Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

반도체 공정 overview

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Home PURPOSE OF THE CENTER: To develop the center to address state-of-the-art research, create innovating educational programs, and support technology transfers using commercially viable results to assist the Army Research Laboratory to develop the next generation Future Combat System in the telecommunications sector that assures prevention of perceived threats, and Non Line of Sight/Beyond Line of Sight lethal support.

How to… home page

Radio Frequency Identification (RFID) and sensor networks are both wireless technologies that provide limitless future potentials. While the industry has witnessed rapid growth in developing and applying RFID technology, and the network research community has devoted tremendous efforts in sensor networks, these two communities would benefit greatly by learning from each other. In pursuing this effect, a project utilizing and integrating both technologies is described. The goal is to build an in-home elder healthcare system that monitors patients' medication in take. This would help addressing the challenge of a growing aging population.

/pdf/a-prototype-on-rfid-and-sensor-networks-for-elder-healthcare-3bih8renwn.pdf

A prototype on RFID and sensor networks for elder healthcare: progress report

Sensor networks have many potential applications in biology, physics, medicine, and the military. One major challenge in sensor networks is to maximize network life under the constraint of limited power supply. The paper addresses energy-efficiency in the context of routing and data gathering. A new protocol is proposed: Hybrid Indirect Transmission (HIT). HIT is based on a hybrid architecture that consists of one or more clusters, each of which is based on multiple, multi-hop indirect transmissions. In order to minimize both energy consumption and network delay, parallel transmissions are used both among multiple clusters and within a cluster. This is made possible by having each sensor independently compute a medium access controlling TDMA schedule. The computation within each sensor is intelligent yet simple. Formal analysis shows that it requires O(n) space and O(n x logn) time complexities, and O(1) setup messages prior to the computation, where n is the total number of sensors. HIT does not require sensor nodes with CDMA capability, or the remote base station to compute a data gathering schedule. Performance is evaluated by simulating and comparing HIT with three other existing protocols, including Low Energy Adaptive Clustering Hierarchy (LEACH), Power Efficient Gathering for Sensor Information System (PEGASIS), and Direct Transmission. Results have shown that HIT greatly reduces both energy consumption and network delay; it also maintains longer network life compared to these three existing protocols. Security issues and a potential application of HIT in biomedical sensing technology are also rigorously discussed. This work is significant to the advancement of energy-efficient micro sensor networks; the proposed protocol is promising and would contribute to the use of wireless micro sensor networks in future biomedical sensing technologies.

/pdf/design-and-analysis-of-hybrid-indirect-transmissions-hit-for-4wlhagt20m.pdf

Design and analysis of Hybrid Indirect Transmissions (HIT) for data gathering in wireless micro sensor networks

Fog computing, similar to edge computing, has been proposed as a model to introduce a virtualized layer between the end users and the back-end cloud data centers. Fog computing has attracted much attention due to the recent rapid deployment of smart devices and Internet-of-Things (IoT) systems, which often requires real-time, stringent-delay services. The fog layer placed between client and cloud layers aims to reduce the delay in terms of transmission and processing times, as well as the overall cost. To support the increasing number of IoT, smart devices, and to improve performance and reduce cost, this paper proposes a task scheduling algorithm in the fog layer based on priority levels. The proposed architecture, queueing and priority models, priority assignment module, and the priority-based task scheduling algorithms are carefully described. Performance evaluation shows that, comparing with existing task scheduling algorithms, the proposed algorithm reduces the overall response time and notably decreases the total cost. We believe that this work is significant to the emerging fog computing technology, and the priority-based algorithm is useful to a wide range of application domains.

/pdf/prioritized-task-scheduling-in-fog-computing-4q6m8yty57.pdf

Prioritized task scheduling in fog computing

This paper investigates the effectiveness of data gathering protocols for in-body biomedical sensor networks. We studied the performance of representatives from each of three major protocol categories: (1) low energy adaptive clustering hierarchy (LEACH), a cluster-based protocol, (2) power efficient gathering for sensory information systems (PEGASIS), a chain-based protocol, and (3) hybrid indirect transmissions (HIT), a hybrid of chains and clusters. First, the ability of each protocol to perform in-network source separation was judged. We consider a human-machine interaction application in which implanted bio-sensors communicate motor unit actions of human muscles to a remote computer. Motor unit action potentials (MUAPs) were modeled, and source separation and recovery at each sensor was simulated. We compare the performance of HIT and LEACH in terms of signal distortion ratios and the energy costs of fusion and communication. Second, we report on the efficiency of each protocol for in-body data collection, using Gupta et al's propagation loss model for biomedical applications (PMBA) - an accurate model of power loss due to signal absorption by the human body. We investigate the effectiveness of HIT, LEACH, and PEGASIS under this model, and compare their performance in terms of energy efficiency and network lifetime

On data gathering protocols for in-body biomedical sensor networks

Cloud data centers consume an enormous amount of energy. Virtual Machine (VM) migration technology can be applied to reduce energy consumption by consolidating VMs onto the minimal number of servers and turn idle servers into power-saving modes. While most existing energy models consider mainly computing energy, an enhanced energy consumption model is formulated, which includes energy consumption for computation, for servers to switch from standby to active modes, and for communication during VM migrations. Next, two new dynamic VM migration algorithms are proposed. They apply a local regression method to predict potentially over-utilized servers, and the 0-1 knapsack dynamic programming to find the best-fit combination of VMs for migration. The time complexity of these algorithms is analyzed, which indicates that they are highly scalable. Performance is evaluated and compared with existing algorithms. The two new heuristics have significantly reduced the number of VM migration, the number of rebooted servers, and energy consumption. Furthermore, one of them has achieved the least overall SLA violations. We believe that the new energy formulation and the two new heuristics contribute significantly towards achieving green cloud computing.

Melody Moh

Papers

A prototype on RFID and sensor networks for elder healthcare: progress report

Design and analysis of Hybrid Indirect Transmissions (HIT) for data gathering in wireless micro sensor networks

Prioritized task scheduling in fog computing

On data gathering protocols for in-body biomedical sensor networks

Dynamic Virtual Machine migration algorithms using enhanced energy consumption model for green cloud data centers