions, SPF allows to define and manage IoT applications and services and represents a promising architecture for future urban computing applications.

The missions and means framework as an ontology

The analysis of warfare frequently suffers from an absence of logical structure for a] specifying explicitly the military mission and b] quantitatively evaluating the mission utility of alternative products and services. In 2003, the Missions and Means Framework (MMF) was developed to redress these shortcomings. The MMF supports multiple combatants, levels of war and, in fact, is a formal embodiment of the Military Decision-Making Process (MDMP). A major effect of incomplete analytic discipline in military systems analyses is that they frequently fall into the category of ill-posed problems in which they are under-specified, under-determined, or under-constrained. Critical context is often missing. This is frequently the result of incomplete materiel requirements analyses which have unclear linkages to higher levels of warfare, system-of-systems linkages, tactics, techniques and procedures, and the effect of opposition forces. In many instances the capabilities of materiel are assumed to be immutable. This is a result of not assessing how platform components morph over time due to damage, logistics, or repair. Though ill-posed issues can be found many places in military analysis, probably the greatest challenge comes in the disciplines of C4ISR supported by ontologies in which formal naming and definition of the types, properties, and interrelationships of the entities are fundamental to characterizing mission success. Though the MMF was not conceived as an ontology, over the past decade some workers, particularly in the field of communication, have labelled the MMF as such. This connection will be described and discussed.

Query generation and recommendation via mission plan interpretation (Conference Presentation)

The abstract is not available

In-context query reformulation for failing SPARQL queries

Knowledge bases for decision support systems are growing increasingly complex, through continued advances in data ingest and management approaches. However, humans do not possess the cognitive capabilities to retain a bird’s-eyeview of such knowledge bases, and may end up issuing unsatisfiable queries to such systems. This work focuses on the implementation of a query reformulation approach for graph-based knowledge bases, specifically designed to support the Resource Description Framework (RDF). The reformulation approach presented is instance-and schema-aware. Thus, in contrast to relaxation techniques found in the state-of-the-art, the presented approach produces in-context query reformulation.

Requirements for Value of Information (VoI) calculation over mission specifications

Intelligence, Surveillance, and Reconnaissance (ISR) operations center on providing relevant situational understanding to military commanders and analysts to facilitate decision-making for execution of mission tasks. However, limitations exist in tactical-edge environments on the ability to disseminate digital materials to analysts and decision makers. This work investigates novel methods to calculate of Value of Information tied to digital materials (termed information objects) for consumer use, based on interpretation of mission specifications. Followed by a short survey of related VoI calculation efforts, discussion is provided on mission-centric VoI calculation for digital materials via adoption of the preexisting Missions and Means Framework model.

Enabling task-based information prioritization via semantic web encodings

Modern Soldiers rely upon accurate and actionable information technology to achieve mission objectives. While increasingly rich sensor networks for Areas of Operation (AO) can offer many directions for aiding Soldiers, limitations are imposed by current tactical edge systems on the rate that content can be transmitted. Furthermore, mission tasks will often require very specific sets of information which may easily be drowned out by other content sources. Prior research on Quality and Value of Information (QoI/VoI) has aimed to define ways to prioritize information objects based on their intrinsic attributes (QoI) and perceived value to a consumer (VoI). As part of this effort, established ranking approaches for obtaining Subject Matter Expert (SME) recommendations, such as the Analytic Hierarchy Process (AHP) have been considered. However, limited work has been done to tie Soldier context – such as descriptions of their mission and tasks – back to intrinsic attributes of information objects. As a first step toward addressing the above challenges, this work introduces an ontology-backed approach – rooted in Semantic Web publication practices – for expressing both AHP decision hierarchies and corresponding SME feedback. Following a short discussion on related QoI/VoI research, an ontology-based data structure is introduced for supporting evaluation of Information Objects, using AHP rankings designed to facilitate information object prioritization. Consistent with alternate AHP approaches, prioritization in this approach is based on pairwise comparisons between Information Objects with respect to established criteria, as well as on pairwise comparison of the criteria to assess their relative importance. The paper concludes with a discussion of both ongoing and future work.

Classification of user interfaces for graph-based online analytical processing

In the domain of business intelligence, user-oriented software for conducting multidimensional analysis via Online- Analytical Processing (OLAP) is now commonplace. In this setting, datasets commonly have well-defined sets of dimensions and measures around which analysis tasks can be conducted. However, many forms of data used in intelligence operations – deriving from social networks, online communications, and text corpora – will consist of graphs with varying forms of potential dimensional structure. Hence, enabling OLAP over such data collections requires explicit definition and extraction of supporting dimensions and measures. Further, as Graph OLAP remains an emerging technique, limited research has been done on its user interface requirements. Namely, on effective pairing of interface designs to different types of graph-derived dimensions and measures. This paper presents a novel technique for pairing of user interface designs to Graph OLAP datasets, rooted in Analytic Hierarchy Process (AHP) driven comparisons. Attributes of the classification strategy are encoded through an AHP ontology, developed in our alternate work and extended to support pairwise comparison of interfaces. Specifically, according to their ability, as perceived by Subject Matter Experts, to support dimensions and measures corresponding to Graph OLAP dataset attributes. To frame this discussion, a survey is provided both on existing variations of Graph OLAP, as well as existing interface designs previously applied in multidimensional analysis settings. Following this, a review of our AHP ontology is provided, along with a listing of corresponding dataset and interface attributes applicable toward SME recommendation structuring. A walkthrough of AHP-based recommendation encoding via the ontology-based approach is then provided. The paper concludes with a short summary of proposed future directions seen as essential for this research area.