Towards an Agile Joint/Coalition Embedded C2 ...

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island

BLACK-CACTUS – Towards an Agile Joint/Coalition Embedded C2 Training Environment Per M. Gustavsson Training Systems and Information Fusion Saab Microwave Systems / University of Skövde Storgatan 20 541 30 Skövde Sweden +46-(0)31-794-8939 [email protected]

Dr. Michael R. Hieb Vikram Kamath Center of Excellence in C4I George Mason University 4400 University Drive Fairfax, VA 22030 USA 001-703-993-3990 [email protected] [email protected]

Magnus Grönkvist Saab Systems Air and Land Systems Nettovägen 6 175 88 Järfälla Sweden +46 (0)8-580 852 77 [email protected]

Jakob Blomberg Saab Training Systems Stortorget 7 SE-252 20 Helsingborg Sweden +46-(0)42-13 20 05 [email protected]

Joakim Wemmergård Swedish Defence Material Administration SMART-Lab 115 88 Stockholm Sweden +46-(0)8-7824000 [email protected] ABSTRACT The Net Centric and Global Information Grid (GIG) visions envision systems that will be interconnected to support multi-lateral, civilian and military missions. The constantly changing environment requires commanders and leaders to plan for missions that allow for units from various nations, agencies, etc. to join or separate from the team, depending on the situation, as the mission unfolds. Training performed at home stations and in mission training/mission rehearsal may occur just days, hours or even minutes before the actual missions. This need for rapid mission-specific rehearsal capabilities and multilateral environment drives requirements to 1) develop a simulation infrastructures that enable embedded simulation capability in the operational systems and 2) develop interoperability mechanisms that enable a more agile, dynamic and adaptive interconnection of heterogeneous simulations. In this paper the lessons learned from the novel BLACK-CACTUS project (Bi-LAteral Collaboration and Knowledge exchange – Command And Control To US and Sweden) is presented. The project shows an agile method of integrating Command and Control Systems and Computer Generated Force engines using the Command and Control Lexical Grammar (C2LG) together with the Widely Integrated Systems Environment (WISE) integration platform. The C2LG is the semantic glue that ties the information parts together and WISE is the framework for disseminating information through several of protocols and information models. The BLACK-CACTUS Proof of Principle consisted of the C2LG GUI, the TVT Vehicle Battle Management System (VBMS), the Joint Semi Automated Forces (JSAF) Simulation, the WISE platform, and the Joint Battle Management Language (JBML) web server and services. This paper presents the architecture, the implementation and the rational why a C2LG together with integration methods provides agile Joint/Coalition Embedded C2 Training Environments.

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1. Introduction This paper presents the demonstration of the ongoing BLACK-CACTUS project which stands for ”BiLAteral Collaboration and Knowledge exchange – Command And Control To US and Sweden” that was conducted during August 2007. It is a project aiming at enabling interoperability amongst operational Command and Control (C2), as well as providing C2embedded training in a way that has not been able to be realized before. The outline of this paper starts with a description of an operational need, following by chapters on Interoperability, Information Centric Integration, Next Generation Training Systems Battle Management Language, command and control grammar, the BLACK-CACTUS demonstration architecture, implementation and ends with a summarization of results.

2. Operational Need Basically, the project deals with the fact that networkcentric operations and effect based operations require systems to be interconnected to support multi-lateral civilian and military missions. The constantly changing environment calls for the commanders to plan for missions that allow for units from various nations, agencies and similar to join or separate from the team, depending on the situation, as the mission unfolds. The uncertainty of the actual mission, and the fact that agencies and organizations should be able to support the mission even after it is underway, leads to a vast number of potential scenarios, which civil and military personnel need to exercise in individual and collaborative training environments. However a major drawback of using computersimulated training is the need for large contingents of support personnel to act as workstation controllers and provide the interface between the training unit and the simulation. The group of workstation controllers is often as large as, or larger than, the training audience. While this enables training opportunities at the corps and division echelon, it is still resource-intensive and lacks the degree of fidelity that actual combat operations present to the commander and staff. Each major simulation used today to represent military operational forces has a representation that expresses how to task simulated units. Unfortunately, each of these are often specific to the own simulation and is often driven by technical constraints of the simulation

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system and not by operational necessities of the war fighter. A flexible and extendible representation of reports, orders and commander’s intent could facilitate both interoperability and support for future automated systems. Even though reports, orders and commander’s intent can be expressed in textual representations, not all recipients will get the information out of a free-text expression. They need a formalized representation. These recipients include coalition forces not speaking English as their native tongue, simulated forces, exercise/training systems, decision support and future (smart) robotic forces.

3. Interoperability Traditionally, systems and applications are connected directly to one another. To integrate more than one application, there is a need to establish several connections. Each application may use a different communication protocol, a different information model, and perform differently. For a connection to work, each application has to be upgraded to be able to understand and function together with the other. As a result, a lot of the integration effort is diverted towards technical platform details. Commonly the two ways of enabling interoperability are by using Application Centric Integration or Interface Centric Integration (Gustavsson and Lundmark, 2007). •

Application Centric Integration is best suited when there are only two systems to be integrated. It requires that each application is individually adapted to the selected protocol. These adaptations are usually also restricted to a minimum in terms of the information being exposed. The full capacity of each application will therefore not be available. The integration points are at each end and are usually hard coded into each system.

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Interface Centric Integration: When more than two systems are connected together the common solution is to identify a set of data elements in an agreed format with an agreed meaning using a specific protocol. The two commonly used standards for simulations are the Distributed Interactive Simulation (DIS) specified in IEEE1278, and High Level Architecture (HLA) specified in IEEE1516. The DIS uses the well defined Protocol Data Units (PDU) that holds the syntax and semantics. HLA is more flexible than

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island DIS and the Object Model Template (OMT) is used as the common syntax to describe the meaning of all object and interaction classes within the Federation Object Model (FOM). Overall the focus is on the interoperation of systems and to exchange data and every system agrees to map their information exchange to the common information exchange model. The integration points are still at each application’s end and usually hard coded. Each application will still need to be adapted to the shared protocol which usually restricts the information being exposed to the shared protocol. The full capability of each application will still not be exposed. Common problems that arise using the above integration methods are: •

Complex Integration: To integrate a new application, it may be necessary to upgrade several existing applications. The more applications that are integrated, the more complex it becomes to integrate an additional application. Further, when upgrading an application, existing functionality may be affected, requiring even more work. This complexity makes it hard to adapt to new protocols.

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High Costs: Each additional application that is integrated potentially requires more integration work than the last one. This makes integration costs increase exponentially. The integration becomes more and more complex for each application that is integrated. Further, since each additional application that is integrated may affect several other applications, life-cycle costs will also remain high.

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Long Time-to-market: The time-to-market is how long it takes to create a new function by integrating a number of applications that together satisfies a new need or sudden requirement. Since integration is complex, the time-to-market will be long.

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Rigid Integration: To change the way a number of applications are integrated may require reintegration of the applications all over again because of the interdependency between the applications. Integration is rigid, and inflexible.

4. Information Centric Integration Information Centric Integration offers the potential to move the system integration points into the information infrastructure giving the integrator full control of the integration. These integration points are configured and not hard coded into the information infrastructure. One way of enabling information centric integration is Common Reference Models (CRM). Model Based Data Engineering (MBDE) (Tolk et al., 2007) describes how to build such CRMs. The CRM supports data engineering that consists of four parts: Data Administration answer the questions: “Where is the data? In what format? How can the data be accessed?” Data Management answers the question: “What does the data mean?” Data Alignment answers the question: “Can all of the needed data be obtained?” and Data Transformation answers the question: “How to transform/mediate the data?” The introduction of a CRM supports the process of Data Engineering. When a CRM is used data alignment may be a less complex task. After target and source are mapped to the CRM, it is possible to compare the mapping of the source model to the CRM with the mapping of the target model to the CRM. If every information element of the source and target model is mapped to an element of the CRM, the models are aligned. If all of the data needed by the target model is not available from the source model, either directly or through transformations of the source data, then the two models are not directly alignable and the mapping will not be possible. The identified gap indicates that a target system will not get all the information it needs from the CRM instantiation, i.e. the source system can not deliver it. Then the solution is to either add another system with another data model that can deliver the missing data elements, i.e. a sort of fusion between the source system and the newly added system, the other way is to extend the data elements in such way that they do not effect the target systems behavior. There are many commercial tools that perform data mappings, but the actual process of mapping data between two models is still time consuming and requires Subject Matter Experts.

5. Next Generation Training Systems Next Generation Training Systems need to allow fast integration of systems for the purpose of doctrine

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Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island development, training and exercises. The first step in any process is to define the purpose of why systems shall be interoperable. Then find out if and how they can be made interoperable. The later part can be made easier by carrying out an Information Needs Analysis using the Model Based Data Engineering and a Common Reference Model with transformation, mediation and mapping tools and utilities so that a separation of protocols and information can be provided and that information can be unambiguously exchanged amongst systems. Communication protocols will continue to evolve. How is it possible to achieve information interoperability over time? •

By focusing on the information flow between systems – not on individual communication standards, protocols, or software platforms.

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By making it possible to “connect” information from different systems regardless of communication standards and protocols.

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By making it possible to control the information flow between connected systems. 5.1 New Communication Protocols

If no new protocol will solve all problems, how is it possible to achieve cost-effective training? •

By using a common training environment where different systems can work together regardless of protocols and internal object models.

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By focusing on the information that each system contributes to the common training environment not on individual protocols, architectures or information exchange models.

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By integrating the common training environment with configuration mechanisms instead of software programming.

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By allowing the user to define the common information model.

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By integrating information communication protocols.

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The Widely Integrated Systems Environment (WISE) is a software suite and an integration platform that provides connectivity amongst systems or applications into a common environment and creates an information flow between them, regardless of architecture, communication standards and protocols. It also offers a comprehensive overview of all the action taking place in it – allowing the monitoring and viewing of entities and events in real time. In Figure 1 the internal architecture of WISE is illustrated and consists of: X

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Since there will be new communication protocols, will they be able to solve all current problems? Will they be • Transformation, T in the figure, performs the able to reduce both complexity and costs? The short alignment and transformation between information answer is no. Even if a new protocol would solve all object models. In that the defined type-conversions present problems, it cannot be prepared for all future problems. And what if a legacy system cannot be adapted to use the new communication protocol. That system would no longer be useful. Also, remember that different communication protocols are designed to solve different problems. Using the same protocol for different systems, such as live, virtual Transformation Transformation and constructive systems, will not be very effective even if they use the same information model. In short, no single communication protocol will solve all problems. That is why it is necessary to understand the need to combine systems and applications that use different protocols and information exchange data models. Protocol Storage Protocol

Figure 1 - WISE architecture 08S-SIW-017


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use of lookup-tables, concatenating, aggregation etc. between data element are conducted.

6. Battle Management Language

Datamanager, controlling the information object model in the application. The S stands for services and provides the ability to prepare or refine the information before it is published to the Common Reference Model. A service offers also the possibility to prepare or refine the information before the subscription is delivered to the application.

The Battle Management Language (BML) is formally defined in (Carey et al., 2001) as “…the unambiguous language used to command and control forces and equipment conducting military operations and to provide for situational awareness and a shared, common operational picture”. (Figure 2)

Driver, implements how the application communicates with other applications. The driver transfer changes in the information model to the native protocol and update the information model according to the protocol.

A guide line is to strive for that as much as possible of the alignment is made with transformations, since they are easy to change and maintain. The second best is to build services for the specific information object model, which then still allows for the driver to be re-used with other information models. Of course it is possible to put conversions and alignment into the driver but then the power of the integration framework is more or less lost. A straight forward example is when connecting a HLA RTI with some other model. Then the driver needs to be built to support the specific RTI of choice, the FOM needs to be described as an Object Model and transformations needs to be defined for the objects. The RTI driver can be reused since it does not have any connections with the object model. The object model, i.e. FOM, can be used by other drivers, i.e. other RTI drivers. From the user application the WISE instance is just like another federate. With the transformers and services there is a whole set of functionality that can be built in such as: •

Extended functionality in a connected application.

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Refine information from an application, adding dead reckoning.

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Aggregation/Disaggregating.

Services and transformations are plug-in and can be developed for the particular requirements an integrator may need.

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BML tasking: Command and Control Forces and Equipment

BML reporting: Provide for Situational Awareness

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C2 System

Simulation System

Robotic System

Figure 2 - BML Tasking and Reporting

Using BML, it should be possible for C4I systems, simulation systems, and emerging robotic forces to communicate unambiguously with any of these other types of systems. Such system-to-system communication is demanding enough when it involves systems within the same organization. It grows even more complex and demanding incorporating other organizations and nations. There are three guiding principles that must be followed in order for a BML implementation to function correctly. (1) BML must contain minimal ambiguity; (2) BML must avoid constraining the full expression of the commander’s intent; (3) BML must allow any elements (that is, some live, constructive, or robotic entity) to communicate information pertaining to itself, its mission and its environment in order to create situational awareness and a shared, common operational picture across all elements. To justify why a data model such as the Joint Consultation Command and Control information Exchange Data Model (JC3IEDM) that is developed by Multi-lateral interoperability Program (MIP) (M I P, 2008) is not sufficient is actually the rationale for the C-BML work and described in the C-BML Study

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island group report (Blais et al., 2005) together with the envisioned future usage of C-BML. In the work by (Schade and Hieb, 2006b, Hieb and Schade, 2007) they present a brief analysis on why just relying upon a data model is insufficient for military communication. First, the JC3IEDM is designed for planning and status, but not for actually performing tasks. Second, the JC3IEDM is not able to represent orders, requests, or reports as entities which concatenate single expressions about actions and states in a cohesive way. Third, the JC3IEDM is for exchanging data, and aims to create shared situational understanding. However in both an operational and simulation context information is exchanged. Further information exchange should be driven by military doctrine. Only then can meanings and intentions be communicated. To express such information richness Hieb and Schade states one way is to develop a grammar that provides rules constituting how the lexical elements of the language in question can be connected and how the meaning of the catenation can be derived from the meaning of the parts if the parts are connected according to the grammar’s rules. For example, grammar determines that in the sentence “The US general ordered the German general to attack” it is the German unit that will attack whereas in the sentence “The US general promised the German general to attack” it is the US unit. The Command and Control Lexical Grammar (C2LG) (Hieb and Schade, 2007) has then been used in the The Joint Battle Management Language (JBML) (Pullen et al., 2007)demonstration and in the NATO Modeling and Simulation Group (MSG-048) (Nico et al., 2008, Pullen et al., 2008a, Pullen et al., 2008b). For the BLACK-CACTUS project the idea is to provide proofs of concept using agile reference models together with operational Command and Control Systems showing the future of embedded training. Then the decision to use the C2LG and JBML became an easy choice to make.

7. Command and Control Grammar Starting with the 5Ws of the BML concept (Who, What, When, Where, Why), the initial work focuses on defining a tasking grammar to create basic phrases relative to the orders aspect of the BML grammar. This work follows the linguistics-derived standard developed by Schade and Hieb (Schade and Hieb, 2006a, , 2006b, Hieb and Schade, 2007, Scahde and

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Hieb, 2007) called the Command and Control Lexical Grammar (C2LG). The C2LG is used to describe the activities or tasking a set of battle assets will engage in and is defined by the following expression structure: S = OB* C_Sp* C_T* Where the OB term defines the unit identifier information for the task, C_Sp term defines the location in space of the activity and C_T term defines when in time the activity will happen. The asterisk (‘*’) means that an arbitrary number of terms can be concatenated. The basic C2LG expression takes the form of a tasking verb, a terminal symbol and the corresponding information frame. The tasking verbs that form the basis of the C2LG are derived directly from the definition of the JC3IEDM action-task table which contains a field named “action-task-activitycode”. Thus, the C2LG sentences describe when and where some activity is to take place. The C2LG is based on a formal linguistics model known as Lexical Functional Grammar (Bresnan, 2001). Its formal properties make it particularly suited for a computational language. According to the linguistic principles as given above, we define basic order expressions as composed of a verb and its frame. The verb denotes a task. For the tasking grammar, tasking verbs could be taken from JC3IEDM’s table “action-task-activity-code.” Thus, the rules to expand OB have the general form as given in (2a). (2b) and (2c) give examples for the tasks “advance” and “defend,” respectively. (2a) OB → Verb Tasker Taskee (Affected|Action) Where Start-When (End-When) Why Label (Mod)* (2b) OB → advance Tasker Taskee Route-Where Start-When (End-When) Why Label (Mod)* (2c) OB → defend Tasker Taskee Affected AtWhere Start-When (End-When) Why Label (Mod)* Tasker is the name of the one who gives the order. Taskee is the name of the unit that is ordered to execute the task. Start-When and End-When are temporal phrases expressing when the execution of the task has to start and when it has to be finished. EndWhen is not needed in all cases, as indicated by the parentheses. Tasker, Taskee, Start-When, and EndWhen appear in each basic order rule.

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island Affected in (2a) must be a term in the expression if someone (e.g., the enemy) will be directly C2LG GUI TVT 2.0 WISE Connectivity WISE DOB DOB affected by the task. Whether WISE BML WS Affected is part of a rule depends BML WS on the tasking verb. For example, it is there in the case of attack or defend because the executing unit is tasked to attack the enemy or to defend against the enemy. It is not BML WS there in the case of advance. The tasking verbs come with frames BML WS JSAF that express which types of JC3IEDM constituents are required, e.g., a constituent of type Affected. This enforces the principles of completeness and coherence. Action is similar to Affected. It Figure 3 - BLACK-CACTUS Architecture only appears if the task affects an action, as a task of type assist does – the unit is tasked to assist temporal coordinates. The optional Mod (for modifier) the execution of another task by another unit. In is a wild-card that represents additional information addition, the type of the Where is also determined by that can be used to describe a particular task, e.g., the verb. It is currently an At-Where or a Routeformation – to specify a particular formation for an Where. An At-Where denotes a location, and a Routeadvance – or manner – to express for example whether Where a path to a location. A Route-Where can be the task in question has to be completed as fast as expanded to more complex concatenations of possible or more slowly, without taking any risks. constituents as in “from LocationA to LocationD via Modifiers are particularly important for decision LocationB and LocationC.” support. A basic rule ends with Why, Label and the optional Mod. Why represents a reason why the task specified by the rule is ordered – the mission’s purpose. Label is a unique identifier for its task. By this identifier the task can referred to in other expressions, especially in

Figure 4 - C2LG GUI sends an Attack

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8. BLACK-CACTUS The BLACK-CACTUS initial proof of concept demonstration setup is illustrated in Figure 3. The setup consisted of the Command and Control Lexical Grammar Graphical User Interface (C2LG GUI), JSAF Computer Generated Force a JBML web server with an extended JC3IEDM database, JBML Parser executable (developed by the ACS) and the Widely Integration Systems Environment (WISE) together with the operation Tactical Vehicle Terminal that are deployed to the Nordic Battle Group 2008. The demo system was executing both at the C4I Center at George Mason University and at the Concept Development Center at Saab Järfälla as well as the Saab facility in Helsingborg, both in Sweden, X

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Figure 5 - TVT receives the order using the SPINE network. SPINE is the infrastructure that consists of routers, firewalls, crypto and virtual private network (VPN) tunnels and is configured in a black box that plugs into the internet. SPINE is the back-bone for Saabs Capability Development Center (CDC) nodes that are scattered all across cities, nations where Saab is driving and participating in projects like the one described in this paper. The CRM used is the one developed by Saab Training Systems (STS) and is made to enable a whole variety of information models and protocols, e.g. HLA, DIS, Link16, and MIP/JC3IEDM. The JBML web-services were implemented into WISE drivers and the information model of JBML was aligned with the STS-CRM, thus enabling orders to literally be enable through HLA, DIS, Link16 etc. F

The scenario used do not have the purpose of being tactical or doctrinal correct. The purpose of the scenario is to show the dissemination between heterogeneous C2 systems and simulation system using the C2LG for describing orders. The scenario is that the Estafishians have reoccupied a territory previous occupied by Orbenaxians. The Nordic Battle Group (NBG) has been deployed to monitor the agreed cease fire amongst the two fractions.

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However in the area there are some militia units that are opposing the NBG operations since it will interfere with their normal business. The mission is to establish control and maintain security in the area. The Beta battalion has been given the mission to hold a supply road open. During their patrolling a hostile militia unit is spotted and the Beta battalion gets some units under fire. The commander of the Beta battalion then issues an order to the Alpha company commander with the order to attack the militia unit and with the purpose to divert them. The Alpha company commander then makes up a plan in how to use his platoons. The order is given to the Gamma platoon that engages the hostile militia and then the scenario ends. The first phase of the demonstration, described by filled arrows in Figure 3, was to show how the order issued by the NBG commander, using a C2LG GUI system (Figure 4), can be transferred to the TVT system. The order was composed using the C2LG GUI and inserted in the extended JC3IEDM by using the JBML web-services. X

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To formulate an order using the C2LG GUI an operator performs the following actions: 1) select an ‘action’ from the drop-down list, 2) Select the appropriate

Figure 6 - TVT issued order

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island ‘Taskee’. 4) Select the ‘route’ or ‘location’ by clicking over the map and entering the co-ordinates directly or by selecting a pre-filled path from the BML Path-Editor list. All the non-mandatory items can be entered depending on the requirement. 5) Enter the value for ‘Why’. 6) Press ‘Test’ to generate the BML-Sentence. 7) If the sentence looks promising it can be appended to the Discourse List as a ‘task’. 8) On pressing ‘Send Order’, a XML based description of the C2LG BML sentence, which conforms to the JBML schema version 1.2 format is generated. This order is pushed into the JC3IEDM database via the JBML Web-Service Interface. Since the C2LG GUI uses the JBML services it has the full capacity to express any order that the C2LG can compose. The order was then stored internally in the JC3IEDM, running on a mySQL server. The order was then pulled by the WISE driver, this since the JBML services at the time of this demonstration did not have any push mechanism. The driver then populated the internal object model representing the JBML structure and transforming the attributes to fit with the STS-CRM. Then, the information residing in the STS-CRM was transformed into the internal object model used in TVT, named DOB The information was then pushed from WISE .

Figure 7 - JSAF receives order using the DOB-Driver and received in textual form by TVT. The information was then mapped to graphics and the NBG commander order was then visible in the TVT (Figure 5). X

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The second phase, the dotted arrows in Figure 3, was to issue an order inside the TVT and send it to a computer-generated force (CGF). The Alpha company commander then made an overlay pinpointing the Gamma platoon to attack the hostile militia (Figure 6). The graphical representation was then decomposed into a text message within TVT and communicated by using the DOB information model and DOB protocol to WISE. X

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Within WISE the received order from TVT was inserted into the object model for DOB and then transformed to the STS-CRM. The received order was then sent to the CGF (JSAF) using the JBML web-services. The CGF then executed the order given by the Alpha company commander. In Figure 7 the order has been received and is on its way to be performed. X

Figure 8 - TVT visualizes the CGF information

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The units visible in TVT were sent to the TVT using the DIS connectivity in JSAF. Since the DIS protocol and PDUs previously has been integrated within WSIE, i.e. driver implementation, object model and

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island methods and procedures from the net-centric paradigm.

transformations. Thus when starting the scenario the units in JSAF was automatically enabled in TVT system without any further coding or integration which concluded the demonstration (Figure 8). X

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To implement the MSDL specification to enable the set up and start of scenarios where not all systems uses the MSDL as an input, i.e. the various scenario definition models then can be aligned with MSDL as the base CRM for simulation.

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Coordination and cooperation in joint military and civil missions with the need for agile training environments request that dissemination of information is possible. In the ongoing work of a Crisis Management Language (CML) (Gustavsson et al., 2006, Gustavsson et al., 2008) that follows the C-BML standardization such approach is under its way and some hands on experiments is the next step to take, i.e. extending the BLACK-CACTUS into a WHITE-SPRUCE (WHat Information Technology Environment is required for a Simulation PRodUct aiming at civil-military Collaborative Education).

9. Summarization In this simple proof of concept, it was not only proved possible to give, receive and present orders, but also showed how to perform real-time simulations without changing the interfaces in any of the systems. This showed that the idea of next-generation training systems is a fact, and that C2LG together with WISE gives the capability to develop agile C2-embedded training systems. This in turn means that C2 operators can use their own C2 systems to run simulations, eliminate ambiguous orders, and enhance coalition operations, thereby reducing training costs. Several other projects have used the C2LG GUI to evaluate the language for tasking and reports. Muguira et. al. (Muguira et al., 2008) also implemented the C2LG in a Proof of Principle demonstration to simulate a realistic scenario for JC3IEDM-based C2 system (SitaWare). Borgers et. al. (Borgers et al., 2008) implemented the C2LG in a multi-agent environment using an aggregate Netherlands Army Simulation. Both of these projects as well as the BLACKCACTUS, used the syntax of the C2LG without using the JC3IEDM directly. For the future the illustration in Figure 9 gives the overall intention. However the four first items on the agenda are: X

C2 - TVT

For the standardization of a C-BML this and the other experiments show that the C2LG can indeed be used with operational systems and provide a mechanism to disseminate orders to and from CGF and there by be a part in enable the envisioned agile training capability.

C2 - DACCIS

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Include more systems using different protocols and information models such as Link16. With such a connection WISE will provide interoperable between C2LG BML based systems and Link16 systems. Enable the CGF in the BattleTek Simulation with the ability to receive not only orders but also the Commander’s Intent to allow for a more effect-based training and education approach, i.e. enabling training of agile concepts,

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C2 – STRIC AOC

C2 – 9C2

Civil C2 - WCU

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CGF - StricS

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SAM SIM – RBS70

FlightSIM – T3SIM CGF - TACSI

Figure 9 - Planned Expansion of BLACK-CACTUS


Acknowledgements We honor all our co-workers at Saab and at C4I Center, George Mason University for all their work during the BLACK-CACTUS demonstration. Per Gustavsson was a visiting scholar at the C4I Center during the summer of 2007 and is an Affiliate Assistant Professor at the Center.

References Blais, C., Galvin, K. & Hieb, M. R. "Coalition Battle Management Language (C-BML) Study Group Report", Paper 05F-SIW-041 in the Procedings of Fall Simulation Interoperability Workshop, September, in Orlando, FL, U.S.A, 2005. Borgers, E., Spaans, M., Voogd, J., Bonse, R. & Hieb, M. "Using a Command and Control Language to Simulate Operations in a Multi-Agent Environment", Paper I-155 in the Procedings of 13th International Command and Control Research and Technology Symposium in Bellevue, WA, 2008. Carey, S. A., Kleiner, M. S., Hieb, M. R. & Brown, R. "Standardizing Battle Management Language - A Vital Move Towards the Army Transformation", Paper 0F1-SIW-067 in the Procedings of Fall Simulation Interoperability Workshop, September, in Orlando, FL, U.S.A, 2001. Gustavsson, P. M., Garcia, J. J., Wemmergård, J. & Norstedt-Larsson, M. "Expanding the Management Language Smorgasbord - Towards Standardization of Crisis Management Language (CML)" in the Procedings of IEEE Spring Simulation Interoperability Workshop, April, in Huntsville, AL, US, 2006. Gustavsson, P. M., Hieb, M. R., Niklasson, L., Eriksson, P. & Moore, P. R. "Machine Interpretable Representation of Commander's Intent" in the Procedings of International Command and Control Research Symposium (13th-ICCRTS), June 17-19, in Bellevue, WA, 2008. Gustavsson, P. M. & Lundmark, S. "One Step Further Towards the Next Generation Training Systems" in the Procedings of I/ITSEC-07, November 2007, in Orlando,Fl, U.S.A, 2007.

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Hieb, M. R. & Schade, U. "Formalizing Command Intent Through Development of a Command and Control Grammar", Paper I-069 in the Procedings of 12th International Command and Control Research and technology Symposium, June, in Newport, RI, 2007. M I P. "MIP Website", http://www.mip-site.org, 2008. Muguira, J. A., Kamath, V. & Hieb, M. R. "Applying Battle Management Language (BML) to a Command and Control Application: Lessons Learned", Paper 08S-SIW-039 in the Procedings of Spring Simulation Interoperability Workshop, in Providence, RI, 2008. Nico, R., Paul, K., Mevassvik, O.-M., Alstad, A., Schade, U. & Frey, M. "BML Enabling of National C2 Systems for Coupling to Simulation" in the Procedings of Spring Simulation Interoperability Workshop, 2008. Pullen, J. M., Carey, S. A., Cordonnier, N., Khimeche, L., Schade, U., Reus De, N., N. Le Grand, Mevassvik, O.-M., Galan, S., Gonzales Godoy, S., Powers, M. & Galvin, K. "NATO MSG-048 Coalition Battle Management Initial Demonstration – Lessons Learned and Way Forward", Paper 08S-SIW-082 in the Procedings of Spring Simulation Interoperability Workshop, in Providence, RI, 2008a. Pullen, J. M., Hieb, M. R. & Levine, S. "Using Web Service-based Command and Control to Support Coalition Collaboration in C2 and Simulation", Paper I-234 in the Procedings of 13th International Command and Control Research and Technology Symposium, in Bellevue, WA, 2008b. Pullen, J. M., Hieb, M. R., Levine, S., Tolk, A. & Blais, C. "Joint Battle Management Language (JBML) - US Contribution to the C-BML PDG and NATO MSG-048 TA" in the Procedings of European Simulation Interoperability Workshop, 2007. Scahde, U. & Hieb, M. R. "Battle Management Language: A Grammar for Specifying Reports", Paper,” Paper 07S-SIW-036 presented at the in the Procedings of Spring Simulation Interoperability Workshop March, in Norfolk, VA, 2007. Schade, U. & Hieb, M. R. "Development of Formal Grammars to Support Coalition Command and Control: A Battle Management Language for

Spring Simulation Interoperability Workshop 2008 Providence, Rhode Island Orders, Requests, and Reports", Paper Paper I-069 in the Procedings of in the Proceedings of the 11th ICCRTS, in Cambridge, UK, 2006a.

MICHAEL R. HIEB is a Research Associate Professor at the Center for Excellence in C4I at George Mason University

Schade, U. & Hieb, M. R. "Formalizing Battle Management Language: A Grammar for Specifying Orders", Paper 06S-SIW-068 in the Procedings of Spring Simulation Interoperability Workshop, April, in Huntsville, AL, U.S.A, 2006b.

MAGNUS GRÖNKVIST works at Saab Systems as a system specialist in training and simulation at the Air and Land division.

Tolk, A., Diallo, S. Y. & Turnitsa, C. D. 2007. Data Engineering for Integration of Heterogeneous Homeland Security Applications. In Journal of Aerospace Computing, Information, and Communication: (To Be Published).

Author Biographies PER M. GUSTAVSSON is a Senior Research Scientist at the Training Systems and Information Fusion office at Saab Microwave Systems working with applied research in the area of advanced decision support systems. He is also an industrial Ph.D. student at University of Skövde, Sweden and Assistant Professor at C4I-Center, George Mason University. Gustavsson holds a M.Sc. in Computer Science, New Generations Representations, Distributed Real-Time Systems and a B.Sc. in Systems Programming both from University of Skövde, Sweden.

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VIKRAM KAMATH is a Masters Student in Electrical Engineering and researcher with the C4I Center of George Mason University in Fairfax, Virginia. He worked as a Software Developer at Infosys Technologies Limited, India from Oct 2003 Jul 2006. He received his Bachelors in Electronics and Telecommunication at University of Bombay (Mumbai), India in 2003. JAKOB BLOMBERG is a software engineer at Saab Training Systems. He works as a system integrations expert in the field of live, virtual and constructive integrations. B. N. JOAKIM WEMMERGÅRD is a Project Manager at the division SMART-lab at Swedish Defence Materiel Administration, FMV, in the field of both research and development of different M&S systems and projects. He has the position of Program Manager for the development of the future M&S Infrastructure and Design Guidelines for the Swedish Armed Forces, is a POC for a Project Agreement with RDECOM in the field of M&S as well as an Enterprise Analyst at FMV. Wemmergård holds a M.Sc. in Mechanical Engineering, Computer Systems for Design and Manufacturing, from The Royal Institute of Technology, Sweden.