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Successful defense of Masters theses

CFP: Journal of Software: Practice and Engineering (SPE): Special Issue on Big Data and Cloud of Things (CoT)

Journal of Software: Practice and Engineering (SPE): Special Issue on Big Data and Cloud of Things (CoT)

Guest Editors: Rajiv Ranjan, Lizhe Wang, Prem Prakash Jayaraman, Karan Mitra, Dimitrios Georgakopoulos

Edited by: Rajkumar Buyya and R. Nigel Horspool

Cloud computing and Internet of Things (IoT) are two technologies that are already becoming part of our daily lives and are attracting significant interest from both industry and academia. The Cloud of Things (CoT) is a vision inspired from the IoT paradigm where everyday devices namely “smart objects” are fully connected to the network and integrated with the cloud. It is expected, the IoT will grow to 35 billion units by 2020 making them one of the main sources of  “Big Data” with characteristics such as volume, heterogeneity, complexity, velocity and value. Specific attention must be paid to address the issues such as data collection, storage, processing, analytics on demand and automatic provision and management of cloud resources to support the growing population of things. In recent years, CoT has given rise to a number of new cloud paradigms (but not limited to) including: Sensing-as-a-Service, Sensing- and Actuation-as-a-Service, Video-Surveillance-as-a-Service, Big Data Analytics-as-a-Service, Data-as-a-Service, Sensor-as-a-Service and Sensor-Event-as-a-Service. Cloud computing is a more mature technology compared to IoT. It can offer virtually unrestricted capabilities (e.g. storage and processing) to implement IoT services and application that can exploit the data produced by IoT. The cloud essentially acts as a transparent layer between the IoT and applications providing flexibility, scalability and hiding the complexities between the two layers (IoT and applications). However, the integration of cloud and IoT into Cloud of Things impose several challenges such as service discovery and delivery, big data management and analytics, cloud monitoring and orchestration, mobility issues in cloud access, privacy and security and SLA management for both cloud and IoT.

Topics of interest include (but not limited to):

  • CoT Architectures and models
  • CoT and Big Data Analytics
  • Smart resource provisioning for CoT
  • CoT applications • CoT Digital ecosystems
  • Data Management in CoT
  • Mobile CoT
  • Middleware for CoT
  • Networking issues in CoT
  • Software and tools for CoT
  • Monitoring CoT resources
  • SLA management in CoT
  • Privacy and Security in CoT
  • QoS in CoT
  • CoT in Healthcare

Schedule Submission due date:

  • September 30th, 2015
  • Notification of acceptance: December 30th, 2015
  • Submission of final manuscript: Jan 30th, 2015
  • Publication date: 1st Quarter, 2016 (Tentative)

CFP can be downloaded  from here.

Solving problem with CISCO VPN client

Follow this link –

Discretization of MOS based on the Table B.1/G.107 – Provisional guide for the relation between R-value and user satisfaction

=IF(“cellval”<2.58,1,IF(“cellval”<3.1,2,IF(“cellval”<3.6,3,IF(“cellval”<4.03,4,IF(“cellval”>4.34,5))))). Replace “cellval” with MOS ratings obtained using the ITU-T G.107 recommendation (2009 tested).

Commands for pjsua

Machine 1: ./pjsua-x86_64-unknown-linux-gnu –play-file female.wav –auto-play –auto-answer 200 –duration=15
Machine 2: ./pjsua-i686-pc-linux-gnu –auto-rec –rec-file=bharat.wav

Tools to convert a BN from GeNIe to BNT

I tested the Bayesian Networks Format Converter today with my test Bayesian network which was created using GeNIe. It only seems to work with BN saved  as a .net extension. Once the .bif file is converted, I used the BIF-BNT converter to convert it to the BNT format. It doesn’t work out of the box. So, I had to make sure that I follow the same format shown as an example (Sprinkler BN) in the text box. Once it is done, it will output the BN in BNT format.