A Dynamic Data Driven Application System for Vehicle Tracking

AbstractTracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement and defense. A dynamic data driven application system (DDDAS) is described to track a vehicle's movements by repeatedly identifying the vehicle under investigation from live image and video data, predicting probable future locations, and repositioning sensors or retargeting requests for information in order to reacquire the vehicle. An overview of the envisioned system is described that includes image processing algorithms to detect and recapture the vehicle from live image data, a computational framework to predict probable vehicle locations at future points in time, and a power aware data distribution management system to disseminate data and requests for information over ad hoc wireless communication networks. A testbed under development in the midtown area of Atlanta, Georgia in the United States is briefly described

Design and investigation of scalable multicast recursive protocols for wired and wireless ad hoc networks

The ever-increasing demand on content distribution and media streaming over the Internet has created the need for efficient methods of delivering information. One of the most promising approaches is based on multicasting. However, multicast solutions have to cope with several constraints as well as being able to perform in different environments such as wired, wireless, and ad hoc environments. Additionally, the scale and size of the Internet introduces another dimension of difficulty. Providing scalable multicast for mobile hosts in wireless environment and in mobile ad hoc networks (MANETs) is a challenging problem. In the past few years, several protocols have been proposed to efficient multicast solutions over the Internet, but these protocols did not give efficient solution for the scalability issue. In this thesis, scalable multicast protocols for wired, wireless and wireless ad hoc networks are proposed and evaluated. These protocols share the idea of building up a multicast tree gradually and recursively as join/leave of the multicast group members using a dynamic branching node-based tree (DBT) concept. The DBT uses a pair of branching node messages (BNMs). These messages traverse between a set of dynamically assigned branching node routers (BNRs) to build the multicast tree. In the proposed protocols only the branching node routers (BNRs) carry the state information about their next BNRs rather than the multicast group members, which gives a fixed size of control packet header size as the multicast group size increases, i.e. a good solution to the problem of scalability. Also the process of join/leave of multicast group members is carried out locally which gives low join/leave latency. The proposed protocols include: Scalable Recursive Multicast protocol (SReM) which is proposed using the DBT concepts mentioned above, Mobile Scalable Recursive Multicast protocol (MoSReM) which is an extension for SReM by taking into consideration the mobility feature in the end hosts and performing an efficient roaming process, and finally, a Scalable Ad hoc Recursive Multicast protocol (SARM) to achieve the mobility feature for all nodes and performing an efficient solution for link recovery because of node movement. By cost analysis and an extensive simulation, the proposed protocols show many positive features like fixed size control messages, being scalable, low end to end delay, high packet rate delivery and low normalized routing overhead. The thesis concludes by discussing the contributions of the proposed protocols on scalable multicast in the Internet society

Hybrid Simulation and Test of Vessel Traffic Systems on the Cloud

This paper presents a cloud-based hybrid simulation platform to test large-scale distributed System-of-Systems (SoS) for the management and control of maritime traffic, the so-called Vessel Traffic Systems (VTS). A VTS consists of multiple, heterogeneous, distributed and interoperating systems, including radar, automatic identification systems, direction finders, electro-optical sensors, gateways to external VTSs, information systems; identifying, representing and analyzing interactions is a challenge to the evaluation of the real risks for safety and security of the marine environment. The need for reproducing in fabric the system behaviors that could occur in situ demands for the ability of integrating emulated and simulated environments to cope with the different testability requirements of involved systems and to keep testing cost sustainable. The platform exploits hybrid simulation and virtualization technologies, and it is deployable on a private cloud, reducing the cost of setting up realistic and effective testing scenarios

Modeling the Internet of Things: a simulation perspective

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017

A policy compliance detection architecture for data exchange infrastructures

Data sharing and federation can significantly increase efficiency and lower the cost of digital collaborations. It is important to convince the data owners that their outsourced data will be used in a secure and controlled manner. To achieve this goal, constructing a policy governing concrete data usage rule among all parties is essential. More importantly, we need to establish digital infrastructures that can enforce the policy. In this thesis, we investigate how to select optimal application-tailored infrastructures and enhance policy compliance capabilities. First, we introduce a component linking the policy to the infrastructure patterns. The mechanism selects digital infrastructure patterns that satisfy the collaboration request to a maximal degree by modelling and closeness identification. Second, we present a threat-analysis driven risk assessment framework. The framework quantitatively assesses the remaining risk of an application delegated to digital infrastructure. The optimal digital infrastructure for a specific data federation application is the one which can support the requested collaboration model and provides the best security guarantee. Finally, we present a distributed architecture that detects policy compliance when an algorithm executes on the data. A profile and an IDS model are built for each containerized algorithm and are distributed to endpoint execution platforms via a secure channel. Syscall traces are monitored and analysed in endpoint points platforms. The machine learning based IDS is retrained periodically to increase generalization. A sanitization algorithm is implemented to filter out malicious samples to further defend the architecture against adversarial machine learning attacks

An introduction of small-scale intelligent manufacturing system

Embargoed OA, manuscript version after 24 months from publishing date. Link to publishers version: http://doi.org/10.1109/SIMS.2016.7802896Manufacturing companies in Northern Peripheral and Arctic region are predominately small and medium-sized and face considerable challenges like geographical isolation and a lack of benefits offered by industrial clusters. For the ultimate goal of enhancing their competitiveness in a global market, it is imperative for companies to innovate or adopt innovations in order to quickly response to changes in market, meet customer demands, reduce time-to-market and lower cost. A novel concept for small-scale intelligent manufacturing systems (SIMS) is introduced, in which diverse methods and innovative technologies can be applied and integrated. This paper gives an introduction of SIMS, defines its design objectives, and summarizes major relevant tools, techniques and paradigms for the development of SIMS, to generate a facilitative environment for small and medium-scale manufacturing enterprises to embrace new and innovative technologies

Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487