Sumit Kalra

Bio: Sumit Kalra is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Smart contract & Cloud computing. The author has an hindex of 4, co-authored 20 publications receiving 44 citations. Previous affiliations of Sumit Kalra include Indian Institute of Technology Kanpur & Infosys.

Patterns for Indexing Large Datasets

Abstract: Searching is one of the fundamental tasks in Computer Science. An intuitive way to search is to do it linearly, that is, start at the beginning of the dataset and continue till the searched-for item is found or nothing is found. However, as the volume of data increases, the response time of linear search is no longer acceptable. Indexes are designed to search through massive datasets quickly. There are a number of different ways of building complex and advanced indexes. Appropriate selection and modification of indexing structures according to dynamic business requirements is crucial for data-intensive applications. In this work, we present a few basic reusable indexing structures. These structures can be used to create advanced and complex indexing structures with lesser effort and time.

An Architectural Roadmap Towards Building an Alarm Diffusion System

Abstract: Alarm Diffusion Systems(ADS) have complex, exacting and critical requirements. In this work we aim to provide a software architecture perspective towards ADS. We look at both functional and quality requirements for an ADS and also attempt to identify certain quality attributes specific to an ADS and attempted to provide a set of architectural tactics to realise them. We also propose a Reference Architecture for designing such systems. We have provided ample examples to support our inferences and take a deeper look at a case study of the Traffic Collision Avoidance System(TCAS) in aircrafts.

An Efficient LSI Based Multi-keyword Ranked Search Algorithm on Encrypted Data in Cloud Environment

Abstract: Since the advent of cloud computing, a huge number of data owners are outsourcing their sensitive data to be stored on to the cloud. To maintain privacy requirements, this sensitive data should be encrypted when it is stored on the cloud server which renders simple keyword based document retrieval schemes obsolete. In this paper, we propose a semantic multi-keyword ranked search scheme for document retrieval on cloud data that is encrypted. The proposed scheme returns not only the documents containing terms that match with our query terms but also some more documents that contain terms which are semantically similar to the query keywords. Our experimental result shows that our technique is more precise than TF-IDF/VSM(Vector Space Model) models that focus only keyword matching while simultaneously achieving faster retrieval times than other tree based TF-IDF/VSM approach as our algorithm runs on reduced dimensions.

Internal Quality to External Quality: an Approach to Manage Conflicts

Abstract: Software Quality Attributes (QAs) can be categorised as either internal to the system as experienced by the developers or external to the system perceived by the end users. These QA categories have trade-off among them - an emphasis on internal QA may result in a compromise of an external QA. For example, there is a trade-off between maintainability and performance. Model-driven development approaches manage this trade-off and increase the degree of internal QA maintainability. In this work, we propose an ontology-based communication mechanism among software components to handle the trade-off. The approach increases the degree of internal QAs such as modifiability, maintainability, testability during the design and development phases without compromising the external QAs for the end users during the operation phase. We also evaluate a prototype system to validate the proposed approach using Software Architecture Analysis Method (SAAM). It is also easier to integrate into the software development life cycle as compared to existing model-driven approaches.

How to Enable Multiple Skill Learning in a SLA Constrained Service System

Abstract: In a knowledge based service system like IT services, the requirements of skills to service customer requests keep changing with time. The service workers are expected to learn the required skills very quickly and become productive. Due to high attrition rate and demand, service workers are given basic class room training and then rest of the training is carried out on-job. When a service worker learns multiple skills simultaneously, learning slows down due to factors like forgetting and interference. At the same time, the organization needs to meet service level agreements (SLA). We have developed a model for on-job training which extends the business process for IT service delivery. The key idea is to model learning, forgetting and interference in service time estimation to get realistic service times. Accurate estimation of service time taken by a service worker to resolve the service tickets helps in resource allocation and planning decisions for achieving the desired objectives of upskilling and SLA success. The simulation of execution of the augmented business process provides insights into what kind of planning and dispatch policies should be practiced for achieving the desired goals of multi-skill learning and SLA success.

Model Driven Engineering

Abstract: The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Requirements Engineering A Good Practice Guide

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Rule‐Based Expert Systems

Abstract: What is knowledge? § is a theoretical or practical understanding of a subject or a domain. § is also the sim of what is currently known, and apparently knowledge is power. Those who possess knowledge are called experts. § Anyone can be considered a domain expert if he or she has deep knowledge and strong practical experience in a particular domain. § The human mental process is internal, and it is too complex to be represented as an algorithm § However, most experts are capable of expressing their knowledge in the form of rules for problem solving.

Blockchain smart contracts: Applications, challenges, and future trends

Abstract: In recent years, the rapid development of blockchain technology and cryptocurrencies has influenced the financial industry by creating a new crypto-economy. Then, next-generation decentralized applications without involving a trusted third-party have emerged thanks to the appearance of smart contracts, which are computer protocols designed to facilitate, verify, and enforce automatically the negotiation and agreement among multiple untrustworthy parties. Despite the bright side of smart contracts, several concerns continue to undermine their adoption, such as security threats, vulnerabilities, and legal issues. In this paper, we present a comprehensive survey of blockchain-enabled smart contracts from both technical and usage points of view. To do so, we present a taxonomy of existing blockchain-enabled smart contract solutions, categorize the included research papers, and discuss the existing smart contract-based studies. Based on the findings from the survey, we identify a set of challenges and open issues that need to be addressed in future studies. Finally, we identify future trends.

A Design Framework for Internet-scale Event Observation and Notification

Abstract: A new framework that captures many of the design issues was presented in this paper and it comprises seven models: an object model, event model, observation model, naming model, time model, notification model, resource model. This paper discusses each of these models in detail. We discuss the some issues related to Internet-scale event-based infrastructure and give a speculation about the potential areas for research.