A Distributed Architecture for Remote Service Discovery in Pervasive Computing
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Pervasive Computing Service Discovery in Secure Framework Environment
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 10 | Oct 2018 www.irjet.net p-ISSN: 2395-0072 PERVASIVE COMPUTING SERVICE DISCOVERY IN SECURE FRAMEWORK ENVIRONMENT Mrs. Sweta Singh, Mr. Alok Katiyar, Mr. Amit kumar Singh 1Asst. Professor (M.Tech), Department of Computer Science, JIT Barabanki, Lucknow, UP, India, 225203 2Asst. Professor (M.Tech), Department of Computer Science, Inderprastha Engineering College, Ghaziabad, UP, India, 201010 3Asst. Professor (M.Tech), Department of Computer Science, BBDUniversity, Lucknow ---------------------------------------------------------------------***-------------------------------------------------------------------- Abstract - Pervasive systems must offer an open, extensible, and evolving portfolio of services which integrate sensor data from a diverse range of sources. The core challenge is to provide appropriate and consistent adaptive behaviors for these services in the face of huge volumes of sensor data exhibiting varying degrees of precision, accuracy and dynamism. Situation identification is an enabling technology that resolves noisy sensor data and abstracts it into higher-level concepts that are interesting to applications. We provide a comprehensive analysis of the nature and characteristics of situations, discuss the complexities of situation identification, and review the techniques that are most popularly used in modeling and inferring situations from sensor data. We compare and contrast these techniques, and conclude by identifying some of the open research opportunities in the area. Introduction Pervasive computing means the technology that is gracefully integrated in our everyday life. The user is no longer aware of this embedded technology. Pervasive computing uses web technology, portable devices, wireless communications and nomadic or ubiquitous computing systems. Other terms for pervasive computing are Ubiquitous Computing, Calm Technology, and Things That Think. -
Cisco Firepower Application Detector Reference - VDB 342
Cisco Firepower Application Detector Reference - VDB 342 First Published: 2021-03-30 Americas Headquarters Cisco Systems, Inc. 170 West Tasman Drive San Jose, CA 95134-1706 USA http://www.cisco.com Tel: 408 526-4000 800 553-NETS (6387) Fax: 408 527-0883 THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. The Cisco implementation of TCP header compression is an adaptation of a program developed by the University of California, Berkeley (UCB) as part of UCB's public domain version of the UNIX operating system. All rights reserved. Copyright © 1981, Regents of the University of California. NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS" WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE. IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. -
HANDY: a Hybrid Association Rules Mining Approach for Network Layer Discovery of Services for Mobile Ad Hoc Network
HANDY: A Hybrid Association Rules Mining Approach for Network Layer Discovery of Services for Mobile Ad hoc Network Noman Islam, Zubair A. Shaikh, Aqeel-ur-Rehman, Muhammad Shahab Siddiqui Noman Islam (Corresponding Author) National University of Computer and Emerging Sciences, Karachi, Pakistan Email: [email protected] Zubair A. Shaikh National University of Computer and Emerging Sciences, Karachi, Pakistan Aqeel-ur-Rehman Hamdard University, Karachi, Pakistan Muhammad Shahab Siddiqui Hamdard University, Karachi, Pakistan Abstract Mobile Ad hoc Network (MANET) is an infrastructure-less network formed between a set of mobile nodes. The discovery of services in MANET is a challenging job due to the unique properties of network. In this paper, a novel service discovery framework called Hybrid Association Rules Based Network Layer Discovery of Services for Ad hoc Networks (HANDY) has been proposed. HANDY provides three major research contributions. At first, it adopts a cross-layer optimized design for discovery of services that is based on simultaneous discovery of services and corresponding routes. Secondly, it provides a multi-level ontology-based approach to describe the services. This resolves the issue of semantic interoperability among the service consumers in a scalable fashion. Finally, to further optimize the performance of the discovery process, HANDY recommends exploiting the inherent associations present among the services. These associations are used in two ways. First, periodic service advertisements are performed based on these associations. In addition, when a response of a service discovery request is generated, correlated services are also attached with the response. The proposed service discovery scheme has been implemented in JIST/SWANS simulator. -
Dirpl: a RPL-Based Resource and Service Discovery Algorithm for 6Lowpans
applied sciences Article DiRPL: A RPL-Based Resource and Service Discovery Algorithm for 6LoWPANs Luca Davoli 1,† , Mattia Antonini 2,3,†,‡ and Gianluigi Ferrari 1,*,† 1 Internet of Things (IoT) Lab, Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; [email protected] 2 OpenIoT Research Unit, FBK CREATE-NET, 38123 Povo, Italy; [email protected] 3 Department of Information Engineering and Computer Science, University of Trento, 38123 Povo, Italy * Correspondence: [email protected]; Tel.: +39-0521-906513 † These authors contributed equally to this work. ‡ M. Antonini was with the Internet of Things (IoT) Lab, Department of Engineering and Architecture, University of Parma, Italy, at the time of writing. Received: 26 October 2018; Accepted: 20 December 2018; Published: 22 December 2018 Featured Application: The proposed Resource Discovery (RD) and Service Discovery (SD) mechanism, denoted as DiRPL, is applicable to real deployments, where the tree-like network topology built by the IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) adaptation layer can be effective in guaranteeing reliable data collection through effective RD/SD (e.g., smart street lighting and water consumption monitoring in smart city scenarios). Smart city scenarios are typically characterized by: (i) large coverage areas; (ii) distributed sensing; and (iii) the need for human intervention in the presence of a fault. In this context, the proposed approach is very attractive as faulty devices can be automatically excluded from the network (which self-organizes) and newly installed IoT devices can be automatically self-discovered by the network itself. Abstract: The Internet of Things (IoT) will bring together billions of devices, denoted as Smart Objects (SOs), in an Internet-like architecture.