Leo Motus

Time-awareness and Proactivity in Models of Interactive Computation

The paper discusses explicit properties and the requirements that are to be verified, imposed upon software-intensive systems by their environment and by their users. Those systems are time-critical, may contain autonomous components, and may exhibit proactive behaviour. It is suggested that the analysis and verification of properties in software-intensive systems requires time-aware model of interactive computation. The authors of this paper claim that hitherto used time interpretation in computer science is too simplified, and several simultaneously maintained independent time counting systems is a necessary precondition for timing analysis of interactions. A feature space for comparing the existing approaches to interactive computing is suggested, and a potential candidate for time-aware model of interactive computation is discussed.

Towards middleware based situation awareness

Potential solution to some problems related to forming, updating, and personalized distribution of companys level local operational picture (LOP) is suggested. Sensor networks, information collected by UAV-s and UGV-s, observations from reconnaissance parties, larger scale COP that sporadically become available are considered as sources of information. At the companys level LOP has to be made available in a personalized form to any member (including autonomous devices) of the company.

On-line data validation in distributed data fusion

Data acquisition and data fusion systems are becoming increasingly complex, being in fact systems of systems, where every component may be a system with varying levels of autonomy by themselves. Possible changes in system configuration by entities joining or being removed from the system make the system complex. As synchronous operation cannot be expected in such a system configuration, the temporal and spatial correctness of data must be achieved via other means. This paper presents the concept of mediated interactions as a method for ensuring correctness of computation in a distributed system. The mediator associated with each computing entity is responsible for online checking of the data both before it is sent out at the sender side and before it is received at the receiver side, ensuring that only data satisfying the validity constraints of the receiver-side data processing algorithm is used in computation. This assumes that each data item is augmented with metadata, which enables online data validation. The validity and quality dimensions in use depend on the system requirements defined by a specific problem and situational context; they may be temporal, spatial and involve various data quality dimensions, such as accuracy, confidence, relevance, credibility, and reliability. Among other capabilities, the mediator is able to cope with the unknowns in the temporal dimension that occur at runtime and are not predictable, such as channel delay, jitter of clocks and processing delays. This capability becomes an especially relevant factor in multi-tasking systems and in configurations in which a computing entity may have to process a variable number of parallel streams of data. Both the architecture and a simulation case study of a distributed data fusion scenario are presented in the paper.

Situation awareness for networked systems

Modern technology offers the possibility to construct networked monitoring systems from autonomous computing nodes equipped with appropriate sensors. Complementing such a system with actuators yields a cyber-physical system that must be able to cope with uncertainties arising from feedback loops via the physical world. The common property of such systems lies in the high degree of uncertainty in the varying configuration of the system and also in the potentially high amounts of (unstructured) data that can be generated by such a system. In order to tackle these problems and make the distributed monitoring systems more usable the concepts of situational information and hierarchies of situations can be applied in this domain. The problem of high amounts of data can be partially solved by arriving at a higher level of abstraction lower in the processing chain, communicating only data fused into an ontological structure to information consumers. The fusion templates are called situation parameters and values of the fused data items are called situational parameter values in the context of the current article. Situation parameter values must be tagged with situational and temporal validity information in order to cope with the delays and spatial uncertainties that can occur in a distributed monitoring system. The lower level situation parameters can be fused to even higher level situation parameters, projecting the temporal and spatial validity information from the lower level parameters up to the higher level parameters. The article presents the concepts of forming situational information templates and hierarchies based on data available from a distributed monitoring system where the temporal and spatial properties of situational information are taken into account. A case study is presented that shows the feasibility of the concepts in a real world monitoring scenario.

Data to decision: pushing situational information needs to the edge of the network

Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.

Location awareness of information agents

This paper discusses the use of generic geospatial agents (provided by agent development environment KRATT) for collecting and processing location aware information. The approach is essentially based on agent-based digital map processing software that is capable of handling raster or vector maps, and maps with different colour schemes, with different packing methods, with different systems of signs, etc. Each application can be configured and reconfigured dynamically. Agents, and the applications that use services provided by agents, are not in one-to-one relationship; one agent can simultaneously work with many applications. Also, an agent may use services from different agents in different situations. The approach is illustrated by pilot applications, such as participatory GIS, tracking of active objects, information collection and navigation in a sensor network with beacons.

A System of Systems solution for perimeter control: Combining Unmanned Aerial System with unattended ground sensor network

The paper describes a novel and practical System of Systems (SoS) approach for perimeter control in ISR (Intelligence, Surveillance and Reconnaissance) applications. The SoS combines an Unmanned autonomous Aerial System (UAS) with an Unattended Ground Sensor (UGS) SoS in order to provide enhanced situation awareness to the users. A simple mini Unmanned Aerial Vehicle (UAV) with an autopilot capable of waypoint navigation is equipped with additional hardware to become a UAS and is integrated with an existing UGS network, forming a System of Systems of heterogeneous systems. The systems in the resulting SoS are autonomous and they offer the generated information via a subscription based service architecture. The SoS described in the paper offers its detection and identification capabilities as services to external entities. The UGS nodes autonomously detect objects and phenomena of interest (based on information requests received from external entities) and by building up collective situation awareness they are able to classify the detected objects, involving the UAS in image acquisition if an object of interest has been classified. The data collected by the SoS is combined and delivered to the external entity that made the information request. The paper describes the creation of the UAS, its integration with an existing SoS and the evaluation of the performance of the resulting SoS.

Self-aware architecture to support partial control of emergent behavior

System of systems comprises interacting, heterogeneous, autonomous components with incomplete information about their inner states, and about the surrounding environment. Many interactions are often not rigorously defined, and change dynamically. System of systems usually exhibits emergent behavior that cannot be predicted by analyzing static properties of the components, and is not always permissible. This paper suggests that the designer can improve systems behavior by substituting (part of) regular interactions with smart mediated interactions that bolster up shared situation awareness of the systems components and thus strengthens systems capability to monitor and partially control its emergent behavior. This paper discusses smart mediated interactions that focus on awareness of temporal features and on estimates of spatial location of the components. Interactions are assembled into proactive middleware that forms a backbone of system of systems.

On Models for Time-Sensitive Interactive Computing

Agent-based paradigm is increasingly applied to building computing systems where conventionally latent requirements, e.g. time-sensitivity of data and event validity, and/or truth-values of predicates, timeliness of communication, and others become essential for correct functioning of systems. In many such cases empirical demonstration of expected behaviour is not sufficient, formal verification of certain properties becomes desirable. This assumes that interaction-based models of computing are to be enhanced by introducing sufficiently sophisticated time. Such enhancement is not too simple since time has been abstracted away from models of computing during the evolution of computer science. This paper introduces some preliminary ideas for developing time-sensitive interaction-based models of computations.

AN ARCHITECTURE FOR A MULTI-AGENT SYSTEM TEST-BED

Abstract Architecture of a test-bed is suggested that has capabilities for the development of agents and multi-agent systems, and also serves for semi-automatic testing, assessment and verification of selected properties of those agents and systems. The test-bed is essentially based on models of interactive computations. New features in the test-bed are caused by an attempt explicitly to describe and formally analyse timing characteristics of agents and their interactions. Time properties of agents and their interactions have top importance in guaranteeing proper functioning of many monitoring and control applications.