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A Novel distributed Fog-based Networked Architecture to Preserve Energy in Fog Data Centers 14

A Novel Distributed Fog-based Networked Architecture to Pres...

引用

14th IEEE international conference on Mobile Ad Hoc and Sensor Systems (MASS)

作者： Pooranian, Zahra Shojafar, Mohammad Naranjo, Paola G. Vinueza Chiaraviglio, Luca Conti, Mauro Univ Padua Padua Italy CNIT Intel Software Innovator Rome Italy Sapienza Univ Rome DIET Rome Italy Tor Vergata Univ Rome Dept Elect Engn Rome Italy

ISBN: (纸本)9781538623237

the distinguishing feature of the Fog computing (FC) paradigm is that FC spreads communication and computing resources over the wireless access network, so as to provide resource augmentation to resource and energy-limited wireless (possibly mobile) devices. Since FC would lead to substantial reductions in energy consumption and access latency, it will play a key role in the realization of the Fog of Everything (FoE) paradigm. the core challenge of the resulting FoE paradigm is to materialize the seamless convergence of three distinct disciplines, namely, broadband mobile communication, cloud computing, and Internet of Everything (IoE). In this paper, we present a new IoE architecture for FC in order to implement the resulting FoE technological platform. then, we elaborate the related Quality of Service (QoS) requirements to be satisfied by the underlying FoE technological platform. Furthermore, in order to corroborate the conclusion that advancements in the envisioned architecture description, we present: (i) the proposed energy aware algorithm adopt Fog data center;and, (ii) the obtained numerical performance, for a real-world case study that shows that our approach saves energy consumption impressively in the Fog data Center compared with the existing methods and could be of practical interest in the incoming Fog of Everything (FoE) realm.

关键词： Fog computing (FC) Internet of Everything (IoE) Fog of Everything (FoE) energy-efficiency networked computing platform distributed resource management

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conference organization

Conference organization

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ACIS international conference on Software Engineering, Artificial Intelligence, networking, and Parallel/distributed computing (SNPD)

Provides a listing of current committee members and society officers.

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Towards interoperability between heterogeneous distributed components

Towards interoperability between heterogeneous distributed c...

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12th international Workshop on Adaptive and Reflective Middleware, ARM 2013 - Co-located with ACM/IFIP/USENIX 14th international Middleware conference, Middleware 2013

作者： Cassemiro Do Nascimento, Sidney Carvalho, Felipe Oliveira Da Rocha, Tarcisio Brazil Brazil

ISBN: (纸本)9781450325530

the popularization of middleware occurred in recent years promoted the emergence of different technological models. Because of this diversity, interoperability between different models of software components becomes essential to promote the integration of heterogeneous parts. the problems involved with interoperability are treated in general by adopting middleware systems able to mediate and establish communication between different platforms. In this context, this paper proposes the InteropFrame, a framework for interoperability between different models of software components (e.g. OpenCOM and Fractal) that aims its extensibility to support other models through the development of plugins. © 2013 ACM.

关键词： Middleware

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High performance Java sockets (HPJS) for scientific health clouds

High performance Java sockets (HPJS) for scientific health c...

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2012 IEEE 14th international conference on e-Health networking, Applications and Services, Healthcom 2012

作者： Amin, Muhammad Bilal Shafi, Aamir Hussain, Shujaat Khan, Wajahat Ali Lee, Sungyoung Department of Computer Engineering Kyung Hee University Korea Republic of School of Electrical Engineering and Computer Sciences National University of Sciences and Technology Pakistan

ISBN: (纸本)9781457720390

Cloud computing has been adopted by health-care industry for their data's storage, manipulation, and secured sharing needs. However, cloud's distributed nature can be exploited to the use of scientific applications that are designed for health-care data evaluation. these scientific applications, such as, Medical Imaging, Gene and Protein annotation, Mapdrug therapy and Clinical Decision Support Systems (CDSS), require high-performance messaging libraries with minimum computational and communication overhead, and efficient resource utilization. the proposed High Performance Java Sockets (HPJS) encapsulates the needs of high-performance messaging of scientific applications for cloud platforms. HPJS effectively uses Java's socket implementation for high-performance inter-process communication. With single-copy protocol, thread re-usability and reduced communication overhead, HPJS can perform messaging twice as fast to conventional buffered-base communication libraries. © 2012 IEEE.

关键词： distributed cloud

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Reducing Cloud Workload Costs in Geographically distributed Data Centers with GeoSched 14

Reducing Cloud Workload Costs in Geographically Distributed ...

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14th international conference on computing Communication and networking Technologies, ICCCNT 2023

作者： Sai, Vishnuvajjhula Pranav Raj, Harsh University Electronic and Communications Engineering Telangana Hyderabad India SRM Institute of Science and Technology Computer Science and Engineering Delhi India

ISBN: (纸本)9798350335095

In this research paper, we present GeoSched, a job provisioning framework for geo-distributed data centers. Our approach takes into account parameters such as temperature and electricity prices to intelligently schedule jobs across different data centers. through extensive simulations, we evaluate the performance of GeoSched and observe significant improvements in energy efficiency. Specifically, our meta-scheduler reduces energy consumption by 8.2% and decreases the cost of operation by 11.7%. these results highlight the effectiveness of our approach in minimizing data center operating costs while meeting workload demands and maintaining Service Level Agreements (SLAs). For future work, we plan to investigate additional factors that impact energy consumption, including the availability of renewable energy sources and the energy required for data transfer. We also aim to develop more comprehensive SLAs that can capture the complex and diverse requirements of cloud workloads, such as response time, availability, throughput, and data consistency. Furthermore, we recognize the importance of considering workload diversity in our meta-scheduling approach. Different types of workloads have varying requirements and priorities, and accommodating them is crucial for optimizing resource allocation and job provisioning. Additionally, we intend to explore the scalability of our framework for larger and more intricate data center networks. this would involve developing more sophisticated resource management strategies and algorithms to handle the complexities of scaling up. By addressing these areas of future research, we aim to further enhance the energy efficiency and performance of geo-distributed data centers while providing robust SLA adherence. © 2023 IEEE.

关键词： Energy efficiency

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DXRAM: A Persistent In-Memory Storage for Billions of Small Objects 14

DXRAM: A Persistent In-Memory Storage for Billions of Small ...

引用

14th international conference on Parallel and distributed computing, Applications and Technologies (PDCAT)

作者： Klein, Florian Schoettner, Michael Univ Dusseldorf Inst Informat D-40225 Dusseldorf Germany

ISBN: (纸本)9781479924189

Large-scale interactive applications and realtime data-processing are facing problems with traditional disk-based storage solutions. Because of the often irregular access patterns they must keep almost all data in RAM caches, which need to be manually synchronized with secondary storage and need a lot of time to be re-loaded in case of power outages. In this paper we propose a novel key-value storage keeping all data always in RAM by aggregating resources of potentially many nodes in a data center. We aim at supporting management of billions of small data objects (16-64 byte) like for example needed for storing graphs. A scalable low-overhead meta-data management is realized using a novel range-based ID approach combined with a super-overlay network. Furthermore, we provide persistence by a novel SSD-aware logging approach allowing to recover failed nodes very fast.

关键词： distributed systems distributed memory Fault tolerance Memory management

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PLUTUS: Leveraging Location-based Social Networks to Recommend Potential Customers to Venues

PLUTUS: Leveraging Location-based Social Networks to Recomme...

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IEEE 14th international conference on Mobile Data Management (MDM)

作者： Sarwat, Mohamed Eldawy, Ahmed Mokbel, Mohamed F. Riedl, John Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781467360685

In a business setting, the customer value is crucial as it determines how much it is worth spending to acquire a particular customer. Viral marketing techniques leverages social ties among users to help advertising a particular product. Recently, as mobile devices (e.g., smart phones, GPS devices) became ubiquitous, location-based social networking websites (e. g., Gowalla, BrightKite, Foursquare) are getting more and more popular. Along with location-based social networking services being prominent, new kind of data came into play besides the traditional social networking data: (1) Spatial data: represents the users geo-locations, venues geo-locations and information about users visiting different venues. (2) Users Opinions data: represents how much a user likes the venues she visits (e.g., Alice visited restaurant A and gave it a rating of five over five). In this paper, we present PLUTUS;a framework that assists venues (e.g., restaurant, gym, shopping mall) owners in growing their business. To recommend the best set of customers, PLUTUS takes three main aspects into consideration: (1) Social aspect, (2) Spatial aspect, and (3) Users opinions aspect. To this end, PLUTUS proposes two main algorithms: (1) Profit Calculation: It is responsible of calculating the total profit that a user u may add to a venue v taking into account the social, spatial, and user opinions aspects. (2) Profit Maximization: this algorithm is used to maximize the total profit of a given venue. We evaluated PLUTUS using real data set extracted from an existing Location-based Social networking website, Foursquare. the results show that Plutus achieves higher estimated profit and more efficient profit calculation than naive marketing algorithms.

关键词： advertising data processing customer satisfaction mobile computing social networking (online)

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Mobile Stream Sampling under Time Constraints

Mobile Stream Sampling under Time Constraints

引用

IEEE 14th international conference on Mobile Data Management (MDM)

作者： Boutsis, Ioannis Kalogeraki, Vana Athens Univ Econ & Business Dept Informat Athens Greece

ISBN: (纸本)9781467360685

the proliferation of mobile networking and the increasing capabilities of smartphone devices in the recent years have resulted in transforming mobile smartphone devices into ubiquitous sensing platforms. In this new class of "Community-based Participatory Sensing" systems, users actively participate in the data collection and sharing for the benefit of the community, in a wide range of application areas from entertainment, to transportation, to environmental monitoring. these approaches, however, generate large amounts of transient data streams, leading to real-time computational challenges. In this paper we propose sampling algorithms on streams of mobile data generated by ubiquitous sensing devices that need to be processed under time constraints. In our approach users participate in the system by sensing and sharing streams of data. the system then uses a sampling mechanism to select a subset of data streams that preserves the characteristics of the stream data and provides the highest "information gain" to the system, given the real-time, budget and resource constraints. Detailed experimental results illustrate that our approach is practical, efficient and depicts good performance.

关键词： data handling mobile computing smart phones

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Resource unaware computing - A distributed strategy for divisible load processing on linear daisy chain networks

Resource unaware computing - A distributed strategy for divi...

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14th IEEE international conference on Networks

作者： Jia, Jingxi Veeravalli, Bharadwaj Natl Univ Singapore Dept Elect & Comp Engn Comp Networks & Distributed Syst Lab CNDS 4 Engn Dr 3 Singapore 117576 Singapore

ISBN: (纸本)9780780397460

In this paper we present a novel load distribution strategy for scheduling divisible loads on linear networks, when the speeds of the computing nodes and the speeds of the communication links are unknown. this practical assumption is captured in our problem formulation and we present a novel strategy, referred to as Early Start Strategy (ESS), to generate a load distribution. Our strategy estimates the speed parameters and takes distinct advantage in utilizing a processor that responds earliest in the computation and including other fast processors in a progressive manner in phases to minimize the overall processing time. We analyze the strategy under several influencing parameters such as, load size, network size, and probe load size. We present simulation studies to validate all the theoretical findings and quantify the performance of our strategy.

关键词： divisible loads linear networks communication delays processing time computation time

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An Ensemble Learning-Based DDoS Attack Detection Considering the Impact of ICA 14

An Ensemble Learning-Based DDoS Attack Detection Considering...

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14th international conference on computing Communication and networking Technologies, ICCCNT 2023

作者： Jana, Anique Mahato, Dipesh Karmakar, Raja Ghosal, Sandipan Chatterjee, Twinkle Techno International NewTown Computer Science and Engineering Kolkata700156 India Heritage Institute of Technology Computer Science and Engineering Kolkata700107 India Techno International NewTown Information Technology Kolkata700156 India

ISBN: (纸本)9798350335095

distributed denial of service (DDoS) attacks can cause considerable financial harm and operational concerns in the internet business era. Detecting such attacks necessitates overcoming two challenges: distinguishing normal packets from attack packets and consistently and effectively identifying distinct attack categories. As a result, an ideal detection system should be simple, reliable, and effective, with low false alarm rates. the goal of this paper is to give an analysis of machine learning (ML) methods for the detection of DDoS attacks using Ensemble Learning with and without implementing Independent Component Analysis (ICA). It improves the feature extraction, source separation, noise reduction, and data pre-processing, resulting in better performance and insights. the KDD-99 dataset is used to train and test ML models, using Logistic Regression, Random Forest, Decision Trees, K-Nearest Neighbors, and Gaussian Naive Bayes. they are used to extract data while categorizing the different types of input features during the training. the performance of the proposed mechanism is analyzed with and without the use of ICA. Results show that the DDoS attack is most successfully detected using the Random Forest classifier with an accuracy of 99.9670%. Moreover, ICA improves the performance of all ML models when compared to unsupervised learning techniques. © 2023 IEEE.

关键词： Decision trees

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