WebSphere Application Server is a software product which helps to perform the role of a web application server. WebSphere is a flagship product and a set of Java-based tools by IBM which allows customers to create and manage sophisticated business Web sites. It was originally created by Donald F. Ferguson, who later became CTO of Software for Dell and the first version was launched in 1998.   

While the central WebSphere tool is known as WebSphere Application Server (WAS). WAS is an application server that helps the customer to connect Web site users with Servlets or Java applications. A Servlet is a Java program that runs on the server rather than on the user's application as Java applets do. Servlets are developed to replace the traditional common gateway interface (CGI) scripts. These scripts are usually written in C language, Practical Extraction or Reporting Language to run much faster and to control all other user requests that run in the same process space. 

In addition to Java, WebSphere also supports the open standard interfaces such as Common Object Request Broker Architecture (CORBA) and Java Database Connectivity — JDBC.  WebSphere is designed to use across different operating system platforms. You have an option of selecting the version suitable for your business purpose, as one edition of WebSphere will be offered for small to medium size businesses and another edition is for larger businesses with a huge number of transactions. It also has a Studio, which is a developer's environment added with additional components which allow creating web pages’ for a website and you can also the web pages accordingly. Both the versions support Solaris, Windows NT, OS/2, OS/390, and AIX operating systems.  

While the WebSphere Studio includes a copy of the Apache Web server; which helps the developers to test Web pages and Java applications at any given time.

What is WebSphere?

The moment you ask this question, the first thing that strikes in your mind is WebSphere is an application server; but in reality, WebSphere is the name of the product in IBM family. IBM has many more products under the brand name WebSphere, here are some of them WebSphere Application Server, WebSphere MQ, WebSphere Message broker, WebSphere process Server, WebSphere business modeler, WebSphere business monitor, WebSphere integration developer, WebSphere partner gateway.  

WebSphere Application Server Architecture

WAS is built using Open standards such as Java EE, XML, and Web Services. WebSphere application is supported on the following platforms; Linux, Windows, AIX, Solaris, IBM i and z/OS. It was started with Version 6.1 and the latest version is Version 8.5. While the open and standard specifications are aligned across all the platforms. Platform utilization is to an extent it takes place, but now it is done below across all open standard specifications line. 

Security

The WebSphere Application Server security model is based on the services provided by the operating system and as per the Java EE security model. WebSphere Application Server provides implementations of user authentication and authorization mechanisms given that support for various user registries:

•    Local operating system user registry

•    LDAP user registry

•    Federated user registry (version 6.1)

•    Custom user registry

The authentication mechanisms supported by WebSphere are

• Lightweight Third Party Authentication (LTPA)

Digitalization, digital networking, research, network automation, education and educational networks; are all these the buzz words of recent technology and for education institutions?  Why everyone is talking about digitalization and networks, how are these both interconnected; and what is network automation and education networks are what we are going to know on this blog today .

While what the smaller research say about the education networks and individual campus networks; we can say that both stand for the same aim which is implementing education through current network automation strategies and tools. Are these tools, strategies, and significant efficiencies or the network automation wave more hype than these smaller institutions?

Let us look at some of the regional networks, how they are succeeded and what are the challenges involved in this path of deploying various network automation with relatively small and outsourced staff and support. Also discussed will be the experience of working with this diverse technology and how it increased the awareness about the possible proposed value of network automation and how regional’s can assist smaller schools through this network path. 

Digital learning and collaboration have become an essential part of today’s education. From k-12 schools are implementing the methods of digital learning. These blended learning methods and one to one computing programs are reshaping the classroom studies and engaging more students to become tech-savvy’s. The higher educational institutions are announcing BYOD- which means bring your own device concept; students are also allowed to use their smart phones, laptops, tablets and other gadgets to be connected. This helps the institutions to meet the unprecedented demand for connectivity with high performance and to get recognized as highly reliable campus and data network center solution provider.

Challenges:

The hike of latest technologies, mobile devices and growing appetite for applications and rising security concerns are placing new burdens on educational networks. To meet these challenges, schools are expanding their networks to meet student and faculty expectations for high performance, highly reliable, and always-on connectivity.

The school network is always mission-critical, and downtime will be more and un-tolerable when class lectures, research projects, assignments are involved. We can see diversity and richness using these educational applications as learning is increasingly leveraging interactive curricula, collaboration tools, streaming media, and digital media. The success of the Common Core Assessments hugely depends on connectivity. The higher education, universities, and colleges that have poor quality, non-ubiquitous network access, quickly discover that this is affecting their registration/enrollment rates.

The other challenge is with the number of Wi-Fi devices and the types of devices students bring to a university or college campus; Students commonly have three or more devices like; smartphone, tablet, laptop, gaming device, or streaming media player and expect flawless connectivity. While higher education is deploying wireless IP phones for better communications, IP video cameras to develop physical security, and sensors for a more efficient environment. The projections for the Internet of Things, which will connect hundreds of billions of devices in a few short years, are nothing short of staggering.

The trends that educational networks are looking today for students, faculties and administrator expectations is that of for the connectivity which is rising and the complexity and cost of networking are also growing exponentially. In addition to this growth, the “adding on” to networking equipment for old designs is causing the network to become ever more fragile. IT budgets are tight, and technology necessities are growing faster than the funding.

What if schools took a step back and had a unique opportunity to proactively aim their networks to meet the challenges which hit today and tomorrow? What if deploying the network was simple, not a manual, time-consuming chore? What if your initial design and build could scale for years to come, without having to build configurations on the fly every time? What if networks were easier to plan and build, configure and deploy, visualize and monitor—and had automated troubleshooting and broad reporting?

The tools which are of high configurations help the educational networks are Juniper Networks, HP, CODE42, DLT, EKINOPS, Level 3, cloudyCluster, OSI and much more. It’s time to update the educational institutions towards the design, building, and maintaining the network and taking the advantage of automation and modern management tools to create scale, consistency, and efficiency.

Artificial intelligence has been spread over a very large area of computing since the beginning of the computer, but we are getting closer than ever with cognitive computing models. What are these models and why are we talking about it today. 

Cognitive computing comes from a mash-up of cognitive science which is the study of the human brain and how it functions and a touch of computer science and the results will have far-reaching impacts on our private lives, healthcare, business, and more.

What is Cognitive Computing?

The aim of cognitive computing is to replicate human thought processes in a programmed model. It describes technology platforms that broadly speaking, and which are involved in self-learning systems that use data mining, natural language processing, and pattern recognition to mimic the way the human brain works. With the goal to automate the IT systems that are capable of solving the problems without requiring human assistance the Cognitive computing is growing very fast.

Cognitive computing systems use machine learning algorithms; which repeatedly acquire knowledge from the data fed into them by mining data for information. These systems treat the way they look for patterns and as well as the way they process data so they have become competent of anticipating new problems and modeling possible solutions.

Cognitive computing is used in numerous artificial intelligence applications (AI), including expert systems, neural networks, natural language programming, robotics and virtual reality.  While computers are proved the faster machines at calculations and meting out the humans for decades; these machines haven’t been able to accomplish some tasks that humans take for granted as simple, like understanding natural language, or recognizing unique objects in an image. The cognitive computing represents the third era of computing: it from computers that could tabulate sums (the 1900s) to programmable systems (1950s), and now to cognitive systems.

The cognitive systems; most remarkably IBM and IBM +0.55%’s Watson, depend on deep learning algorithms and neural networks to process the information by comparing it to an education set of data.  The more data the systems are exposed to, the more it learns, and the more accurate it becomes over time, and this type of neural network is a complex “tree” of decisions the computer can make to arrive at an answer.

What can cognitive computing do?

As per the recent TED Talk from IBM, Watson could ultimately be applied in a healthcare setting also, this helps the administrative department of healthcare to collate the span of knowledge around conditions, which include the patient history, journal articles, best practices, diagnostic tools, and many more. Through this, you can easily analyze that vast quantity of information, and provide your recommendations as needed.

The next stage is to examine, which will be proceeded by the consulting doctor, who will then be able to look at the evidence and based on the recorded evidence the treatment options will be released based on these large number of factors including the individual patient’s presentation and history. Hopefully, this will lead to making better treatment decisions.

While in other scenarios, when the goal is not to clear and you look to replace the doctor, and the doctor’s capabilities by processing the humongous amount of data available will not be retained by any human and thus providing a summary of potential application will be overdue. This type of process could be done for any field such as including finance, law, and education in which large quantities of complex data will be in need to be processed and analyzed to solve problems.

However, you can also apply these systems in other areas of business like consumer behavior analysis, personal shopping bots, travel agents, tutors, customer support bots, security, and diagnostics.  We see that there are personal digital assistants available nowadays in our personal phones and computers like —Siri and Google GOOGL -0.21% among others, which are not true cognitive systems; and have a pre-programmed set of responses and can only respond to a preset number of requests.  But, as tech is on high volume we will be able to address our phones, our computers, our cars, our smart houses and get a real time in the near future when thoughtful response rather than a pre-programmed one.

The coming future will be more delightful for us as computers will become more like humans and they will also expand our capabilities and knowledge. Just be ready to welcome the coming era when computers can enhance human knowledge and ingenuity in entirely new ways.