Arnab Majumdar

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Arnab Majumdar

I have 11+ years of experience in Quality Assurance both in Non functional and Functional testing. I have extensive experience in performance testing of multiple technologies like Java, JavaScript, MS Dynamics, Mainframe, Salesforce. Procured expertise on Performance testing tools like Microfocus LoadRunner, Neoload and premium APM tools like AppDynamics, Dynatrace, Kibana. I have good understanding of Agile and Waterfall methodologies of Project Delivery. I have good knowledge in Java programming and worked on implementing many automation tools as part project lifecycle improvement. I have also worked in Accessibility Testing and have good understanding of WCAG guidelines.
I am currently working as a Non Functional Test Lead from Cognizant in one of the leading banks in UK and managing a team of 5+ members for one of the most ambitious projects for the client where project delivery follows Agile process and Latest technologies like Agile, MS Dynamics, Azure, Elastic Search are involved.

Title: Performance Evaluation Strategy of multi-access edge computing

Abstract:

The year 2020 has posed a never-seen-before challenge to the technology industries where COVID-19 pandemic has restricted IT operations and support to isolated locations within the boundaries of personal homes. A radical shift has been experienced from integrated infrastructures to distributed computing topologies. Processing of data or information at the edge or user level of the entire network has come up as the single most important factor for the organisations to survive and thrive in one of the most challenging years of IT industry. Such a distributed computing topology which has gained significant importance during recent times is Edge computing.

At its ground level, edge computing puts information processing and data storage closer to the devices where it’s being gathered, rather than relying on a central location far away from the user device. This is done in such a manner so that data, especially real-time data, does not undergo latency issues that

can affect an application’s performance. In addition, organizations can save cost and effort by having the data processing done locally or at the Edge, reducing the amount of data that needs to be processed in a centralized or cloud-based location. Edge computing is being dubbed as one of the most foundational technologies for enterprises due to its shorter latencies, robust security, responsive data collection and lower costs.

Emergence of 5G technology has further enhanced the possibility of wide level adoption of multi-access edge computing formerly known as mobile edge computings(MEC) technologies at enterprise level. Instead of such promising future present for this technology, the design of mobile edge cloud systems is complex and thus its important to find a suitable deployment and QA strategy. Since mobile edge cloud computing technology and its deployment techniques are quite new, no proper techniques and knowledge are available about possible deployments, configurations, and performance evaluation. Hence it is necessary to create a viable performance evaluation strategy for the MEC systems.

Hence in this paper we will discuss about the challenges and possible solutions for the performance testing of MEC systems and will propose a suitable performance evaluation strategy for these systems

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