Emerging Technologies for Developing Countries

Data transfer using wireless sensor networks (WSN) is bound by its limited coverage range. In order to communicate data beyond the coverage capa‐ bility of a WSN link and make it pervasive, the authors here propose a method of information handover using heterogeneous wireless links for sensor-based data transmission. They draw on connectivity, one of the main features of a pervasive network. In the handover method proposed here, the WSN link is part of a wireless module which integrates various heterogeneous wireless links. All these wireless links are combined and coordinated using media independent handover functions (MIH) in accordance with the 802.21 Standard. As wireless modules have multiple wireless links, each module can communicate with the others using any one of the active links. When these wireless modules consisting of multiple links move beyond the communication range of the WSN link to maintain continuous connectivity the MIH in the module triggers the other wireless links to hand over the service with the help of access points in the surrounding area. The concept is discussed here in the context of a smart home application which transfers the sensed information continuously to a remotely located controlling station using the existing wireless infrastructure.

[1]  David A. Freedman,et al.  Statistical Models: Theory and Practice: References , 2005 .

[2]  Parthasarathy Ranganathan,et al.  Energy Efficiency: The New Holy Grail of Data Management Systems Research , 2009, CIDR.

[3]  Luigi Atzori,et al.  Trustworthiness Management in the Social Internet of Things , 2014, IEEE Transactions on Knowledge and Data Engineering.

[4]  Ananthram Swami,et al.  LogitTrust : A Logit Regression-based Trust Model for Mobile Ad Hoc Networks , 2014 .

[5]  M C Rodriguez-Sanchez,et al.  Wireless Sensor Networks for Conservation and Monitoring Cultural Assets , 2011, IEEE Sensors Journal.

[6]  Colin Atkinson,et al.  The MORABIT Approach to Runtime Component Testing , 2006, 30th Annual International Computer Software and Applications Conference (COMPSAC'06).

[7]  Martin Kardos,et al.  Model-based Runtime Verification Framework for Self-optimizing Systems , 2006, RV@CAV.

[8]  Kunal Verma,et al.  Dynamic Web Service Composition in METEOR-S , 2004 .

[9]  Gustavo Pinto,et al.  Data-Oriented Characterization of Application-Level Energy Optimization , 2015, FASE.

[10]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[11]  Colin Atkinson,et al.  Strategies for the Run-Time Testing of Third Party Web Services , 2007, IEEE International Conference on Service-Oriented Computing and Applications (SOCA '07).

[12]  Beng Chin Ooi,et al.  The Claremont report on database research , 2008, SGMD.

[13]  Syed Akhter Hossain,et al.  NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison , 2013, ArXiv.

[14]  Fabio Casati,et al.  An open, flexible, and configurable system for service composition , 2000, Proceedings Second International Workshop on Advanced Issues of E-Commerce and Web-Based Information Systems. WECWIS 2000.

[15]  Amrit Tiwana,et al.  E-services: problems, opportunities, and digital platforms , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[16]  Mahesh Viswanathan,et al.  Foundations for the run-time analysis of software systems , 2000 .

[17]  Paulo F. Pires,et al.  Building Reliable Web Services Compositions , 2002, Web, Web-Services, and Database Systems.

[18]  Paolo Falcarin,et al.  Automated context aware composition of Advanced Telecom Services for environmental early warnings , 2014, Expert Syst. Appl..

[19]  Jignesh M. Patel,et al.  Rethinking Query Processing for Energy Efficiency: Slowing Down to Win the Race , 2011, IEEE Data Eng. Bull..

[20]  Jayant R. Haritsa,et al.  Peak power plays in database engines , 2012, EDBT '12.

[21]  Jignesh M. Patel,et al.  Towards Eco-friendly Database Management Systems , 2009, CIDR.

[22]  Junho Jeong,et al.  Cyber Physical Systems for User Reliability Measurements in a Sharing Economy Environment , 2017, Sensors.

[23]  Noël Crespi,et al.  Context-aware service composition framework in web-enabled building automation system , 2012, 2012 16th International Conference on Intelligence in Next Generation Networks.

[24]  Xiaoqing Frank Liu,et al.  Cyber-physical manufacturing cloud: Architecture, virtualization, communication, and testbed , 2017 .

[25]  Mohamed Jmaiel,et al.  Safe and efficient runtime testing framework applied in dynamic and distributed systems , 2016, Sci. Comput. Program..

[26]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[27]  Marten van Sinderen,et al.  Supporting Dynamic Service Composition at Runtime based on End-user Requirements , 2009 .

[28]  Paul Resnick,et al.  Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system , 2002, The Economics of the Internet and E-commerce.

[29]  Alwyn E. Goodloe,et al.  Monitoring Distributed Real-Time Systems: A Survey and Future Directions , 2010 .

[30]  Jia Guo,et al.  A Classification of Trust Computation Models for Service-Oriented Internet of Things Systems , 2015, 2015 IEEE International Conference on Services Computing.

[31]  Salim Hariri,et al.  Autonomic power and performance management for computing systems , 2006, 2006 IEEE International Conference on Autonomic Computing.

[32]  João Saraiva,et al.  Establishing Energy Consumption Plans for Green Star-Queries in Data Warehousing Systems , 2015, 2015 IEEE International Conference on Data Science and Data Intensive Systems.

[33]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[34]  Luís Ferreira Pires,et al.  A Framework for Dynamic Web Services Composition , 2007, WEWST.

[35]  Soundar R. T. Kumara,et al.  Effective Web Service Composition in Diverse and Large-Scale Service Networks , 2008, IEEE Transactions on Services Computing.

[36]  Kwangsoo Kim,et al.  Classification between Failed Nodes and Left Nodes in Mobile Asset Tracking Systems † , 2016, Sensors.

[37]  Yu Zhang,et al.  A Social Reputation Management for Web Communities , 2011, WAIM Workshops.

[38]  Boualem Benatallah,et al.  Web Service Composition , 2015 .

[39]  Frank Vahid,et al.  A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems , 2014, KSII Trans. Internet Inf. Syst..

[40]  Zhan Zhang,et al.  A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems , 2017, Sensors.

[41]  João Saraiva,et al.  Defining Energy Consumption Plans for Data Querying Processes , 2014, 2014 IEEE Fourth International Conference on Big Data and Cloud Computing.

[42]  Athanasios V. Vasilakos,et al.  Web services composition: A decade's overview , 2014, Inf. Sci..

[43]  Éric Piel,et al.  Architecture support for runtime integration and verification of component-based Systems of Systems , 2008, 2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops.

[44]  Abdelhakim Hafid,et al.  A QoS broker based architecture for efficient Web services selection , 2005, IEEE International Conference on Web Services (ICWS'05).

[45]  Paulo F. Pires,et al.  Webtransact: A Framework For Specifying And Coordinating Reliable Web Services Compositions , 2002 .