Y. Xun, M. M. Kokar, and K. Baclawski. Control based sensor management for a multiple radar monitoring scenario. Information Fusion: An International Journal on Multi-Sensor, Multi-Source Information Fusion, 5,1:49–63, 2004.

Abstact: In this paper we consider the problem of monitoring illuminations of multiple emitters by one electronic receiver located on a moving platform. The emitters exhibit a quasi-periodic radiation pattern, each in a different frequency band and with a different illumination period and illumination time. The goal is to tune the receiver to the appropriate frequency band at the appropriate time so as to maximize the probability of detection of each illumination of each radar (expressed as a quality of service metric). This problem can be viewed as two subproblems: (1) generating tuning requests by particular frequency bands and (2) scheduling the receiver to satisfy the requests. In our scenario the number of requests from all the bands exceeds the physical capability of one receiver (overload) and thus selection is needed. The goal is to push the limits on the overload while still maintaining a required level of quality of service metric. This can be achieved by controlling both the generation of the tuning requests and the scheduling. According to the control theory metaphor of software development, we map this problem onto a control architecture with one system-level controller and a collection of emitter level controllers (one per emitter). We show that our control based sensor manager has significant advantages over a scheduler without feedback in terms of both the overload and the quality of service metric. We also discuss design issues of such sensor management systems.

. Y. Xun, M. M. Kokar, and K. Baclawski. Using a Task-Speci.c QoS for Controlling Sensing Requests and Scheduling. In Proceedings of the 3-rd IEEE International Symposium on Network Computing and Applications, pages 269–276, 2004.

Typically, management of networked computational and sensing nodes is based upon a quality of service metric (QoS) that is based on some generic principles, like “be fair in allocating resources” or “utilize the CPU capacity to the maximum”. The consequences of accepting such a starting point is that (1) task-specific resource requirements are not taken into consideration, and (2) computational and communication resources are saturated without paying attention to whether such a high load is necessary or not. In this paper we describe some of our efforts on how to improve the situation described above. In particular, we discuss one of the approaches that we are currently investigating that can be summarized by the following three points.
(1) We use a task-specific QoS (TS-QoS) as a variable that is controlled by our system. (2) Requests for resources are generated based upon the feedback provided by the TS-QoS, where the request generator’s parameters are adjusted using a simple PID controller. (3) A Dynamic Programming
based algorithm is used for scheduling resource. Simulations using sensor resources show some of the advantages of the proposed approach.

J. Wang, D. Brady, Baclawski K., M. Kokar, and L. Lechowicz. The Use of Ontologies for the Self-Awareness of the Communication Nodes. In Proceedings of the Software Defined Radio Technical Conference SDR’03, 2003.

This paper investigates an approach to establishing communication by explicitly maintaining self-awareness and communication of knowledge about the operation of the communication nodes. The self-awareness and communication of knowledge is based on the maintenance of an explicit, declarative knowledge base or ontology of communication. Hence, we refer to the concept as Ontology
Based Radio (OBR). The proposed approach is based on the model-driven architecture implemented by means of ontologies, DAML-based annotations and Java’s reflection capabilities. Each software module can be queried about its structure and contents using a DAML based query. It can then reply to the queries by analyzing its own structure using Java’s reflection and the system’s inference capability. In this paper we will show an example of such a functionality in which two nodes exchange information and then reason about the multipath structure. The net result is that after analyzing the multipath structure nodes can
improve the efficiency of communication.

Seth, D. and Kokar, M. M.. SSCS: A Smart Spell Checker System Implementation Using Adaptive Software Architecture. Lecture Notes in Computer Science (in print), 2001.
The subject of this paper is a Smart Spell Checker System (SSCS) that can adapt to a particular user by using the user’s feedback for adjusting its behavior. The result of the adjustment is manifested in a different ordering of the suggestions to the user on how a particular spelling mistake should be corrected. The SSCS uses the Adaptive Software Architecture (ASA). The ASA consists of a hierarchy of layers, each containing a number of components calledKnowledge Sources. The layers are connected by a software bus called Domain. External elements include User and Initiator(s). Initiators supply input data to the system. The system also includes an Evaluator that generates feedback. Each Knowledge Source is responsible for generating suggestions for correcting a specific type of error. Feedback is propagated to Knowledge
Sources after the user makes a selection of the correction. In response to feedback, Knowledge Sources adjust their algorithms. In this paper we present the results of the evaluation of the adaptability of the SSCS.

M. M. Kokar, K. M. Passino, K. Baclawski and J. E. Smith. Mapping an application to a control architecture: Specification of the problem. Lecture Notes in Computer Science, Vol. 1936, pp. 75-89, 2001.

Abstract. This paper deals with self-adapting software that is structured according to a control theory architecture. Such software contains, in addition to its main function, two components - a Controller and a Quality-of-Service module. We show an example of an application and analyze the mapping of this application onto various control theory-based architectures. The application is a radar-based target tracking system. We show how architectural constraints are propagated through the mapping. We also analyze various architectural solutions with respect to stability and time complexity.

M.M. Kokar, K. Baclawski and Y.A. Eracar. Control Theory-Based Foundations of Self-Controlling Software. IEEE Intelligent Systems, pp. 37-45, Vol. 14, No. 3, May/June 1999.

THE AUTHORS’ CONTROL THEORY-BASED PARADIGM GIVES A FRAMEWORK FOR SPECIFYING AND DESIGNING SOFTWARE THAT CONTROLS ITSELF AS IT OPERATES. BASED ON THIS PARADIGM, THEIR SELF-CONTROLLING SOFTWARE MODEL SUPPORTS THREE LEVELS OF CONTROL: FEEDBACK, ADAPTATION, AND RECONFIGURATION.

Y. A. Eracar and M. M. Kokar. An Architecture for Software that Adapts to Changes in Requirements. Journal of Systems and Software, Vol.50, 2000, pp. 209-219.

The goal of the research presented in this paper was to study a new software
paradigm adaptive software in which the structure of an adaptive program is patterned upon the structure of an adaptive controller. Towards this aim we implemented a domain specific object target recognition program RAACR that can adapt to changes in software requirements through the incorporation of feedback. RAACR is a hierarchy of domains blackboards. Each domain includes multiple knowledge sources (KSs) and a domain scheduler. In response to feedback knowledge sources change their processing parameters while domain schedulers change the scheduling policy of the knowledge sources. A generic communication mechanism is implemented on the CORBA compliant SPRING operating system. The adaptability of the program is evaluated quantitatively using a requirements volatility measure and the probability of correct recognition.

Y. S. P. Linder, M. M. Kokar and Z. Korona. Q^2 Symbolic Reasoning about Noisy Dynamic Systems. Journal of Intelligent and Robotic Systems. Pages 295-311 Vol. 25, No. 3, 1999.

Symbolic reasoning about continuous dynamic systems requires consistent qualitative abstraction functions and a consistent symbolic model. Classically, symbolic reasoning systems have utilized a box partition of the system space to achieve qualitative abstraction, but boxes can not provide a consistent abstraction. Our Q2 methodology abstracts a provably consistent symbolic representation of noise-free general dynamic systems. However the Q2 symbolic representation has not been previously evaluated for efficacy in the presence of noise. We evaluate the effects of noise on Q2 symbolic reasoning in the domain of maneuver detection. We demonstrate how the Q2 methodology derives a symbolic abstraction of a general dynamic system model used in evaluating maneuver detectors. Simulation results represented by ROC curves show that the Q2 based maneuver detector is superior to a box-based detector. While no method is consistent in the presence of noise, the Q2 methodology is superior to the classic box’s approach for deriving qualitative decisions about noisy dynamic systems.

S.O. Ibraheem, M.M. Kokar, and L.Lewis. Capturing a qualitative model of network performance and predicting behavior. Journal of Network and Systems Management, Vol.6, No.4, pp. 429-449, December 1998.

This paper describes a method for constructing behavior models of communication networks. The method utilizes archived quantitative performance data created by a network management platform to create a Quantitative/Qualitative (Q2) Dynamic System representation. The Q2 representation captures the predominant qualitative (symbolic) states of the network, qualitative input events and transitions among the states resulting from these events. This symbolic model allows the network manager to understand the current system behavior, and predict future possible behaviors. We evaluated the method on two sets of archive data. The method shows promise for use in network management, including network monitoring, fault detection, prognostication and avoidance.

M.M. Kokar. On consistent symbolic representations of general dynamic systems. IEEE Transactions on Systems, Man and Cybernetics, 25, no. 8:1231--1242, 1995.

This paper deals with the issue of consistent symbolic qualitative representation of continuous dynamic systems. Consistency means here that the results of reasoning with the qualitative representation hold in the underlying quantitative dynamic system. In the formalization proposed in this paper the quantitative structure is represented using the notion of a general dynamic system GDS. The qualitative counterpart QDS is represented by a finite-state automaton structure. The two representational substructures are related through functions, called qualitative abstractions of dynamic systems. Qualitative abstractions associate inputs, states and outputs of the QDS with partitions of appropriate GDS spaces. The paper shows how to establish such consistent partitions given a partitioning of the system's output. To represent borders of these partitions, the notion of critical hypersurfaces is introduced. One of the main ideas that provides consistency is the interpretation of qualitative input events as elements of the partition of the Cartesian product of input initial state and time sets. An example of a consistent qualitative quantitative representation of a
simple dynamic system, and of reasoning using such a representation, is provided.