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target to sensor allocation: A hierarchical dynamic Distributed Constraint Optimization approach

COMPUTER COMMUNICATIONS 2013年第9期36卷 1024-1038页

作者： Semnani, Samaneh Hosseini Basir, Otman A. Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Distributed target allocation and tracking is an important research problem. This problem is complex but has many applications in various domains, including, pervasive computing, surveillance and military systems. In this paper we propose a technique to solve the target to sensor allocation problem by modeling the problem as a hierarchical Distributed Constraint Optimization Problem (HDCOP). Distributed Constrain Optimization Problems (DCOPs) tend to be computationally expensive and often intractable, particularly in large problem spaces such as Wireless sensor Networks (WSNs). To address this challenge we propose changing the sensor to target allocation as a hierarchical set of smaller DCOPs with a shared system of constraints. Thus, we avoid significant computational and communication costs. Furthermore, in contrast to other DCOP modeling methods, a non-binary variable modeling is employed to reduce the number of intra-agent constraints. To evaluate the performance of the proposed approach, we use the surveillance system of the Regional Waterloo Airport as a test case. Two DCOP solution algorithms are considered, namely, the Distributed Breakout Algorithm (DBA) and the Asynchronous Distributed Optimization (ADOPT). We evaluate the computational and communication costs of these two algorithms for solving the target to sensor allocation problem using the proposed hierarchical formulation. We compare the performance of these algorithms with respect to the incurred computational and communication costs. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Constraint Optimization Problem Multi-agent systems sensor networks target to sensor allocation

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Multi-target Engagement in Complex Mobile Surveillance sensor Networks

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UNMANNED SYSTEMS 2017年第1期5卷 31-43页

作者： Semnani, Samaneh Hosseini Basir, Otman A. Univ Waterloo Elect & Comp Engn Dept Waterloo ON Canada

Efficient use of the network's resources to collect information about objects (events) in a given volume of interest (VOI) is a key challenge in large-scale sensor networks. Multi-sensor multi-target tracking in surveillance applications is an example where the network's success in tracking targets, efficiently and effectively, hinges significantly on the network's ability to allocate the right set of sensors to the right set of targets so as to achieve optimal performance which minimizes the number of uncovered targets. This task can be even more complicated when both the sensors and the targets are mobile. To ensure timely tracking of mobile targets, the surveillance sensor network needs to perform the following tasks in real-time: (i) target-to-sensor allocation;(ii) sensor mobility control and coordination. The computational complexity of these two tasks presents a challenge, particularly in large scale dynamic network applications. This paper proposes a formulation based on the Semi-flocking algorithm and the distributed constraint optimization problem (DCOP). The semi-flocking algorithm performs multi-target motion control and coordination, a DCOP modeling algorithm performs the target engagement task. As will be demonstrated experimentally in the paper, this algorithmic combination provides an effective approach to the multisensor/multi-target engagement problem, delivering optimal target coverage as well as maximum sensors utilization.

关键词： Surveillance systems biologically inspired computing constraint optimization problem semi-flocking algorithm hierarchical DCOP modeling sensor coordination mobility control target to sensor allocation sensor networks

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