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Time-Aware Reactive Storage in Wireless Edge Environments 16

Time-Aware Reactive Storage in Wireless Edge Environments

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16th EAI international conference on Mobile and Ubiquitous Systems - computing, networking and Services (MobiQuitous)

作者： Silva, Joao A. Paulino, Herve Lourenco, Joao M. Leitao, Joao Preguica, Nuno Univ NOVA Lisboa Dept Informat NOVA Lab Comp Sci & Informat Fac Ciencias & Tecnol P-2829516 Caparica Portugal

ISBN: (纸本)9781450372831

Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, these devices often experience poor connectivity, leading to availability issues if applications' storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed. Thus, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this paper, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose Thyme, a novel time-aware reactive data storage system for wireless edge networks, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of Thyme and evaluate it through simulation, characterizing the scenarios best suited for its use. The evaluation shows that Thyme allows for reliable notification and retrieval of relevant data with low overhead and latency.

关键词： distributed storage publish/subscribe wireless networks mobile devices edge computing

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Analysis of Cloud Forensics Techniques for Emerging Technologies

Analysis of Cloud Forensics Techniques for Emerging Technolo...

引用

computing, networking, Telecommunications & Engineering Sciences Applications (CoNTESA), international conference on

作者： Syed Ahmed Ali Shahzad Memon Farhan Sahito University of Sindh Jamshoro Pakistan Graz University of Technology Graz Austria

ISBN: (数字)9781728184883

ISBN: (纸本)9781728184890

Cloud computing is the technology of the modern era having invaluable features that convince enterprises to adopt. It provides opportunities to the enterprises to compete with their opponents, to facilitate their customers, and grow up their day to day business by reducing cost and infrastructure management burden. Regardless of the enormous features offered by cloud computing, enterprises generally hesitate to adopt it due to the physical inaccessibility and deployment of their intellectual properties to a location that is unknown to them. On the other hand, the cyber-criminals sniffing around to find the loopholes to breach in, and compromise the confidentiality, integrity, and availability of the resources managed by Cloud Service Provider (CSP). The emergence of the Internet of Things (IoT) and Cyber-Physical Cloud Systems (CPCS) where the data is processed and stored in the cloud environment, demands the need to tighten up the security of the cloud itself. Identifying and tracing the source of a cyber-attack plays an integral role in the investigation process. Digital forensics in the cloud termed Cloud Forensics which boosts the confidence of the stack holders by reconstructing the past cloud events to give a hypothetical view of the crime scene and describe how the malicious activity had happened? The collection of evidence especially in the cloud environment is the most complex task due to its scattered architecture. Moreover, the collected evidence was used for the investigation to shield the cloud environment from a future security breach and bring the cybercriminal to the court of justice. In this paper, we have presented an analysis of cloud forensics techniques and their practical challenges/limitations to cope with cloud forensic investigators.

关键词： Cloud computing Digital forensics Tools Security Object recognition distributed databases Computer architecture

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4th international conference on Advanced computing, networking and Informatics, ICACNI 2016

4th International Conference on Advanced Computing, Networki...

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4th international conference on Advanced computing, networking and Informatics, ICACNI 2016

ISBN: (纸本)9789811033759

The proceedings contain 61 papers. The special focus in this conference is on Advanced computing, networking and Informatics. The topics include: A browser-based distributed framework for content sharing and student collaboration;seed point selection algorithm in clustering of image data;comparative analysis of AHP and its integrated techniques applied for stock index ranking;a proposed what-why-how (WWH) learning model for students and strengthening learning skills through computational thinking;band power tuning of primary motor cortex EEG for continuous bimanual movements;probabilistically generated ternary quasigroup based stream cipher;dynamic access control in a hierarchy with constant key derivation cost;an efficient LWE-based additively homomorphic encryption with shorter public keys;understanding perception of cache-based side-channel attack on cloud environment;an enhanced remote user authentication scheme for multi-server environment using smartcard;a proposed bucket based feature selection technique (BBFST) for phishing e-mail classification;a novel security mechanism in symmetric cryptography using MRGA;techniques for enhancing the security of fuzzy vault: A review;an efficient vector quantization based watermarking method for image integrity authentication;xSS attack prevention using DOM-based filter;friendship recommendation system using topological structure of social networks;personalized recommendation approach for academic literature using high-utility itemset mining technique;an estimation of user preferences for search engine results and its usage patterns;a comparative analysis of various spam classifications;a semantic approach to classifying Twitter users;review spam detection using opinion mining;review spam detection using semi-supervised technique;dimensionality reduction using decision-based framework for classification: Sky and ground;comparative analysis of adaptive beamforming techniques.

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A simple 2(1-1/l) factor distributed approximation algorithm for Steiner tree in the CONGEST model 19

A simple 2(1-1/l) factor distributed approximation algorithm...

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20th international conference on distributed computing and networking (ICDCN)

作者： Saikia, Parikshit Karmakar, Sushanta Indian Inst Technol Guwahati Dept Comp Sci & Engn Gauhati 781039 India

ISBN: (纸本)9781450360944

The Steiner tree problem is a classical and fundamental problem in combinatorial optimization. The best known deterministic distributed algorithm for the Steiner tree problem in the CONGEST model was proposed by Lenzen and Patt-Shamir [25] that constructs a Steiner tree whose cost is optimal upto a factor of 2 and the round complexity is (O) over tilde (S + root min{St, n}) for a graph of n nodes and t terminals, where S is the shortest path diameter of the graph. Note here that the (O) over tilde(center dot) notation hides polylogarithmic factors in n. In this paper we present a simple deterministic distributed algorithm for constructing a Steiner tree in the CONGEST model with an approximation factor 2(1 - 1/l) of the optimal where l is the number of terminal leaf nodes in the optimal Steiner tree. The round complexity of our algorithm is O(S + root n log* n) and the message complexity is O(Delta(n - t)S + n(3/2)), where. is the maximum degree of a vertex in the graph. Our algorithm is based on the computation of a sub-graph called the shortest path forest for which we present a separate deterministic distributed algorithm with round and message complexities of O(S) and O(Delta(n - t)S) respectively.

关键词： Steiner tree shortest path forest distributed approximation algorithm

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Automatic Rumour Detection Model on Social Media

Automatic Rumour Detection Model on Social Media

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international conference on Parallel distributed and Grid computing (PDGC)

作者： Monika Bharti Himanshu Jindal Computer Science Engineering and Information Technology Jaypee University of Information Technology Waknaghat Solan

ISBN: (数字)9781728171326

ISBN: (纸本)9781728171333

Social networking site Twitter, in particular, has become a popular spot for gossip. Rumors or false news spread very easily through the Twitter network by re-tweeting users without understanding the real truth. These reports trigger popular confusion, threaten the authority of the government and pose a major threat to social order. It is also a very necessary job to dispel theories as quickly as possible. In this research, multiple descriptive and consumer-based features via tweets are retrieved and integrated these features with the TF-IDF system to develop a composite set of features. This composite set of features is then used by several machine learning techniques like Support Vector Machine (SVM), Linear regression, K-Nearest Neighbor (KNN), Naive Bayes, Decision Tree, Random Forest, and Gradient Boosting. Along with these machine learning classification models, a Convolutional Neural Network (CNN) algorithm is proposed to distinguish rumour and non-rumor tweets. The proposed model is evaluated with freely accessible twitter datasets. The existing machine-based learning models have acquired an Fl-score of 0.46 to 0.76 for rumour detection, while the CNN model attained an Fl-score of 0.77 for rumour class. Overall, the CNN model yields greater results with a weighted average Fl-score of 0.84 for both rumour and non-rumor categories. The potential mechanism will help to detect misinformation as quickly as possible to counteract the dissemination of rumours and build users' deep confidence in social media sites.

关键词： Social networking (online) Machine learning Blogs Feature extraction Support vector machines Information technology Handheld computers

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Unsplittable flow Edge Load factor Balancing in SDN using P4 Runtime 29

Unsplittable flow Edge Load factor Balancing in SDN using P4...

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29th international Telecommunication Networks and Applications conference (ITNAC)

作者： Kawaguchi, Eiichiro Kasuga, Hikaru Shinomiya, Norihiko Soka Univ Grad Sch Engn Tokyo Japan

ISBN: (数字)9781728136738

ISBN: (纸本)9781728136738

The spread of services and applications using cloud computing has led to an increase in the amount of network traffic. Therefore, traffic control methods using an SDN architecture for flexibly managing a network have been studied. Previous studies have proposed a traffic load balancing method by a single SDN controller. However, implementation with multiple SDN controllers has been considered to cope with scalability and redundancy. This paper model the distributed network as a flow network and defines the ratio of flow to capacity in an edge as a load factor. Besides, this study proposes a traffic load balancing method considering Unsplittable flow Edge Load factor Balancing problem and implements it to confirm its feasibility in a real network.

关键词： Software Defined networking (SDN) traffic engineering linear programming P4

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Load balancing and resource management in distributed B5G networks

Load balancing and resource management in distributed B5G ne...

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international conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Lu Ma Weiling Chang Chao Li Shanjin Ni Jia Cui Ming Liu National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing P.R.China

ISBN: (数字)9781728199160

ISBN: (纸本)9781728192369

The traffic explosion and the rising of diverse requirements lead to many challenges for the mobile networks on flexibility, scalability, and deployability. To meet the challenges, end-to-end network slicing and mobile edge computing (MEC) are introduced into beyond fifth-generation (B5G) mobile communication networks. However, the edge servers are limited by computing and data processing capabilities, how to implement efficient load balancing and resource management in data center are still challenges for B5G network slices. In this paper, we first propose a model of load balancing for B5G network slices and formulate a total cost minimization problem, considering the energy cost, processing delay, backhaul bandwidth cost, and revenue loss associated with the backhaul delay. Then, a distributed algorithm based on Proximal Jacobian Alternating Direction Method of Multipliers (PJ-ADMM) is proposed to solve the formulated problem. Simulations are conducted to show that the proposed algorithm are effective in terms of reducing network operating cost.

关键词： Bandwidth Load management Minimization Delays Resource management distributed algorithms Load modeling

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Memory Abstraction and Optimization for distributed Executors

Memory Abstraction and Optimization for Distributed Executor...

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international conference on Collaborative computing: networking, Applications and Worksharing (CollaborateCom)

作者： Semih Sahin Ling Liu Wenqi Cao Qi Zhang Juhyun Bae Yanzhao Wu Georgia Institute of Technology

ISBN: (数字)9781728141466

ISBN: (纸本)9781728185422

This paper presents a suite of memory abstraction and optimization techniques for distributed executors, with the focus on showing the performance optimization opportunities for Spark executors, which are known to outperform Hadoop MapReduce executors by leveraging Resilient distributed Datasets (RDDs), a fundamental core of Spark. This paper makes three original contributions. First, we show that applications on Spark experience large performance deterioration, when RDD is too large to fit in memory, causing unbalanced memory utilizations and premature spilling. Second, we develop a suite of techniques to guide the configuration of RDDs in Spark executors, aiming to optimize the performance of iterative ML workloads on Spark executors when their allocated memory is sufficient for RDD caching. Third, we design DAHI, a light-weight RDD optimizer. DAHI provides three enhancements to Spark: (i) using elastic executors, instead of fixed size JVM executors; (ii) supporting coarser grained tasks and large size RDDs by enabling partial RDD caching; and (iii) automatically leveraging remote memory for secondary RDD caching in the shortage of primary RDD caching on a local node. Extensive experiments on machine learning and graph processing benchmarks show that with DAHI, the performance of ML workloads and applications on Spark improves by up to 12.4x.

关键词： Sparks Task analysis Memory management Optimization Proposals Writing Virtual machining

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Massive Parallelization for Finding Shortest Lattice Vectors Based on Ubiquity Generator Framework 20

Massive Parallelization for Finding Shortest Lattice Vectors...

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Supercomputing conference

作者： Nariaki Tateiwa Yuji Shinano Satoshi Nakamura Akihiro Yoshida Shizuo Kaji Masaya Yasuda Katsuki Fujisawa Graduate School of Mathematics Kyushu University Fukuoka Japan Mathematical Algorithmic Intelligence Applied Algorithmic Intelligence Methods (A-IM) Zuse Institute Berlin (ZIB) Berlin Germany NTT Secure Platform Laboratories Tokyo Japan Institute of Mathematics for Industry Kyushu University Fukuoka Japan Rikkyo University Tokyo Japan

ISBN: (数字)9781728199986

ISBN: (纸本)9781728199993

Lattice-based cryptography has received attention as a next-generation encryption technique, because it is believed to be secure against attacks by classical and quantum computers. Its essential security depends on the hardness of solving the shortest vector problem (SVP). In the cryptography, to determine security levels, it is becoming significantly more important to estimate the hardness of the SVP by high-performance computing. In this study, we develop the world's first distributed and asynchronous parallel SVP solver, the MAssively Parallel solver for SVP (MAP-SVP). It can parallelize algorithms for solving the SVP by applying the Ubiquity Generator framework, which is a generic framework for branch-and-bound algorithms. The MAP-SVP is suitable for massive-scale parallelization, owing to its small memory footprint, low communication overhead, and rapid checkpoint and restart mechanisms. We demonstrate its performance and scalability of the MAP-SVP by using up to 100,032 cores to solve instances of the Darmstadt SVP Challenge.

关键词： Quantum computing Scalability High performance computing Lattices Generators Encryption Next generation networking

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Election Result Prediction Using Twitter Sentiments Analysis

Election Result Prediction Using Twitter Sentiments Analysis

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international conference on Parallel distributed and Grid computing (PDGC)

作者： Payal Khurana Batra Aditi Saxena Shruti Chaitanya Goel Jaypee Institute of Information Technology Noida India

ISBN: (数字)9781728171326

ISBN: (纸本)9781728171333

Democracy is the form of government where people have the right to choose their leaders. In our country, India, elections are held periodically to choose their political leader. Nowadays, people like to know beforehand that who is going to win the elections. They predict results based on news, their discussions and online platforms. Online sites such as Facebook, Twitter and WhatsApp have become a trend these days. Anyone with internet connection has access to these social sites. The views, news and discussions available on these platforms help in predicting the results beforehand. These are the platforms to share ones views' on an online junction. Twitter is one such platform which becomes popular during any event in our country. Anything that is news becomes a trend on twitter. People share their views, hatred, campaigns towards any political party, figure or leader. It is very useful to predict electoral results before the exit poll results. Therefore, this work analyzes tweets collected from twitter and predicts election results by performing sentimental analysis on them.

关键词： Voting Social networking (online) Blogs Decision trees Machine learning Feature extraction Predictive models

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