Joanna Kołodziej

• PhD
• Professor at NASK National Research Institute

This book presents the main scientific results from the GUARD project. It aims at filling the current technological gap between software management paradigms and cybersecurity models, the latter still lacking orchestration and agility to effectively address the dynamicity of the former. This book provides a comprehensive review of the main concepts...

As cars and other transportation devices become increasingly interconnected, mobility takes on a new meaning, offering new opportunities. The integration of new communications technologies in modern vehicles has generated an enormous variety of data from various communications sources. Hence, there is a demand for intelligent transportation systems...

Blockchain can be successfully utilised in diverse areas, including the financial sector and the Information and Communication Technology environments, such as computational clouds (CC). While cloud computing optimises the use of resources, it does not (yet) provide an effective solution for the secure hosting scheduling and execution of large comp...

Security is one of the most important criteria in the management of cloud resources. In Mobile Cloud Computing (MCC), secure allocation of tasks remains challenging due to the limited storage, battery life and computational power of mobile devices connected to the core cloud cluster infrastructure. Secure wireless communication channels and protoco...

In this article, we present an original agent‐based adaptive task scheduling system which optimizes the performance of services in the mobile cloud computing environment using machine learning mechanisms and context information. The system learns how to allocate resources appropriately: how to schedule services/tasks optimally between the mobile de...

Stimulating innovation is one of the most critical challenges of the broader economy. In recent years, events that activate people from various fields to develop innovative solutions or to familiarize themselves with the latest technologies have been very popular. We can also observe that there is a growing demand for geospatial data and tools, whi...

Looking at the rapid development of computer networks,it can be said that the transmission quality assurance isvery important issue. In the past there were attempts toimplement Quality of Service (QoS) techniques when usingvarious network technologies. However QoS parameters arenot always assured. This paper presents a novel concept oftransmission...

Although a lot of work has been done in the domain, tasks scheduling and resource allocation in cloud computing remain the challenging problems for both industry and academia. Security in scheduling in highly distributed computing environments is one of the most important criteria in the era of personalization of the cloud services. Blockchain beca...

This paper presents a generic model of the energy aware, secure sensing and computing system composed of clusters comprised of static and mobile wireless sensors. The architecture of the modelled system is based on the paradigms of edge and fog computing. The data collected by all sensing devices (edge devices) located in each cluster is preprocess...

While the modern parallel computing systems offer high performance, utilizing these powerful computing resources to the highest possible extent demands advanced knowledge of various hardware architectures and parallel programming models. Furthermore, optimized software execution on parallel computing systems demands consideration of many parameters...

Many complex problems, such as natural language processing or visual object detection, are solved using deep learning. However, efficient training of complex deep convolutional neural networks for large data sets is computationally demanding and requires parallel computing resources. In this paper, we present two parameterized performance models fo...

Determining the optimal location of control cabinet components requires the exploration of a large configuration space. For real-world control cabinets it is impractical to evaluate all possible cabinet configurations. Therefore, we need to apply methods for intelligent exploration of cabinet configuration space that enable to find a near-optimal c...

Body Area Networks (BANs) connect together nodes attached to a human body and transfer the data to an external infrastructure. The wireless communication channel and a variety of miniature sensor devices have lead to many useful applications of BANs, such as healthcare monitoring, military and emergency coordination, rescue services, sports, and en...

Energy-awareness remains one of the main concerns for today's cloud computing (CC) operators. The optimisation of energy consumption in both cloud computational clusters and computing servers is usually related to scheduling problems. The definition of an optimal scheduling policy which does not negatively impact to system performance and task comp...

The main research challenge in the ICT support of the financial markets is the development of a next generation financial technology for a secure use of electronic currencies and a secure network technology for system user communication, as well as data processing and storage without the involvement of third parties. To deal with the security aspec...

Optimized software execution on parallel computing systems demands consideration of many parameters at run-time. Determining the optimal set of parameters in a given execution context is a complex task, and therefore to address this issue researchers have proposed different approaches that use heuristic search or machine learning. In this paper, we...

Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of perfor...

Achieving efficiency both in terms of resource utilisation and energy consumption is a complex challenge, especially in large-scale wide-purpose data centers that serve cloud-computing services. Simulation presents an appropriate solution for the development and testing of strategies that aim to improve efficiency problems before their applications...

Stackelberg games may reveal to be extremely useful in supporting decisions in attack-defense scenarios. We call such games Security Stackelberg games. They are characterized by two kinds of players: the defender, who defines his strategy in advance, and the attacker, who follows the defender's decisions. Security Stackelberg games may be used to m...

In this chapter, the k-anonymity algorithm is used for anonymization of sensitive data sending via network and analyzed by experts. Anonymization is a technique used to generalize sensitive data to block the possibility of assigning them to specific individuals or entities. In our proposed model, we have developed a layer that enables virtualizatio...

While modern parallel computing systems offer high performance, utilizing these powerful computing resources to the highest possible extent demands advanced knowledge of various hardware architectures and parallel programming models. Furthermore, optimized software execution on parallel computing systems demands consideration of many parameters at...

Modern computer based systems are characterized by several complexity dimensions: a non-exhaustive list includes scale, architecture, distribution, variability, flexibility, dynamics, workloads, time constraints, dependability, availability, security, performances. The design, implementation, operation, maintenance and evolution of such systems req...

Many modern parallel computing systems are heterogeneous at their node level. Such nodes may comprise general purpose CPUs and accelerators (such as, GPU, or Intel Xeon Phi) that provide high performance with suitable energy-consumption characteristics. However, exploiting the available performance of heterogeneous architectures may be challenging....

Cloud Computing is one of the most intensively developed solutions for large-scale distributed processing. Effective use of such environments, management of their high complexity and ensuring appropriate levels of Quality of Service (QoS) require advanced monitoring systems. Such monitoring systems have to support the scalability, adaptability and...

Energy consumption is one of the most important problems in the era of Computational Clouds (CC). CC infrastructures must be elastic and scalable for being accessible by huge population of users in different geographical locations. It means also that CC energy utilization systems must be modern and dynamic in order to reduce the cost of using the c...

Many modern parallel computing systems are heterogeneous at their node level. Such nodes may comprise general purpose CPUs and accelerators (such as, GPU, or Intel Xeon Phi) that provide high performance with suitable energy-consumption characteristics. However, exploiting the available performance of heterogeneous architectures may be challenging....

Modelling and simulation are widely considered essential for the analysis of complex systems and natural phenomena in science and engineering. They often require a significant amount of computational resources with large data sets, typically scattered across different geographical locations with dissimilar computational infrastructures. Moreover, r...

This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage profiles are presented together with energy efficiency measuring methods. Modeling of computing dynamics is discussed from the viewpoint of system identification theory, indicating basic experim...

With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, sto...

Network optimization concerned with operational traffic management in existing data networks is typically oriented towards either maximizing throughput in congested networks while providing for adequate transmission quality, or towards balancing the traffic so as to maintain possibly large free capacity for carrying additional (new) traffic. Nowada...

In this chapter, we describe an optimized approach for DNA sequence analysis on a heterogeneous platform that is accelerated with the Intel Xeon Phi. Such platforms commonly comprise one or two general purpose CPUs and one (or more) Xeon Phi coprocessors. Our parallel DNA sequence analysis algorithm is based on Finite Automata and finds patterns in...

Stackelberg games are non-symmetric games where one player or specified group of players have the privilege position and make decision before the other players. Such games are used in telecommunication and computational systems for supporting administrative decisions. Recently Stackleberg games became useful also in the systems where security issue...

Task scheduling in large-scale distributed High Performance Computing (HPC) systems environments remains challenging research and engineering problem. There is a need of development of novel advanced scheduling techniques in order to optimise the resource utilisation. In this work, we develop the Agent Supported Non-Deterministic Meta Scheduler for...

E-Learning has revolutionized the delivery of learning through the support of rapid advances in Internet technology. Compared with face-to-face traditional classroom education, e-learning lacks interpersonal and emotional interaction between students and teachers. In other words, although a vital factor in learning that influences a human’s ability...

In the last years there has been considerable interest in using distributed systems, especially Cloud Systems, in any domains. Resource management contributes to ensure quality of services for any type of application, especially when a system involves elements of heterogeneity characterized by a variety of resources that may or may not be coupled w...

This book constitutes a flagship driver towards presenting and supporting advance research in the area of Big Data platforms and applications. Extracting valuable information from raw data is especially difficult considering the velocity of growing data from year to year and the fact that 80% of data is unstructured. In addition, data sources are h...

When there is a mismatch between the cardinality of a periodic task set and the priority levels supported by the underlying hardware systems, multiple tasks are grouped into one class so as to maintain a specific level of confidence in their accuracy. However, such a transformation is achieved at the expense of the loss of schedulability of the ori...

Monitoring of the system performance in highly distributed computing environments is a wide research area. In cloud and grid computing, it is usually restricted to the utilization and reliability of the resources. However, in today’s Computational Grids (CGs) and Clouds (CCs), the end users may define the special personal requirements and preferenc...

Data-aware scheduling in large-scale heterogeneous computing systems remains a challenging research issue, especially in the era of Big Data. Design of all data-related components of the popular distributed environments, such as Data Clouds (DCs), Data Grids (DGs) and Data Centers supports the processing, analysis and monitoring of the big data gen...

Cloud computing has transformed people's perception of how Internet-based applications can be deployed in datacenters and offered to users in a pay-as-you-go model. Despite the growing adoption of cloud datacenters, challenges related to big data application management still exist. One important research challenge is selecting configurations of res...

In this survey, we review different text mining techniques to discover various textual patterns from the social networking sites. Social network applications create opportunities to establish interaction among people leading to mutual learning and sharing of valuable knowledge, such as chat, comments, and discussion boards. Data in social networkin...

Intelligent computing in large-scale systems provides systematic methodologies and tools for building complex inferential systems, which are able to adapt, mine data sets, evolve, and act in a nimble manner within major distributed environments with diverse architectures featuring multiple cores, accelerators, and high-speed networks. We believe th...

Today, almost everyone is connected to the Internet and uses different Cloud solutions to store, deliver and process data. Cloud computing assembles large networks of virtualized services such as hardware and software resources. The new era in which ICT penetrated almost all domains (healthcare, aged-care, social assistance, surveillance, education...

Smart evacuation systems must extract meaningful information from multiple sources in real time, while avoiding unnecessary data transmission or storage. Cloud computing is a natural fit for deploying such systems; however, transformational techniques for managing the resulting big data are still needed.

Cloud computing is the latest computing paradigm that delivers hardware and software resources as virtualization enabled services. Recently, cloud service selection has emerged as an important research problem due to large number of cloud providers and their diverse service configurations, multiple selection criteria, and customer's fuzzy perceptio...

MapReduce is regarded as an adequate programming model for large-scale data-intensive applications. The Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks on a cluster system. G-Hadoop is an extension of the Hadoop MapReduce framework with the functionality of allowing the MapReduce tasks to run on multiple clus...

This special issue renders ten original technical contributions which represent the latest trends in the emerging inter-disciplinary area of data-intensive modelling and simulation. Ranging from performance-oriented and energy-aware infrastructure support through parallel programming frameworks and scheduling heuristics to high-end applicative envi...

In a cloud computing paradigm, energy efficient allocation of different vir-tualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery net-works, MapReduce, web applications, and the like) workloads having contentious 123 A. Hameed et al....

Task scheduling and resource allocations are the key issues for computational grids. Distributed resources usually work at different autonomous domains with their own access and security policies that impact successful job executions across the domain boundaries. In this paper, we propose an Artificial Neural Network (ANN) approach for supporting t...

Multi-policy resource management have been considered as an efficient methodology for delivering ready-to-use media-optimized applications in Software-Defined Networks (SDNs). Prioritized flow scheduling ensures high-speed communication in SDNs under large-scale distribution, heterogeneity of network resources, and exponential distribution of the f...

The big data era poses a critically difficult challenge and striking development opportunities to high performance computing (HPC). The major problem is an efficient transformation of the massive data of various types into valuable information and meaningful knowledge. Computationally-effective HPC is required in a fast-increasing number of data-in...

Devices that form a wireless sensor network (WSN) system are usually remotely deployed in large numbers in a sensing field. WSNs have enabled numerous applications, in which location awareness is usually required. Therefore, numerous localization systems are provided to assign geographic coordinates to each node in a network. In this paper, we desc...

In this paper we summarise the results of our research concerned with the development, implementation and evaluation of a software framework for wireless sensor networks (WSNs) localisation - high performance localisation system (HPLS). The system can be used to calculate positions of sensing devices (network nodes) in the deployment area, and to t...

Profiting from the development of space remote sensing technology, the amount of remote sensing image data obtained by satellite is increasing dramatically; however, how to deal with these data quickly and efficiently has turned out to be a great computational challenge. With the rapid development of general-purpose GPU computing technology, resear...

Virtualization is one of the key technologies that enable Cloud Computing, a novel computing paradigm aiming at provisioning on-demand computing capacities as services. With the special features of self-service and pay-as-you-use, Cloud Computing is attracting not only personal users but also small and middle enterprises. By running applications on...

The social computing, such as social networking services (SNSs) and social Networking Platforms (SNPs) provide a coherent medium through which people can be interactive and socialize. The SNP is a Web-based social space, specifically designed for end user-driven applications that facilitate communication, collaboration and sharing of the knowledge...

Data-aware scheduling in today's large-scale computing systems has become a major complex research issue. This problem becomes even more challenging when data is stored and accessed from many highly distributed servers and energy-efficiency is treated as a main scheduling objective. In this paper we approach the independent batch scheduling in grid...

The data sets produced in our daily life is getting larger and larger. How to manage and analyze such big data is currently a grand challenge for scientists in various research fields. MapReduce is regarded as an appropriate programming model for processing such big data. However, the users or developers still need to efficiently program appropriat...

This paper addresses issues concerned with design and managing of mobile ad hoc networks. We focus on self-organizing, cooperative and coherent networks that enable a continuous communication with a central decision unit and adopt to changes in an unknown environment to achieve a given goal. In general, it is very difficult to model a motion of nod...

With the mushroom growth of state-of-the-art digital image and video manipulations tools, establishing the authenticity of multimedia content has become a challenging issue. Digital image forensics is an increasingly growing research field that symbolises a never ending struggle against forgery and tampering. This survey attempts to cover the blind...

A key agreement scheme is an important technique to establish a common secret over an insecure communication environment such as the Internet. In this paper, we elaborate on the merits of self-certified public key systems and bilinear pairing cryptosystems ...

This chapter summarizes the recent work of the authors on the game-theoretic models of the grid users behavior in security aware scheduling. The scheduling process may be realized in two alternate scenarios, namely risky and secure modes. The chapter focuses on the fundamental type of the scheduling problem in computational grids, namely independen...

Network optimization concerned with operational traffic management in existing data networks is typically oriented towards either maximizing throughput in congested networks while providing for adequate transmission quality, or towards balancing the traffic so as to maintain possibly large free capacity for carrying additional (new) traffic. Nowada...

The last decade has witnessed an explosion of the interest in technologies of large simulation with the rapid growth of both the complexity and the scale of problem domains. Modelling & simulation of crowd is a typical paradigm, especially when dealing with large crowd. On top of a hierarchical Grid simulation infrastructure, a simulation of evacua...

Wireless sensor networks (WSNs) are emerging as useful technology for information extraction from the surrounding environment by using numerous small-sized sensor nodes that are mostly deployed in sensitive, unattended, and (sometimes) hostile territories. Traditional cryptographic approaches are widely used to provide security in WSN. However, bec...

Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware scheduling has become a major research issue. In this work we present two implementations of classical genetic-based data-aware schedulers...

Recently, the computational requirements for large-scale data-intensive analysis of scientific data have grown significantly. In High Energy Physics (HEP) for example, the Large Hadron Collider (LHC) produced 13 petabytes of data in 2010. This huge amount of data are processed on more than 140 computing centers distributed across 34 countries. The...

Recently, the computational requirements for large-scale data-intensive analysis of scientific data have grown significantly. In High Energy Physics (HEP) for example, the Large Hadron Collider (LHC) produced 13 petabytes of data in 2010. This huge amount of data are processed on more than 140 computing centers distributed across 34 countries. The...

Data-aware scheduling in today’s large-scale heterogeneous environments has become a major research issue. Data Grids (DGs) and Data Centers arise quite naturally to support needs of scientific communities to share, access, process, and manage large data collections geographically distributed. Data scheduling, although similar in nature with grid s...