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Recent trends have shown a migration of software from local machines to server-based services. These servicebased networks depend on high up-times and heavy resistance in order to compete in the market. Along with this growth, denial of service attacks have equally grown. Defending against these attacks has become increasingly difficult with the growth of Internet of Things and the different varieties of denial of service attacks. For this, our research offers a solution of implementing software-defined networking and real-time metric based techniques to mitigate a denial of service attack within a smaller time window than other comparable solutions. The use of our method offers both efficient attack handling and also flexibility to fit a variety of implementations. The end result being a network that can automatically adapt against new attacks based on previous network activity.

This paper reports the development of a computer-controlled machine for non-contact inspection of manufactured parts The machine, called PAMM (Precision Automatic Measuring Machine), is capable of providing "on-the-fly" measurements accurate to within 100 microinches. The intersection of a rotating spiral slot with a stationary linear slot produces a moving aperture for scanning in small increments over a projected, enlarged image of a part. The scanner assembly moves along an overhead cantilever beam in the x direction, and the part being inspected moves in the y direction along the machine base; position in each direction is monitored by a separate laser interferometer.In the paper conventional methods of coordinate measuring are briefly reviewed, the details of the new design are presented, some experimentally obtained measurements are given, measurement errors induced by photodetector shot noise and aperture roughness are analyzed, and the computer-control and data-analysis techniques are discussed.

The importance of reliable and adaptable networks has become increasingly relevant with the escalation of connectivity in our lives. The growth of streaming of entertainment and development of always online software has created an environment of large data flows that need to be handled efficiently. Historically this problem has been solved with hardware-based load-balancers. These solutions often times are expensive and lack flexibility and scalability. With the use of Software-Defined Networking, a more dynamic solution can be created to meet network load balancing needs. We propose a Smart and adaptable network design seeking to utilize network resources more efficiently by identifying traffic patterns and analyzing network metric to dynamically build virtual slices. With this design, we were able to solve the aforementioned issues through minimizing packet loss, maximizing network link utilization, and efficiently reduce the load on the controller.