Diganta Goswami

Bio: Diganta Goswami is an academic researcher from Indian Institute of Technology Guwahati. The author has contributed to research in topics: Tuple space & Routing table. The author has an hindex of 7, co-authored 43 publications receiving 190 citations. Previous affiliations of Diganta Goswami include Indian Institute of Technology Kharagpur.

Dynamic Slicing of Concurrent Programs

Abstract: We present a framework for computing dynamic slices of concurrent programs using a form of dependence graph as intermediate representations. We introduce the notion of a Dynamic Program Dependence Graph (DPDG) to represent various intra- and interprocess dependences of concurrent programs. We construct this graph through three hierarchical stages. Besides being intuitive, this approach also enables us to display slices at different levels of abstraction. We have considered interprocess communication using both shared memory and message passing mechanisms.

NS3 Simulator for a Study of Data Center Networks

Abstract: The increasing complexity and sophistication of the applications deployed on Data Center Network (DCN) demanded new features and greater performance from the DCN. This resulted in many designs addressing various challenges such as cost, performance, reliability, scalability, security and energy. One major challenge a designer often faces is the realization of their proposed design or realization of the existing designs for comparison. Although proto-typing is a better choice but it does have certain limitation and is very complex and expensive. Hence, Simulation is considered as an alternative to the prototyping. In this paper, we present a case study of using Network Simulator 3 (NS3) for realization of various architectures for DCN and study their performance. The information we provide includes realization of the most popular designs for DCN and tools available with NS3 to study their performance. Our effort is to make it easy for a beginner to build popular designs for DCN and study their performance using NS3.

On performance improvement issues in unordered Tuple Space based Mobile Middleware

Abstract: Tuple Space based Mobile Middleware (TSMM), a new genre of mobile middleware, is developed to tackle emerging dynamics in underlying infrastructure. It uses tuple space model to coordinate interactions between different active components (agents) of supported applications. This paper focusses on a primary design issue of tuple space model, viz. tuple-antituple structure, which specifies arities and nature of arrangements of constituent fields of tuples and antituples. This factor not only affects application design, but also impacts simplicity, flexibility, scalability and performance of TSMM. Broadly, two types of arrangements are possible: ordered (where arity and arrangement of fields are predefined), and unordered (where none of them are predefined). Ordered structure lacks flexibility and restricts the design of TSMM and its applications. Unordered structure removes these drawbacks, but degrades TSMM's performance and scalability, as additional creation and lookup overheads are introduced here. Among the existing TSMM, LIMONE incorporates unordered tuple-antituple structure. In this paper, we modify LIMONE's tuple-antituple structure for improving its performance and scalability. Both original and modified models are analyzed and experimented to show the improvements.

Static slicing in Unix process environment

Abstract: We present a method for computing static slices of concurrent programs in a Unix process environment. As a part of our methodology, we introduce the notion of a Concurrent Program Dependence Graph (CPDG). A CPDG represents various aspects of concurrent programs in a hierarchical fashion. This hierarchical representation lets us compute static slices of programs at different levels of abstraction. Based on our methodology, we have implemented a static slicing tool supporting an option to view slices of programs at different levels of details. Experience with our implementation shows that this approach helps the user get a better understanding of the behavior of concurrent programs. Copyright © 2000 John Wiley & Sons, Ltd.

Networked control system: a brief survey

Abstract: A survey on networked control systems (NCSs), published in a previous paper, is updated and extended. A simple framework and some general formulations for the study of NCSs are proposed. In addition to the survey on NCSs, the impact of NCSs on traditional large-scale system control methodologies with a related application is also reviewed.

A brief survey of program slicing

Abstract: Program slicing is a technique to extract program parts with respect to some special computation. Since Weiser first proposed the notion of slicing in 1979, hundreds of papers have been presented in this area. Tens of variants of slicing have been studied, as well as algorithms to compute them. Different notions of slicing have different properties and different applications. These notions vary from Weiser's syntax-preserving static slicing to amorphous slicing which is not syntax-preserving, and the algorithms can be based on dataflow equations, information-flow relations or dependence graphs.Slicing was first-developed to facilitate debugging, but it is then found helpful in many aspects of the software development life cycle, including program debugging, software testing, software measurement, program comprehension, software maintenance, program parallelization and so on.Over the last two decades, several surveys on program slicing have been presented. However, most of them only reviewed parts of researches on program slicing or have now been out of date. People who are interested in program slicing need more information about the up to date researches. Our survey fills this gap. In this paper, we briefly review most of existing slicing techniques including static slicing, dynamic slicing and the latest slicing techniques. We also discuss the contribution of each work and compare the major difference between them. Researches on slicing are classified by the research hot spots such that people can be kept informed of the overall program slicing researches.

Optimal load balancing in distributed computer systems

Abstract: 1 Single Channel and Star Network Configurations.- 1.1 Introduction.- 1.2 Load Balancing in the Single Job Class Environment.- 1.2.1 Introduction.- 1.2.2 Model description.- 1.2.3 Properties of the optimal solution and an optimal load balancing algorithm.- 1.2.4 Comparison of load balancing algorithm performance.- 1.2.5 An algorithm for star network configurations.- 1.2.6 Conclusion.- 1.3 Load Balancing in the Multi-class Job Environment.- 1.3.1 Introduction.- 1.3.2 Model description.- 1.3.3 Optimal solution.- 1.3.4 Optimal load balancing algorithm.- 1.3.5 Comparison of algorithm performance.- 1.3.6 Conclusion.- 2 Overall vs. Individual Optimum.- 2.1 Introduction.- 2.2 Single Channel Communications Networks.- 2.2.1 Model Description.- 2.2.2 Optimal Solutions.- 2.2.3 Parametric Analysis.- 2.2.4 Anomalous Behaviors of the Optimum and the Equilibrium.- 2.2.5 Numerical Examination.- 2.2.6 Conclusion.- 2.3 Star Network Configurations.- 2.3.1 Model Description.- 2.3.2 Optimal Solutions.- 2.3.3 Parametric Analysis.- 2.3.4 Anomalous Behaviors of the Performance Variables.- 2.3.5 Numerical Examination.- 2.3.6 Discussion.- 2.3.7 Conclusion.- 2.4 Multiclass Single Channel Networks.- 2.4.1 Policies and model.- 2.4.2 Numerical experiment.- 2.4.3 Discussion.- 2.4.4 Conclusion.- 3 Tree Hierarchy Network Configurations.- 3.1 Introduction.- 3.2 Model Description and Problem Formulation.- 3.3 Optimal Load Balancing.- 3.4 Decomposability.- 3.5 Proposed Algorithm.- 3.6 Comparison of Algorithm Performance.- 3.6.1 Comparison of Storage Requirements.- 3.6.2 Comparison of Computation Time Requirements.- 3.7 Link Communication Time and Node Processing Time.- 3.7.1 Concept of Sub-Tree Networks.- 3.7.2 Parametric Analysis.- 3.7.3 Effects of Link Communication Time.- 3.7.4 Effects of Node Processing Time.- 3.8 Conclusion.- 4 Star Network with Two-way Traffic.- 4.1 Introduction.- 4.2 Model Description and Problem Formulation.- 4.3 Necessary and Sufficient Conditions.- 4.4 Proposed Algorithm.- 4.5 Parametric Analysis.- 4.6 A Numerical Example.- 4.7 Discussion.- 4.8 Conclusion.- 5 Tree Network with Two-way Traffic.- 5.1 Introduction.- 5.2 Model Description and Problem Formulation.- 5.3 Necessary and Sufficient Conditions.- 5.4 Decomposition.- 5.5 Proposed Algorithm.- 5.6 Comparison of Algorithm Performance.- 5.6.1 Comparison of Storage Requirements.- 5.6.2 Comparison of Computation Time Requirements.- 5.7 Conclusion.- 6 Uniqueness.- 6.1 Introduction.- 6.2 Description of the Model.- 6.3 The Overall Optimal Solution.- 6.4 The Individually Optimal Solution.- 6.5 Numerical Examples.- 6.6 Concluding Remarks.- 7 A Survey of Dynamic Load Balancing.- 8 Static vs. Dynamic.- 8.1 System Model.- 8.2 Static and Dynamic.- 8.2.1 Static Load Balancing Policies.- 8.2.2 Dynamic Load Balancing Policies.- 8.3 Simulation Results.- 8.4 Discussion.

Context-sensitive slicing of concurrent programs

Abstract: Program slicing is a technique to identify statements that may influence the computations at other statements. Precise slicing has been shown to be undecidable for concurrent programs. This work presents the first context-sensitive approach to slice concurrent programs accurately. It extends the well known structures of the control flow graph and the (interprocedural) program dependence graph for concurrent programs with interference. This new technique does not require serialization or inlining.

Towards Energy-Efficient Wireless Networking in the Big Data Era: A Survey

Abstract: With the proliferation of wireless devices, wireless networks in various forms have become global information infrastructure and an important part of our daily life, which, at the same time, incur fast escalations of both data volumes and energy demand. In other words, energy-efficient wireless networking is a critical and challenging issue in the big data era. In this paper, we provide a comprehensive survey of recent developments on energy-efficient wireless networking technologies that are effective or promisingly effective in addressing the challenges raised by big data. We categorize existing research into two main parts depending on the roles of big data. The first part focuses on energy-efficient wireless networking techniques in dealing with big data and covers studies in big data acquisition, communication, storage, and computation; while the second part investigates recent approaches based on big data analytics that are promising to enhance energy efficiency of wireless networks. In addition, we identify a number of open issues and discuss future research directions for enhancing energy efficiency of wireless networks in the big data era.