Networked Operations

Decentralized, peer-to-peer command and control is a key principle of network-centric operations that has received a lot of scholarly attention. So far, robust networking, another principle, has remained rather underexposed in the academic debate. This chapter introduces theory on modular organizing to start a discourse on network robustness from an organizational design perspective. Above all, the chapter makes clear that the level of system decomposition influences the command and control process of composite military structures. When military organizations follow a fine-grained modularization approach, the structure of a task force deployed may become complex, asking for extra coordination mechanisms to achieve syntheses between the many contributing functional organizational components. In addition, it is argued that modularity's principle of near-decomposability has to be incorporated into the available mathematical models on network-centric operations. A point of concern, in this respect, is that the current modeling parameters make no clear distinction between the different types of actors—or nodes—in a military network structure, whereas in reality, technological, organizational, and human actors all live by their own specific rules.

Shaping Comprehensive Emergency Response Networks

Given its nature, a crisis has a significant community impact. This applies in particular to emergencies: crises that arise quickly. Because of the complex and multifaceted nature of large-scale incidents, the response requires coordinated effort by multiple organizations. This networked collaboration is not solely restricted to professional organizations. In responding to an incident, the affected community can itself be an important source of information and capabilities. This chapter discusses how one can shape a trustworthy and decisive response organization in which relevant and useful capacities available in the community are incorporated. This discussion has two focal points. The first focal point is the role of the affected community in the case of an emergency. On the one hand, an emergency affects the fabric of the community, such as the critical infrastructure. On the other, a community has inherent internal resources that give it resilience and capacity to respond in a crisis. This needs to be reflected in the choice of emergency response planning model. The second focal point is the structure of the emergency response network. An emergency response network is a mixed-sector network. This means that coordination is needed among organizations and collectives with differing strategic orientations.

De-Conflicting Civil-Military Networks

Operation Unified Protector (OUP) in Libya illustrated the urgent need for civil-military command in the sense of at least de-conflicting primary operational processes of military and international civilian actors. A military theater such as Libya is externally connected and surrounded by huge (additional) movements by air, sea, and land. This chapter provides insight into network structures and practices for achieving such de-confliction in the context of complex peace operations. Based on a case study and prior responsibilities of one of the authors, the chapter shows how NATO's Allied Movement Coordination Centre (AMCC) functioned as a linking pin between military and international civilian actors. Challenges it faced are addressed, including establishment of relationships with relevant actors, understanding their ways of working, and developing procedures to coordinate a heterogeneous network.

Smart Surveillance Systems

To enable effective and efficient command and control in military operations it is necessary to have full awareness of all the actions in the field. In traditional C2 systems, human operators play key roles varying from observation in the field up to semantic interpretation of observed data in the Command and Control Centre. Networks are mainly used to transmit data between different components of the network. Observation by human operators will be replaced by sensor networks. The huge amount of incoming data is far beyond the capacity of operators, so the heterogeneous, multimodal data from the different sensor systems has to be fused, aggregated, and filtered. Automated surveillance sensor networks are discussed in this chapter. Sensors are modelled as a distributed system of smart agents. Methods and technology from Artificial Intelligence such as expert systems, semantic networks, and probabilistic reasoning is used to give a semantic interpretation of the sensed data from the environment.

Complex Adaptive Information Networks for Defence

This chapter focuses on understanding the nature of the information networks that can create Self-Synchronization of the force. The analysis takes place at a number of levels, which for simplicity, are called Levels 1, 2, and 3. At Level 1 (“linked”), the author considers the basic node and linkage topology. At Level 2 (“synched”), he considers the local interaction between intelligent nodes, sharing the information and awareness required for Self-Synchronization in the cognitive domain. At Level 3 (“cliqued”), the author considers how such local networking feeds through into emergent clustering effects in the physical domain. Structured experimental games coupled with information entropy-based measures of merit illustrate these ideas, as do models of fundamental information networking dynamics and their resultant emergent behaviour. It turns out that the tools, models, and concepts of Complexity Theory give deep insight into the topic of Self-Synchronization.

Dynamical Network Structures in Multi-Layered Networks

In modeling military (inter)actions and cooperation as networks, military units or actors may be represented as nodes. In analyzing military networked action, a key observation is that a node is not just part of one type of network but simultaneously belongs to multiple networks. To model the dynamical behavior of actors, one has to take into account the interdependence of the different networks. In this chapter, the authors present a method that is used to implement, analyze, and evaluate some specific principles that may be used by the actors in an organization to drive the process of constant change. It can be used to analyze the effect of these principles on the metrics for coordination, synchronization, robustness, and desired operational effectiveness of the network as a whole. To demonstrate the approach, the authors apply it to networks in which two basic principles are operational: reciprocity and a novel principle called covering.

Modeling C2 Networks as Dependencies

This chapter describes an approach to modeling C2 and other types of networks as a series of nodes (people, groups, resources, locations, concepts, etc.). The nodes are linked by one or more weighted arcs describing the type and the strength of the dependency that one node has on another node. This model allows analysts to identify the most important nodes in a network in terms of their direct and indirect dependencies and to rank them accordingly. The same model also supports consequence analysis in which the direct, indirect, cascading, and cumulative effects of changes to node capabilities can be propagated across the networks. The chapter describes the basic modeling technique and two types of dependency propagation that it supports. These are illustrated with two examples involving the modeling and reasoning across insurgent networks and an Integrated Air Defense System. These show how aspects of the networks can be analyzed and targeted. Details are also provided on the mechanisms to link the analysis to a planning system through which plans can be developed to bring about desired effect(s) in the networks.

Formalized Ontology for Representing C2 Systems as Layered Networks

Command and Control (C2) is an essential operating capability in which the commander exercises authority over assigned forces to accomplish the mission. Traditionally, military C2 was organized hierarchically with the commander issuing directives top-down and subordinates reporting progress upwards. Over the past two decades, developments in digital telecommunication technology have made it possible to link distributed computer systems into a network. These developments can be exploited to delegate decision-making authority down the organizational hierarchy. Subordinates can be empowered to share information and synchronize their actions with their peers, speeding up the response to changes in the situation. This is known as Network-Enabled Capabilities or information-age C2. Experience has shown that multiple factors must co-evolve to gain the full benefit of transforming C2 to become network enabled. In this chapter, the authors group these factors into five layers: geographical, physical, information, cognitive, and socio-organizational. They formalize the key entities in each layer, together with within- and across-layer relationships, into a conceptual ontology, known as the Formalized Layered Ontology for Networked C2 (FLONC). To ensure the ontology is militarily relevant, the authors show that a set of networks found in military operations can be extracted from the ontology. Finally, they compare the formalized ontology to related work on ontologies in C2. In further research, the ontology could be used in developing software to simulate and support network-enabled C2 processes. A case study based on the events of September 11, 2001 shows how this could be done.

Modelling Command and Control in Networks

This chapter proposes an approach to modelling the functions of C2 performed over a network of geographically distributed entities. Any kind of command and control (C2) organisation, hierarchical, networked, or combinations thereof, can be represented with this approach. The chapter also discusses why a theory of C2 needs to be expressed in functions in order to support design and evaluation of C2 systems. The basic principle of how to model functions performed by network is borrowed from Cares' network model of warfare, which is also used to model the context in which C2 is performed. The approach requires that C2 is conceived of as fulfilling a set of necessary and sufficient functions. Brehmer proposes such a theoretical model that is at a sufficiently high level of abstraction to illustrate the suggested approach. More detailed models will be required, however, for the approach to be of practical use.

Cyber Security in Tactical Network Infrastructure for Command and Control

Emerging information and communications technology has had significant importance for military operations during the last decades. Development within such technology areas as sensors, computers, and wireless communications has allowed for faster and more efficient collection, transmission, storage, processing, analysis, and distribution of data. This has led to new and improved military capabilities within command and control, intelligence, targeting, and logistics. However, the increased complexity and interdependencies of networked systems, the continuously growing amounts of data, changing non-technical requirements, and evolving adversary threats makes upholding cyber security in command and control systems a challenging task. Although some best-practice approaches have been developed, finding good solutions for protecting critical infrastructure and important information assets is still an open research question requiring an interdisciplinary approach. This chapter describes recent developments within emerging network technology for command and control, and suggests focus areas where further research is needed in order to attain sufficient operational effect from the employed systems. While a gradual and evolutionary progress of military cyber security has been seen, a long-term commitment is required within such areas as procurement, standardization, training, doctrinal, and legal development, in order to achieve military utility of command and control systems.