{"id":12,"date":"2015-01-22T12:45:18","date_gmt":"2015-01-22T17:45:18","guid":{"rendered":"http:\/\/localhost\/wordpress\/?page_id=12"},"modified":"2021-03-17T11:31:14","modified_gmt":"2021-03-17T15:31:14","slug":"research","status":"publish","type":"page","link":"https:\/\/www.csit.carleton.ca\/wshi\/?page_id=12","title":{"rendered":"Research Projects"},"content":{"rendered":"<h1>&#8211; M-MIMO Channel Estimation using Distributed Machine Learning and Edge Computing Technologies<\/h1>\n<h4>Supported by Ericsson and OCE-VIP<\/h4>\n<h4><a href=\"https:\/\/hubforgood.carleton.ca\/ericsson\/m-mimo-channel-estimation-using-distributed-machine-learning-and-edge-computing-technologies\/\">Project description<\/a><\/h4>\n<h1>&#8211; Spectrum Sharing with Machine Learning<\/h1>\n<h4>Supported by Ericsson<\/h4>\n<h4><a href=\"https:\/\/hubforgood.carleton.ca\/ericsson\/spectrum-sharing-with-machine-learning\/\">Project description<\/a><\/h4>\n<h1>&#8211; Contact Tracing System (Covid-19 Quarantine\/Test Notification System)<\/h1>\n<h4>Supported by NSERC Alliances Covid-19 Grant and CU Covid-19 Rapid Response Research Grant<\/h4>\n<h3 style=\"text-align: left;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/covidcts.carleton.ca\/\">Our System Website<\/a><\/span><\/h3>\n<h3 style=\"text-align: left;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/newsroom.carleton.ca\/story\/covid-19-exposure-alerts-app\/?utm_source=Homepage&amp;utm_medium=Banner\">Article about our system on Carleton Webpage<\/a><\/span><\/h3>\n<h1>&#8211; Cyber Security in Critical Infrastructures<\/h1>\n<h2>Supported by NSERC Discovery Grant<\/h2>\n<h4>A distributed system is a system whose components are located on different networked entities (e.g.,<br \/>\ncomputers, sensors) that communicate and coordinate their actions by exchanging messages. These<br \/>\nentities have a shared state, operate concurrently and can fail independently without affecting the whole<br \/>\nsystem&#8217;s uptime. With the ever-growing technological expansion of the world, distributed systems are<br \/>\nbecoming more and more widespread.<\/h4>\n<h4>In past years, I have addressed the protection and resilience of distributed systems such as Clouds, Data<br \/>\nCentres, Mobile Agent and Actuator Networks, Vehicular and Wireless Sensor Networks. Building on this<br \/>\nexpertise, in the medium term, I plan to address various cyber security issues and develop attack resilient<br \/>\nsolutions for a very important type of distributed systems, namely the industrial automated control<br \/>\nsystems and networks that are monitoring and controlling the operation of critical infrastructures in<br \/>\ndifferent sectors. These include the Energy sector (e.g., oil pipelines, nuclear plants), the Financial sector,<br \/>\nGovernment Operations, Water Supply, Health Systems and more. Cyberattacks against critical<br \/>\ninfrastructures have increased significantly in the last decade and caused serious damage with very<br \/>\nimportant social and economic losses. However, research on protecting the control systems of critical<br \/>\ninfrastructures against cyberattacks is still at an early stage and faces many open technical challenges.<\/h4>\n<h1>&#8211; Distributed Computing<\/h1>\n<h2>Supported by NSERC Discovery Grant<\/h2>\n<h3>A. Secure Localization<br \/>\nB. Sensor Deployment in Complex Region of Interest<br \/>\nC. Security Threats in Clouds: Black Hole Search and Intrusion Detection using Mobile Agents<\/h3>\n<h1>&#8211; Big Data Analytics<\/h1>\n<h2>Supported by NSERC Discovery Grant<\/h2>\n<h3>A. Big Data Analytics<\/h3>\n<h4>Big data analytics is the process of examining (i.e., data mining) large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. There are two types of big data: data at rest (e.g., collection of what has streamed, web logs, emails, social media, unstructured documents and structured data from disparate system) and data in motion (e.g., twitter\/facebook comments, stock market data and sensor data). Dealing effectively with big data despite its volume and variety requires efficient analysis of this data while it is still in motion, not just after it is at rest. Currently, there are essentially three approaches for Big Data Analytics: direct analytics over Massively Parallel Processing Data Warehouses, indirect analytics using Hadoop and direct analytics using Hadoop (which is a framework widely used in academia and industry in order to perform Big Data Analytics). With respect to Big Data Analytics, I am involved in the following projects:<\/h4>\n<h4>a. Multiplayer Online Game Players&#8217; Movement Prediction: an Effective Solution for Minimizing the Consequences of Poor Internet Quality<\/h4>\n<h4>b. Social Network-based Data Dissemination in Vehicular Networks<\/h4>\n<h3>B. Big Data Infrastructure<\/h3>\n<h4>Work Distribution, Service Migration and Replica Placement algorithms and their simulations for MapReduce in the context of the Hadoop framework.<\/h4>\n<h3>C. Big Data Applications: Information Security Issues Pertaining to Big Data in Healthcare<\/h3>\n<h4>a. A Patient-Oriented Computer-Aided Approach to Improve Chronic Disease Care for Children<br \/>\nb. A Privacy-Protective Method for the Disclosure of Small Geographic Areas in Health Research<\/h4>\n<h1>&#8211; Software Engineering<\/h1>\n<h3>A. Reverse-Engineering Tests into Blueprint Requirements<br \/>\nB. Support for Non-Functional Requirements in Zeligsoft tools<br \/>\nC. Model-Based Acceptance Testing<\/h3>\n","protected":false},"excerpt":{"rendered":"<p>&#8211; M-MIMO Channel Estimation using Distributed Machine Learning and Edge Computing Technologies Supported by Ericsson and OCE-VIP Project description &#8211; Spectrum Sharing with Machine Learning Supported by Ericsson Project description &#8211; Contact Tracing System (Covid-19 Quarantine\/Test Notification System) Supported by NSERC Alliances Covid-19 Grant and CU Covid-19 Rapid Response Research Grant Our System Website Article<\/p>\n<p><a href=\"https:\/\/www.csit.carleton.ca\/wshi\/?page_id=12\" class=\"more-link themebutton\">Read More<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/pages\/12"}],"collection":[{"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=12"}],"version-history":[{"count":29,"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/pages\/12\/revisions"}],"predecessor-version":[{"id":1068,"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=\/wp\/v2\/pages\/12\/revisions\/1068"}],"wp:attachment":[{"href":"https:\/\/www.csit.carleton.ca\/wshi\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}