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Implementation technology software-defined networking in Wireless Sensor Networks

Implementation technology software-defined networking in Wir...

引用

IEEE international Workshop on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications

作者： Marek Boguslav Aleksander Lesia Dubchak Vitalii Chyzh Artur Naglik Anton Yavorski Natalia Yavorska Mikolaj Karpinski State Higher Vocational School in Nowy Sacz Nowy Sącz Poland Ternopil National Economic University Ternopil Ukraine Ternopil Ivan Pul'uj National Technical University Ternopil Ukraine University of Bielsko-Biala Bielsko-Biala Poland

Recent advances in the micro electromechanical systems technology MEMS, wireless communications and digital electronics allowed to create inexpensive, low-powered, multi-functional nodes. they are small and "talk" directly with each other. Wireless Sensor Network (WSN) is considered to be a distributed, self-organizing system of a large number of sensors and assistive devices that communicate with each other through the radio channel. Sensor networks are based on the joint work of a large number of tiny nodes that consist of data collection and processing modules and a transmitter or a transceiver. Such networks have significant advantages over the set of traditional sensors. the main problem in sensor networks is a short stint due to high power consumption and the incompatibility of various hardware. Because of the absence of a clear standardization in sensor networks, there are several different platforms. All platforms meet the essential basic requirements for sensor networks: low power consumption, long operating time, low-power transmitters and presence of sensors. Each platform is in its own interest substantiated and has its own peculiarities. they will transmit the observation data to the central nodes where data collection, storing, and processing will be performed. the main purpose is to enhance the security wireless sensor networks.

关键词： Wireless sensor networks Sensor phenomena and characterization Radio transmitters Protocols Data communication Routing

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PLAG: Practical Landmark Allocation for Cloud Geolocation

PLAG: Practical Landmark Allocation for Cloud Geolocation

引用

IEEE international conference on Cloud computing, CLOUD

作者： Maziar Fotouhi Abhishek Anand Ragib Hasan Department of Computer and Information Sciences University of Alabama at Birmingham Birmingham AL

Knowing the physical location of files in a cloud system is of a great importance for any user, as is it can affect the whole service drastically. However, pinpointing the exact coordinates for the location of a server is very challenging. Providers prefer not to share the location of their data centers with public for security reasons, and this fact also adds to the complexity of this concept. Researchers have recently developed delay based schemes for cloud data geolocation, some of which use proprietary landmarks for location verification. Unfortunately, such landmark-based schemes are often impractical due to high cost and latency. In this paper, we have developed a practical scheme for landmark allocation in cloud data geolocation. We augment existing approaches with a new landmark allocation modification to get the same or often better accuracy, while decreasing the cost considerably. Our approach improves the existing state of the art by introducing the concept of publicly distributed landmarks for all delay based geolocation techniques.

关键词： Geology Delays Delay effects Cloud computing Servers Accuracy Resource management

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Securing Cryptographic Keys in the IaaS Cloud Model 15

Securing Cryptographic Keys in the IaaS Cloud Model

引用

IEEE international conference on Utility and Cloud computing (UCC)

作者： B. AlBelooshi K. Salah T. Martin E. Damiani Department of Electrical and Computer Engineering Khalifah University of Science Technology and Research Sharjah UAE

ISBN: (纸本)9780769556970

Infrastructure-as-a-Service (IaaS) is a widespread cloud computing provisioning model where ICT infrastructure, including servers, storage and networking, is supplied on-demand, in a pay-as-you-go fashion. IaaS cloud providers give their clients virtual machines (VMs) that are controlled by cloud administrators who can run, stop, restore and migrate the VMs. A typical threat to IaaS is unauthorized access of untrustworthy administrators to cloud users' sensitive information residing in VMs' memory. In this paper we focus on the threat of users' cryptographic keys being stolen from the RAM of the VM they provision. We propose a decrypt-scatter/gather-decrypt technique that allows users to carry our encryption/decryption while protecting keys from unauthorized peeks on the part of cloud administrators. Our technique does not require modification to the current cloud architecture, but only the availability of a Trusted Platform Module (TPM) capable of creating and holding a TPM-protected public/private key pair. It lends itself to security-as-a-service scenarios where third parties perform encryption/decryption on behalf of data owners.

关键词： Cloud computing Random access memory Encryption Virtualization Virtual machine monitors

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Power Consumption of Virtualization Technologies: An Empirical Investigation

Power Consumption of Virtualization Technologies: An Empiric...

引用

IEEE international conference on Utility and Cloud computing (UCC)

作者： Roberto Morabito Department of Communications and Networking (Comnet) Aalto University Espoo Finland Ericsson Research NomadicLab Jorvas Finland

Virtualization is growing rapidly as a result of the increasing number of alternative solutions in this area, and of the wide range of application field. Until now, hypervisor-based virtualization has been the de facto solution to perform server virtualization. Recently, container-based virtualization -- an alternative to hypervisors -- has gained more attention because of lightweight characteristics, attracting cloud providers that have already made use of it to deliver their services. However, a gap in the existing research on containers exists in the area of power consumption. this paper presents the results of a performance comparison in terms of power consumption of four different virtualization technologies: KVM and Xen, which are based on hypervisor virtualization, Docker and LXC which are based on container virtualization. the aim of this empirical investigation, carried out by means of a testbed, is to understand how these technologies react to particular workloads. Our initial results show how, despite of the number of virtual entities running, both kinds of virtualization alternatives behave similarly in idle state and in CPU/Memory stress test. Contrarily, the results on network performance show differences between the two technologies.

关键词： Virtualization Containers Virtual machine monitors Power demand Hardware Servers Operating systems

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Kafka and Its Using in High-throughput and Reliable Message Distribution

Kafka and Its Using in High-throughput and Reliable Message ...

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international Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Zhenghe Wang Wei Dai Feng Wang Hui Deng Shoulin Wei Xiaoli Zhang Bo Liang Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming China

Nowadays, with the rapid development of distributed computing, message distribution has been more and more important to distributed systems. Kafka was developed to collect and distribute massive messages for distributed systems. It is a high-throughput distributed messaging system. Kafka can always keep stable performance even if it processes millions of messages per second. Messages are persistent in Kafka, and Kafka is able to scale out easily. Besides, it is suitable for both online and offline processing simultaneously. Existing messaging systems all have some disadvantages. In comparison with these messaging systems, Kafka has superior performance. therefore, Kafka has already been successfully used in production by some companies for a certain time. though Kafka is still able to be improved in some aspects, it's expected to have broad development prospects.

关键词： Reliability Servers throughput Real-time systems Computers distributed databases Data processing

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Data Partition Optimization for Column-Family NoSQL databases

Data Partition Optimization for Column-Family NoSQL database...

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IEEE international conference on Smart City

作者： Li-Yung Ho Meng-Ju Hsieh Jan-Jan Wu Pangfeng Liu Research Center for Information Technology Innovation Academia Sinica Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Department of Computer Science and Information Engineering Graduate Intitute of Networking and Multimedia National Taiwan University

ISBN: (纸本)9781509018949

Data conversion has become an emerging topic in BigData era. To face the challenge of rapid data growth, legacy or existing relational databases have the need to convert into NoSQL column-family database in order to achieve better scalability. the conversion from SQL to NoSQL databases requires combining small, normalized SQL data tables into larger NoSQL data tables;a process called denormalization. A challenging issues in data conversion is how to group the denormalized columns in a large data table into "families" in order to ensure the performance of query processing. In this paper, we propose an efficient heuristic algorithm, GPA (Graph-based Partition Algorithm), to address this problem. We use TPC-C and TPC-H benchmarks to demonstrate that, the column-families produced by GPA is very efficient for large scale data processing.

关键词： Vertical partition Column partition Column family NoSQL database

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MILP-Based Approach for Efficient Cloud IaaS Resource Allocation

MILP-Based Approach for Efficient Cloud IaaS Resource Alloca...

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IEEE international conference on Cloud computing, CLOUD

作者： Khaled Metwally Abdallah Jarray Ahmed Karmouch SITE University of Ottawa Ottawa Canada

Current data center designs suffer from poor resource utilization. Several research works have addressed the data center resource allocation problem, and recent proposals have focused on network resource utilization as a bottleneck problem in data centers. However, little attention has been paid to manage the convergence of networking and other infrastructure resources. In this paper, we present a solution for improving data center's resource utilization. We introduce a unified cloud resource representation model and build a general resources repository using that model. We define a combined controller to manipulate infrastructure resources collected in the repository. A joint optimization model that performs the resource allocation as the main controller operation is also presented. this model represents the integration of semantic similarity and closeness centrality concepts and is formulated on a two-phase Mixed Integer Linear Programming (MILP-2P-IaaS): (i) mapping of hosting resources, and (ii) connectivity composition. Simulation results show that the (MILP-2P-IaaS) resource allocation approach improves data center's resource utilization and outperforms other benchmarks in terms of resource utilization and acceptance ratio.

关键词： Resource management Bandwidth Semantics Computational modeling Cloud computing Quality of service Benchmark testing

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Scalable Network Traffic Classification Using distributed Support Vector Machines

Scalable Network Traffic Classification Using Distributed Su...

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IEEE international conference on Cloud computing, CLOUD

作者： Do Le Quoc Valerio D'Alessandro Byungchul Park Luigi Romano Christof Fetzer Dresden Univ. of Technol. Dresden Sachsen DE Universita degli Studi di Napoli Federico II Napoli Campania IT Parthenope University of Naples Naples Italy University of Toronto Toronto Canada Dresden University of Technology Dresden Germany

Internet traffic has increased dramatically in recent years due to the popularization of the Internet and the appearance of wireless Internet mobile devices such as smart-phones and tablets. the explosive growth of Internet traffic has introduced a practical example that demonstrates the concept of Big Data. Accurate identification and classification of large network traffic data plays an important role in network management including capacity planning, network forensics, QoS and intrusion detection. However, the state-of-the-art solutions, which rely on a dedicated server, are not scalable for analyzing high volume network traffic data. In this paper, we implement a distributed Support Vector Machines (SVMs) framework for classifying network traffic using Hadoop, an open-source distributed computing framework for Big Data processing. We design a global parameter store that maintains the global shared parameters between SVM training nodes. the distributed SVMs have been deployed on a 20 node cluster to analyze real network traffic trace. the results demonstrate that with 19 Mapper nodes the system is around 30% faster than Cloud SVM solution and outperforms the standalone SVM with nearly 9 times faster in training process and 15 times in the classifying process. In addition, the distributed SVMs architecture is designed to analyze large scale datasets. therefore, it can be used not only for processing network traffic dataset, but also other large scale datasets such as Web data.

关键词： Training Support vector machines Feature extraction Accuracy Internet Big data Scalability

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A Semi-distributed Access Control Management Scheme for Securing Cloud Environment

A Semi-distributed Access Control Management Scheme for Secu...

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IEEE international conference on Cloud computing, CLOUD

作者： Syed Rizvi John Mitchell Department of Information Sciences and Technology Pennsylvania State University Altoona PA USA

Despite numerous advantages that cloud computing offer (e.g., Flexibility, elasticity, scalability, etc.), many potential clients are still hesitant to join the cloud due to their security and privacy concerns. Outsourcing the data to a cloud in a multitenant environment brings many security challenges including data leaks, threats, and malicious attacks. the cloud computing platform, virtual servers, and the provider's services are highly dynamic and diverse in nature, making the traditional access control mechanisms (e.g., Firewalls and VLAN etc.) less effective in controlling the unauthorized access to cloud's data and resources. Several access control policies and authorization system have been proposed in literature to defend against cloud security threats. Most of these systems are designed to work with one or more access control policies. However, little work has been done to develop generic access control architecture capable to work with most of the available access control policies. In this paper, we present a new access control architecture using a global resource management system (GRMS) to effectively handle both local and remote access requests. the introduction of GRMS makes our proposed architecture semi distributed at the expense of minimal request-response time. In addition, our proposed architecture works effectively with both peered access control module (PACM) and virtual resource manager (VRM) to protect and manage all resources and services of cloud providers from unauthorized access.

关键词： Computer architecture Cloud computing Authorization Virtualization Containers

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Towards a Multi-objective VM Reassignment for Large Decentralised Data Centres 15

Towards a Multi-objective VM Reassignment for Large Decentra...

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IEEE international conference on Utility and Cloud computing (UCC)

作者： Takfarinas Saber Anthony Ventresque Ivona Brandic James thorburn Liam Murphy University College School of Computer Science and Informatics Dublin Ireland IBM Research Damastown Industrial Estate Dublin Ireland Institute of Information Systems Vienna University of Technology Vienna Austria IBM Software Group Toronto Canada

ISBN: (纸本)9780769556970

Optimising the IT infrastructure of large, often geographically distributed, organisations goes beyond the classical virtual machine reassignment problem, for two reasons: (i) the data centres of these organisations are composed of a number of hosting departments which have different preferences on what to host and where to host it, (ii) the top-level managers in these data centres make complex decisions and need to manipulate possible solutions favouring different objectives to find the right balance. this challenge has not yet been comprehensively addressed in the literature and in this paper we demonstrate that a multi-objective VM reassignment is feasible for large decentralised data centres. We show on a realistic data set that our solution outperforms other classical multi-objective algorithms for VM reassignment in terms of quantity of solutions (by about 15% on average) and quality of the solutions set (by over 6% on average).

关键词： Optimization Reliability Servers Electronic mail Virtual machining Companies Cloud computing

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