Effects of sustained communication time on reliability of JXTA-Overlay P2P platform: a comparison study for two fuzzy-based systems

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In P2P systems, each peer has to obtain information of other peers and propagate the information to other peers through neighboring peers. Thus, it is important for each peer to have some number of neighbor peers. Moreover, it is more significant to discuss if each peer has reliable neighbor peers. In reality, each peer might be faulty or might send obsolete, even incorrect information to the other peers. We have implemented a P2P platform called JXTA-Orverlay, which defines a set of protocols that standardize how different devices may communicate and collaborate among them. JXTA-Overlay provides a set of basic functionalities, primitives, intended to be as complete as possible to satisfy the needs of most JXTA-based applications. In this paper, we present two fuzzy-based systems (called FPRS1 and FPRS2) to improve the reliability of JXTA-Overlay P2P platform. We make a comparison study between the fuzzy-based reliability systems. Comparing the complexity of FPRS1 and FPRS2, the FPRS2 is more complex than FPRS1. However, it considers also the sustained communication time which makes the platform more reliable.Peer ReviewedPostprint (author's final draft

On sharing and synchronizing groupware calendars under android platform

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Sharing a calendar of tasks and events is a cornerstone in collaborative group work. Indeed, the individual work of the members of the group as well as the group work as a whole need the calendar to guide their activity and to meet the deadlines, milestones, deliverables of a project, etc. Additionally the members of the group should be able to work both offline and online, which arises when members of the group use smartphones and can eventually run out of Internet connection from time to time, or simply want to develop some activities locally. In the former case, they should have access to the calendar locally, while in the later case they should access the calendar online, shared by all members of the group. In both cases they should be able to see eventually the same information, namely the local calendars of the members should be synchronized with the group calendar. For the case of smartphones under Android system, one solution could be using the Google calendar, however, that is not easily tailorable to collaborative group work. In this paper we present an analysis, design and implementation of group work calendar that meets several requirements such as 1) sharing among all of members of the group, 2) synchronization among local calendars of members and global group calendar, 3) conflict resolution through a voting system, 4) awareness of changes in the entries (tasks, members, events, etc.) of the calendar and 5) all these requirements under proper privacy, confidentiality and security mechanisms. Moreover, we extend the sharing of calendars among different groups, a situation which often arises in enterprises when different groups need to be aware of other projects' development, or, when some members participate in more than one project at the same time.Peer ReviewedPostprint (author's final draft

Investigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.With the fast development of wireless technologies, Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure due to their low cost and increased high speed wireless Internet connectivity. In our previous work, we implemented a simulation system based on Particle Swam Optimization for solving node placement problem in wireless mesh networks, called WMN-PSO. In this paper, we use Size of Giant Component (SGC) and Number of Covered Mesh Clients (NCMC) as metrics for optimization. Then, we analyze effects of weight-coefficients for SGC and NCMC. From the simulation results, we found that the best values of the weight-coefficients for SGC and NCMC are 0.7 and 0.3, respectively.Peer ReviewedPostprint (author's final draft

A fuzzy-based approach for classifying students' emotional states in online collaborative work

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Emotion awareness is becoming a key aspect in collaborative work at academia, enterprises and organizations that use collaborative group work in their activity. Due to pervasiveness of ICT's, most of collaboration can be performed through communication media channels such as discussion forums, social networks, etc. The emotive state of the users while they carry out their activity such as collaborative learning at Universities or project work at enterprises and organizations influences very much their performance and can actually determine the final learning or project outcome. Therefore, monitoring the users' emotive states and using that information for providing feedback and scaffolding is crucial. To this end, automated analysis over data collected from communication channels is a useful source. In this paper, we propose an approach to process such collected data in order to classify and assess emotional states of involved users and provide them feedback accordingly to their emotive states. In order to achieve this, a fuzzy approach is used to build the emotive classification system, which is fed with data from ANEW dictionary, whose words are bound to emotional weights and these, in turn, are used to map Fuzzy sets in our proposal. The proposed fuzzy-based system has been evaluated using real data from collaborative learning courses in an academic context.Peer ReviewedPostprint (author's final draft

Object-based Information Flow Control in Peer-to-peer Publish/Subscribe Systems

Distributed systems are getting so scalable like IoT (Internet of Things) and P2P (Peer-to-Peer) systems that millions of devices are connected and support various types of applications. Here, distributed systems are required to be secure in addition to increasing the performance, reliability, and availability and reducing the energy consumption. In distributed systems, information in objects flows to other objects by transactions reading and writing data in the objects. Here, some information of an object may illegally flow to a subject which is not allowed to get the information of the object. Especially, a leakage of sensitive information is to be prevented from occurring. In order to keep information systems secure, illegal information flow among objects has to be prevented. Types of synchronization protocols are so far discussed based on read and write access rights in the RBAC (Role-Based Access Control) model to prevent illegal information flow.In this thesis, we newly propose a P2PPSO (P2P type of topic-based PS (Publish/Subscribe) with Object concept) model and discuss the models and protocols for information flow control. A P2PPSO model is composed of peer processes (peers) which communicate with one another by publishing and subscribing event messages. Each peer can both publish and receive event messages with no centralized coordinator compared with traditional centralized PS models. Each event message published by a source peer carries information to a target peer. The contents carried by an event message are considered to be composed of objects. An object is a unit of data resource. Objects are characterized by topics, and each event message is also characterized by topics named publication topics.In order to make a P2PPSO system secure, we first newly propose a TBAC (Topic-Based Access Control) model. Here, an access right is a pair ⟨t, op⟩ of a topic t and a publish or subscribe operation op. A peer is allowed to publish an event message with publication topics and subscribe interesting topics only if the publication and subscription access rights are granted to the peer, respectively. Suppose an event message e_j published by a peer p_j carries an object on some topics into a target peer p_i. Here, information in the peer p_j illegally flows to the peer p_i if the target peer p_i is not allowed to subscribe the topics. An illegal object is an object whose topics a target peer is not allowed to subscribe. Even if an event message is received by a target peer by checking topics, objects carried by the event message may be illegal at the target peer. Hence, first, we propose a TOBS (Topics-of-Objects-Based Synchronization) protocol to prevent target peers from being delivered illegal objects in the P2PPSO system. Here, even if an event message is received by a target peer, illegal objects in the event message are not delivered to the target peer.In the TOBS protocol, every event message is assumed to be causally delivered to every common target peer in the underlying network. Suppose an event message e_2 is delivered to a target peer p_i before another event message e_1 while the event message e_1 causally precedes the event message e_2 (e_1 →_c e_2). Here, the event message e_2 is premature at the peer p_i. Hence, secondly, we propose a TOBSCO (TOBS with Causally Ordering delivery) protocol where the function to causally deliver every pair of event messages is added to the TOBS protocol. Here, we assume the underlying network supports reliable communication among every pair of peers, i.e. no event message loss, no duplicate message, and the sending order delivery of messages. Every pair of event messages received by using topics are causally delivered to every common target peer by using the vector of sequence numbers.In the TOBS and TOBSCO protocols, objects delivered to target peers are held as replicas of the objects by the target peers. If a peer updates data of an object, the peer distributes event messages, i.e. update event messages, to update every replica of the object obtained by other peers. If a peer updates an object without changing topics, the object is referred to as altered. Here, an update event message for the altered object is meaningless since peers check only topics to exchange event messages. Hence, thirdly, we propose an ETOBSCO (Efficient TOBSCO) protocol where update event messages of objects are published only if topics of the objects are updated to reduce the network overhead.In the evaluation, first, we show how many numbers of event messages and objects are prevented from being delivered to target peers in the TOBS protocol. Next, we show every pair of event messages are causally delivered but it takes longer to deliver event messages in the TOBSCO protocol than the TOBS protocol. Finally, we show the fewer number of event messages are delivered while it takes longer to update replicas of altered objects in the ETOBSCO protocol than the TOBSCO protocol.博士(工学)法政大学 (Hosei University

サーバクラスタでの低消費電力化のための移行モデルの研究

博士(工学)法政大学 (Hosei University

The Use of MPI and OpenMP Technologies for Subsequence Similarity Search in Very Large Time Series on Computer Cluster System with Nodes Based on the Intel Xeon Phi Knights Landing Many-core Processor

Nowadays, subsequence similarity search is required in a wide range of time series mining applications: climate modeling, financial forecasts, medical research, etc. In most of these applications, the Dynamic TimeWarping (DTW) similarity measure is used since DTW is empirically confirmed as one of the best similarity measure for most subject domains. Since the DTW measure has a quadratic computational complexity w.r.t. the length of query subsequence, a number of parallel algorithms for various many-core architectures have been developed, namely FPGA, GPU, and Intel MIC. In this article, we propose a new parallel algorithm for subsequence similarity search in very large time series on computer cluster systems with nodes based on Intel Xeon Phi Knights Landing (KNL) many-core processors. Computations are parallelized on two levels as follows: through MPI at the level of all cluster nodes, and through OpenMP within one cluster node. The algorithm involves additional data structures and redundant computations, which make it possible to effectively use the capabilities of vector computations on Phi KNL. Experimental evaluation of the algorithm on real-world and synthetic datasets shows that it is highly scalable.Comment: Accepted for publication in the "Numerical Methods and Programming" journal (http://num-meth.srcc.msu.ru/english/, in Russian "Vychislitelnye Metody i Programmirovanie"), in Russia

A model for providing emotion awareness and feedback using fuzzy logic in online learning

Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.Peer ReviewedPostprint (author's final draft

Model-driven engineering techniques and tools for machine learning-enabled IoT applications: A scoping review

This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services.info:eu-repo/semantics/publishedVersio

Markerless motion capture for 3D human model animation using depth camera

3D animation is created using keyframe based system in 3D animation software such as Blender and Maya. Due to the long time interval and the need of high expertise in 3D animation, motion capture devices were used as an alternative and Microsoft Kinect v2 sensor is one of them. This research analyses the capabilities of the Kinect sensor in producing 3D human model animations using motion capture and keyframe based animation system in reference to a live motion performance. The quality, time interval and cost of both animation results were compared. The experimental result shows that motion capture system with Kinect sensor consumed less time (only 2.6%) and cost (30%) in the long run (10 minutes of animation) compare to keyframe-based system, but it produced lower quality animation. This was due to the lack of body detection accuracy when there is obstruction. Moreover, the sensor’s constant assumption that the performer’s body faces forward made it unreliable to be used for a wide variety of movements. Furthermore, standard test defined in this research covers most body parts’ movements to evaluate other motion capture system