Contributors:Nicola Mc Donnell, Enda Howley, Jim Duggan
This dataset covers five data components of interest developed during our research which is published in “Dynamic Virtual Machine Consolidation using a multi-agent system to optimise energy efficiency in Cloud Computing”. They are: a patch file, peersim-1.0.5-nmcd.patch, for PeerSim version 1.0.5; four zip files contains the source code for the Gossip Contracts framework, GossipContracts-src.zip, the DVMC models, DVMC-src.zip, the module to process the Google dataset, GoogleTraceData-src.zip, and some utility methods, Util-src.zip; and the experiment results files, ResearchData-Results.zip.
Contributors:Soroush Ojagh, Mohammad Reza Malek, Steve Liang, Sara Saeedi
In this study, 20 recommendation lists are provided for each of 7,214 user's locations in total. Four different buffer sizes (two, five, ten, and 15 km) and four UPDs are considered for each user's location to prepare the event recommendation lists. In the implemented scenario, three different scenarios were applied in order to support research claims. The word "SC" refers to a specific scenario as "SC_1" refers to the first scenario. Totally, considering four circle buffers and four UPDs in each buffer, 16 buffer lines will be prepared as "sc_1_line_1" refers to the first UPD in the buffer size of two kilometers. In addition, "sc_1_cycle" refers to all the event venues that are located in the circle buffer size of two kilometers. "EventVenues" and "venuesMBBs" contain geospatial information for the selected venues and also their extracted minimum bounding boxes.
All the imported building located in the city of Calgary, Alberta is in the "calgaryBuilding" table, and "userLocations" shows the spatial information considered for the 7,214 user's locations.
Contributors:Seyedhamid Mashhadi Moghaddam, Cameron Walker, Sareh Fotuhi Piraghaj, Charles Unsworth
The cross validation results for the prediction models.
This is a network capture of the WannaCry ransomware trying to exploit the SMBv1 vulnerability on port 445 using the Eternal Blue exploit.
Contributors:Zhifang Pan, Jiuqiang Chen, King Xinyuan, Yezhi Lin
The main interface of Python package AdomianPy is asolve(eq, ics, kwargs), where the parameter $eq$ can be any supported ordinary or partial differential equations, ics is the set of boundary conditions for the differential equations. kwargs is optional, depending on the sophistication of our physical model. The kwargs includes func=None, n=5 type=4 and core=1,
where func is a function of variables whose derivatives in that variables make up the ordinary or partial differential equations, n represents the required highest order of the truncated series solutions, type is the class number of the Adomian polynomials, core is the number of processors used for computation, and their default value is None, 5 ,4, 1 respectively.
In Appendix A, we will describe the details about how-to-use of AdomianPy.
Contributors:Ralph Koning, Paola Grosso, Gleb Polevoy, Ben de Graaff, Cees de Laat, Robert Meijer
Dataset containing network measurements of certain metrics and observables during various attack/defense scenarios executed on a SARNET overlay network.
Each of the experiments is executed 50x using different parameters of the system.
The accompanied notebook, produces the figures included in the article.
For more detailed information is provided in the article.