Design Challenges of Trustworthy Artificial Intelligence Learning Systems

in Intelligent Information and Database Systems - 12th Asian Conference ACIIDS 2020, Phuket, Thailand, March 23-26, 2020, Companion Proceedings (2020)

Autonomous Flight of Unmanned Aerial Vehicles Using Evolutionary Algorithms

in High Performance Computing (2020)

This article explores the application of evolutionary algorithms and agent-oriented programming to solve the problem of searching and monitoring objectives through a fleet of unmanned aerial vehicles. The ... [more ▼]

This article explores the application of evolutionary algorithms and agent-oriented programming to solve the problem of searching and monitoring objectives through a fleet of unmanned aerial vehicles. The subproblem of static off-line planning is studied to find initial flight plans for each vehicle in the fleet, using evolutionary algorithms to achieve compromise values between the size of the explored area, the proximity of the vehicles, and the monitoring of points of interest defined in the area. The results obtained in the experimental analysis on representative instances of the surveillance problem indicate that the proposed techniques are capable of computing effective flight plans. [less ▲]

Internet of Unmanned Aerial Vehicles—A Multilayer Low-Altitude Airspace Model for Distributed UAV Traffic Management

in Sensors (2019), 19(21), 22

The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution ... [more ▼]

The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring new means of delivering IoT services through a wide range of applications. Owning to their potential, UAVs are expected to soon dominate the low-altitude airspace over populated cities. This introduces new research challenges such as the safe management of UAVs operation under high traffic demands. This paper proposes a novel way of structuring the uncontrolled, low-altitude airspace, with the aim of addressing the complex problem of UAV traffic management at an abstract level. The work, hence, introduces a model of the airspace as a weighted multilayer network of nodes and airways and presents a set of experimental simulation results using three UAV traffic management heuristics. [less ▲]

Trustworthiness in IoT - A Standards Gap Analysis on Security, Data Protection and Privacy

in Samir Labib, Nader; Brust, Matthias R.; Danoy, Grégoire (Eds.) et al Trustworthiness in IoT - A Standards Gap Analysis on Security, Data Protection and Privacy (2019, October)

With the emergence of new digital trends like Internet of Things (IoT), more industry actors and technical committees pursue research in utilising such technologies as they promise a better and optimised ... [more ▼]

With the emergence of new digital trends like Internet of Things (IoT), more industry actors and technical committees pursue research in utilising such technologies as they promise a better and optimised management, improved energy efficiency and a better quality living through a wide array of value-added services. However, as sensing, actuation, communication and control become increasingly more sophisticated, such promising data-driven systems generate, process, and exchange larger amounts of security-critical and privacy-sensitive data, which makes them attractive targets of attacks. In turn this affirms the importance of trustworthiness in IoT and emphasises the need of a solid technical and regulatory foundation. The goal of this paper is to first introduce the concept of trustworthiness in IoT, its main pillars namely, security, privacy and data protection, and then analyse the state-of-the-art in research and standardisation for each of these subareas. Throughout the paper, we develop and refer to Unmanned Aerial Vehicles (UAVs) as a promising value-added service example of mobile IoT devices. The paper then presents a thorough gap analysis and concludes with recommendations for future work. [less ▲]

Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities

in IEEE Symposium on Computers and Communications (ISCC), Barcelona, Spain, 2019 (2019, July)

Urban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven ... [more ▼]

Urban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven approaches in urban computing have emerged for researchers and companies. They aim to address historical urbanization issues by exploiting sensing data gathered by mobile devices under the so-called mobile crowdsensing (MCS) paradigm. This work shows how to exploit sensing data to improve traditionally experience-based approaches for urban decisions. In particular, we apply widely known Machine Learning (ML) techniques to achieve highly accurate results in predicting categories of local businesses (LBs) (e.g., bars, restaurants), and their attractiveness in terms of classes of temporal demands (e.g., nightlife, business hours). The performance evaluation is conducted in Luxembourg city and the city of Munich with publicly available crowdsensed datasets. The results highlight that our approach does not only achieve high accuracy, but it also unveils important hidden features of the interaction of citizens and LBs. [less ▲]

A GP Hyper-Heuristic Approach for Generating TSP Heuristics

in 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019) (2019, May 20)

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

in IEEE Communications Surveys and Tutorials (2019), 21(3, thirdquarter 2019), 2419-2465

Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices ... [more ▼]

Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies, and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas. [less ▲]

Transforming Collaboration Data into Network Layers for Enhanced Analytics

Scientific Conference (2019, February 25)

We consider the problem of automatically generating networks from data of collaborating researchers. The objective is to apply network analysis on the resulting network layers to reveal supplemental ... [more ▼]

We consider the problem of automatically generating networks from data of collaborating researchers. The objective is to apply network analysis on the resulting network layers to reveal supplemental patterns and insights of the research collaborations. In this paper, we describe our data-to-networks method, which automatically generates a set of logical network layers from the relational input data using a linkage threshold. We, then, use a series of network metrics to analyze the impact of the linkage threshold on the individual network layers. Moreover, results from the network analysis also provide beneficial information to improve the network visualization. We demonstrate the feasibility and impact of our approach using real-world collaboration data. We discuss how the produced network layers can reveal insights and patterns to direct the data analytics more intelligently. [less ▲]

Security, reliability and regulation compliance in Ultrascale Computing System

in Zomaya, A. Y.; Carretero, J.; Jeannot, E. (Eds.) Ultrascale Computing Systems (2019)

Ultrascale Computing Systems (UCSs) are envisioned as large-scale complex systems joining parallel and distributed computing systems that will be two to three orders of magnitude larger than today’s ... [more ▼]

Ultrascale Computing Systems (UCSs) are envisioned as large-scale complex systems joining parallel and distributed computing systems that will be two to three orders of magnitude larger than today’s systems (considering the number of Central Process Unit (CPU) cores). It is very challenging to find sustainable solutions for UCSs due to their scale and a wide range of possible applications and involved technologies. For example, we need to deal with heterogeneity and cross fertilization among HPC, large-scale distributed systems, and big data management. One of the challenges regarding sustainable UCSs is resilience. Another one, which attracted less interest in the literature but becomes more and more crucial with the expected convergence with the Cloud computing paradigm, is the notion of regulation in such system to assess the Quality of Service (QoS) and Service Level Agreement (SLA) proposed for the use of these platforms. This chapter covers both aspects through the reproduction of two articles: [1] and [2]. [less ▲]

Multi-Objective Scientific-Workflow Scheduling With Data Movement Awareness in Cloud.

in IEEE Access (2019), 7

Due to serving several purposes simultaneously, running scientific workflows on dynamic environments such as cloud computing, has become multi-objective scheduling. Among these purposes, Cost and Makespan ... [more ▼]

Due to serving several purposes simultaneously, running scientific workflows on dynamic environments such as cloud computing, has become multi-objective scheduling. Among these purposes, Cost and Makespan are probably the most two primitive objectives. Another critical factor in a large-scale scientific workflow is tremendous amount of data during execution. Therefore, this work also includes Data Movement as an additional objective as it has a major impact on network utilization and energy consumption in network equipment in cloud data center. In considering these three objectives, this work proposes a framework for scheduling solutions which combines a new nodes clustering technique in Directed Acyclic Graph (DAG) model known as Multilevel Dependent Node Clustering (MDNC) and the multiobjective optimization, Extreme Nondominated Sorting Genetic Algorithm-III (E-NSGA-III). E-NSGAIII is the recent extension of Nondominated Sorting Genetic Algorithm (NSGA-III). Five well-known scientific workflows, CyberShake, Epigenomics, LIGO, Montage, and SIPHT are selected as testbeds, while the commonly known Hypervolume is chosen as the performance metric. In this work, MDNC is also experimented with both NSGA-III. Comparison among three approaches, E-NAGA-III alone, E-NAGA-III with Peer-to-Peer clustering and E-NAGA-III with MDNC are carried out. The superiority of the proposed framework among them and its limitation are discussed. [less ▲]