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A Comparative Study on Caching Strategies in Content Centric networking for Mobile Networks 11

A Comparative Study on Caching Strategies in Content Centric...

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11th international conference on Advanced computing (ICoAC)

作者： Priscilla, C. Victoria Charulatha, A. R. Univ Madras PG Dept Comp Sci SDNB Vaishnav Coll Women Chennai Tamil Nadu India Univ Madras Dept Comp Sci Stella Maris Coll Chennai Tamil Nadu India

ISBN: (纸本)9781728152868

Mobile communication has become an integral part of everybody's life. the global internet traffic is increasing at an alarming rate because of the demand for internet content like web pages, audio files, and videos. the success of the internet is because of the success of various internet applications which is also the reason for growing internet traffic. this has led to redefining the IP stack by allowing the content-centric networking, CCN. CCN is dependent on the caching contents in-network and off-network nodes. there have been various strategies on how to cache the contents. the Quality of Service offered by the providers improves with a proper selection of caching strategy, which helps in increasing the network efficiency by lowering the bandwidth of the network. the selection of an appropriate caching strategy also proves to improve the user's quality of experience. this paper discusses the need, architecture of CCN, the various caching strategies and a comparative study on LCE, LCD, ProbCache and MAGIC caching strategies by running in a common simulation environment.

关键词： Content Caching Caching strategies Content Centric networking LCE LCD ProbCache MAGIC

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distributed Machine Learning over Directed Network with Fixed Communication Delays 19

Distributed Machine Learning over Directed Network with Fixe...

引用

11th international conference on Machine Learning and computing (ICMLC)

作者： Guo Zhenning Beijing Univ Technol Beijing Dublin Int Coll Dublin Beijing Peoples R China

ISBN: (纸本)9781450366007

In this paper, we present a distributed machine learning algorithm over a network with fixed-delay tolerance. the network is directed and strongly connected. the training dataset is distributed to all agents in the network. We combine the distributed convex optimization (which utilizes double linear iterations) and corresponding machine learning algorithm. Each agent can only access its own local dataset. Suppose the delay between any pair of agents is time-invariant. the simulation shows that our algorithm is able to work under delayed transmission, in the sense that over time at each agent i the ratio of the estimate value x(i)(t) and scaling variable y(i)(t) can converge to the optimal point of the global cost function corresponding to the machine learning problem.

关键词： distributed system machine learning network convex optimization

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Sentiment Analysis Using Language Models: A Study

Sentiment Analysis Using Language Models: A Study

引用

international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Spraha Kumawat Inna Yadav Nisha Pahal Deepti Goel Amity University Noida India RIL Mumbai India

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Sentiment analysis is concerned with extracting sentiment to ascertain the attitudes, and emotions associated with the text. It is broadly applied to voice of the customer as they convey their experience and feelings more blatantly which is why comprehending customer's emotions is a must. To identify and classify these unstructured emotions natural language processing (NLP) and machine learning approaches have been adopted in recent times. the main issue with the existing techniques is the inability to deal with the correct interpretation of context owing to lack of labeled data. In this paper, we studied deep neural network based language models to interpret and classify textual sequences into positive, negative or neutral emotions which remove the bottleneck of explicit human labeling. these models were analyzed and evaluations were performed on the Twitter US Airline Sentiment dataset. We have observed a considerable amount of improvements with respect to prior state-of-the-art approaches which closes the gap with supervised feature learning.

关键词： Deep learning Sentiment analysis Analytical models Social networking (online) Atmospheric modeling Transformer cores Data models

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Spam Detection using ANN and ABC Algorithm

Spam Detection using ANN and ABC Algorithm

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Amar Singh Nidhi Chahal Simranjit Singh Suneet Kumar Gupta Bennett University Noida KIET Group of Institutions Ghaziabad India Bennett University Noida India

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Social network becomes an effective method to engage with our friends. It enables the users to extract a number of in-formation and its usage are increasing day by day. Amidst all the social networking sites, Twitter is one of the interactive social networking services. To change the authorized user accounts, many spammers are utilized a vast amount of spam. Machine Learning (ML) technique is utilized for spam detection system in social sites and for the detection of spammer. Data collection is usually done from H-Spam 14 site with the help of pre-processing mechanism, the data is transforming into lowercase. After the first step, pre-processed data comes under feature extraction phase, which utilizes tokenization process to breakdown each sentence into word group in order to extract the best feature from the raw data. the optimization algorithm referred as Artificial Bee Colony (ABC) is used to pick the optimized value from extracted set of features. It is also utilized to get the optimal sets of features from spam and non-spam data. At the end, performance measure criterion and comparing the existing and proposed work in order to look over the progress of the proposed work. In this work, spam detection system is having higher accuracy, precision, recall, and F-measure as compares to classifiers used previously such as, Naïve Bayes and Support Vector Machine (SVM).

关键词： Support vector machines Social networking (online) Electric breakdown Machine learning Feature extraction Tokenization Optimization

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Blockchain-centric Resource Management System for Disaster Response and Relief

Blockchain-centric Resource Management System for Disaster R...

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Vinayak G. Bhat H. P. Pranaav S. Mini Deepak Tosh National Institute of Technology Goa Goa India University of Texas El Paso TX

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Disaster response and relief efforts require effective handling of resources and timely impact of the goods at the disaster affected areas with least processing time. Time required for goods to travel from origin to affected region has a few components but the one which can be reduced most is the time taken to handle the legalities and paperwork. We propose a resource management system to tackle the issue of extensive paperwork for deployment of relief material through a blockchain based web/mobile application using Hyperledger Fabric. this acts as a communication channel for a consortium of relief enterprises and organisations, a gateway for the populous to donate goods and for volunteers to make their services available to the various non-profit organisations on the platform.

关键词： distributed ledger Communication channels Blockchain Logic gates Fabrics Resource management

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Cyberbullying Detection and Prevention: Data Mining in Social Media

Cyberbullying Detection and Prevention: Data Mining in Socia...

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Daniyar Sultan Azizah Suliman Aigerim Toktarova Batyrkhan Omarov Satmyrza Mamikov Gulbakhram Beissenova al-Farabi Kazakh National University Almaty Kazakhstan College of Computing & Informatics Tenaga National University Kuala Lumpur Malaysia International Kazakh-Turkish University Almaty Kazakhstan al-Farabi Kazakh National University Akhmet Yassawi International Kazakh-Turkish University Kazakhstan University of friendship of people’s academician A. Kuatbekov Shymkent Kazakhstan M. Auezov South Kazakhstan University University of friendship of people’s academician A. Kuatbekov Shymkent Kazakhstan

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

this article is devoted to analysis of the articles on cyberbullying of children and adolescents and creating the methodology of working on the own work, which related especially to Kazakh social media. the article provides examples of similar works by foreign researchers, the United States, England and other European countries. Using the methods of theoretical, namely analysis, synthesis, and empirical: comparison and experiment, the analysis of works on this topic was carried out, and this work was aimed at analyzing the problem in the Kazakh space. In brief, we consider the issue of creating a parser, as well as collecting data for training machine learning and deep learning algorithms that could find and block texts containing a humiliating slope in real time. the article will be of interest to both novice specialists who are engaged in data analysis, and experienced ones to expand their *** question of implementing deep learning algorithms requires further study, which is one of the parts of a large work being done, as well as a future topic for a subsequent article.

关键词： Deep learning Training Machine learning algorithms Social networking (online) Planets Real-time systems Internet

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Optimizing DG Parameters for Voltage Profile and Real Power Loss Improvement using Elephant Herd Optimization

Optimizing DG Parameters for Voltage Profile and Real Power ...

引用

international conference on computing and networking Technology (ICCNT)

作者： Shreya Mahajan Yajvender Pal Verma UIET Panjab University Chandigarh India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

the purpose of distributed generation in improving voltage profile, abating losses, slashing fuel cost and boosting efficiency is becoming important in modern power system operation. this paper summarizes an unconventional optimization technique based on the elephant herd optimization for distributed generation integration in the power system which is inspired by the herding behavior of elephant group. this article elaborates a multi objective optimization problem considering two objectives to reduce the total real power losses of the system and to minimize the overall voltage deviation by placing the distributed generation at suitable location. the objectives are collaborated into a scalar objective optimization problem by using weighted sum method. the proposed elephant herd optimization based methodology is compared with the particle swarm optimization approach for IEEE 14 bus system. the comparative results relating to voltage profile, real power losses and convergence characteristics indicate the superiority of elephant herd optimization over the particle swarm optimization.

关键词： Optimization Mathematical model distributed power generation Power systems Generators Power system stability Particle swarm optimization

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Are Coordinator Election Algorithms in distributed Systems Vulnerable?

Are Coordinator Election Algorithms in Distributed Systems V...

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international conference on computing and networking Technology (ICCNT)

作者： Shital S Supase Rajesh B Ingle Pune Institute of Computer Technology Pune India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Now a days distributed systems are backbone of majority of the networked applications. It has multiple entities working collaboratively. this collaboration needs to be coordinated by an entity among the member entities. the selection of such coordinator entity is critical in distributed systems. the process of coordinator selection is to be performed by member entities. this is termed as coordinator election in distributed systems. Member nodes need to communicate for electing the coordinator entity. the communication over a network makes the process of coordinator election vulnerable to faults, failures and security attacks. these vulnerabilities may lead to the threats like deletion or modification of election data and fake voting. As a result of the same the election algorithm may not terminate or the wrong entity may be elected as coordinator. Hence it is important to discover such vulnerabilities and threats. Existing coordinator election algorithms sparsely address the vulnerabilities. In this work, the vulnerabilities of the coordinator election algorithm are identified and a taxonomy for the same is proposed. the solution approaches for dealing with these vulnerabilities are discussed.

关键词： Voting Security Taxonomy Task analysis Software algorithms Software Partitioning algorithms

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Optimal Task Offloading and Resource Allotment Towards Fog-Cloud Architecture

Optimal Task Offloading and Resource Allotment Towards Fog-C...

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Vibha Jain Bijendra Kumar Computer Science and Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Advancement in IoT research encouraged the generation of ubiquitous computing devices and changed their way of utilization. the high spawning of data through these computing devices and its computation demands the evolvement of a new paradigm. Instead of using a centralized cloud-based system, a new distributed computing environment has been emerged for feature computational and storage capabilities at the periphery of the network called fog computing. the main idea behind fog computing is to utilize the processing and storage resources of fog nodes by offloading the computation-intensive IoT tasks. In the fog-enabled Cloud/IoT architecture, resource-constraint IoT devices offload their resource-hungry tasks to nearby deployed fog nodes to reduce the processing time and fast execution. Fog enabled processing guarantees fast response time and better energy management. therefore, we are proposing a optimal offloading decision strategy and resource allocation scheme in fog atmosphere by minimizing the total energy consumption of IoT users concerning the latency of communication and computation. To optimally offload the tasks to fog node an optimization problem is designed and an improved version of branch-and-bound tree is proposed for its evaluation. Some of the metrics we consider for performance evaluation are average task latency, average energy consumption per task and average remaining energy per IoT node. Simulation results show that using proposed offloading decision strategy, network performance improve significantly.

关键词： Energy consumption Clouds Computer architecture Ubiquitous computing Time factors Task analysis Edge computing

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Amulet: an open-source wrist-worn platform for mHealth research and education 11

Amulet: an open-source wrist-worn platform for mHealth resea...

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11th international conference on Communication Systems & Networks (COMSNETS)

作者： Kotz, David Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA

ISBN: (纸本)9781538679029

the advent of mobile and wearable computing technology has opened up tremendous opportunities for health and wellness applications. It is increasingly possible for individuals to wear devices that can sense their physiology or health-related behaviors, collecting valuable data in support of diagnosis, treatment, public health, or other applications. From a researcher's point of view, the commercial availability of these "mHealth" devices has made it feasible to conduct scientific studies of health conditions and to explore health-related interventions. It remains difficult, however, to conduct systems work or other experimental research involving the hardware, software, security, and networking aspects of mobile and wearable technology. In this paper we describe the Amulet platform, an open-hardware, open-software wrist-worn computing device designed specifically for mHealth applications. Our position is that the Amulet is an inexpensive platform for research and education, and we encourage the mHealth community to explore its potential.

关键词： mHealth wearable computing mobile computing health research education

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