Ramamurthy Badrinath

Bio: Ramamurthy Badrinath is an academic researcher from Ericsson. The author has contributed to research in topics: Cyber-physical system & Protocol (object-oriented programming). The author has an hindex of 11, co-authored 34 publications receiving 384 citations. Previous affiliations of Ramamurthy Badrinath include Hewlett-Packard & Indian Institute of Technology Kharagpur.

Kerrighed: A Single System Image Cluster Operating System for High Performance Computing

Abstract: Kerrighed is a single system image operating system for clusters. Kerrighed aims at combining high performance, high availability and ease of use and programming. Kerrighed implements a set of global resource management services that aim at making resource distribution transparent to the applications, at managing resource sharing in and between applications and at taking benefit of the whole cluster resources for demanding applications. Kerrighed is implemented as a set of modules extending the Linux kernel. Legacy multi-threaded applications and message-passing based applications developed for an SMP PC running Linux can be executed without re-compilation on a Kerrighed cluster. The proposed demonstration presents a prototype of Kerrighed running on a cluster of four portable PCs. It shows the main features of Kerrighed in global memory, process and stream management by running multi-threaded and MPI applications on top of Kerrighed.

IOT Enabled Smart Logistics Using Smart Contracts

Abstract: Advancements in sensors and devices have enabled Internet of Things (IoT) adoption in various sectors, especially in domains looking to automate and increase their real-time decision making capabilities to improve efficiencies. Supply chain management in logistics is a perfect fit for adoption of IoT, since it involves shipment of assets being moved, tracked and housed by a number of machines, vehicles and people each day. Smart Contracts are terms and conditions parties can specify that assure trust in the enforceability of the contract and provide visibility at every step of a supply chain. IoT devices can write to a smart contract as a product moves from the factory floor to the store shelves, providing real-time visibility of an enterprises entire supply chain. This paper proposes a smart logistics solution encapsulating smart contracts, logistics planner and condition monitoring of the assets in the Supply Chain Management area. A prototype of the solution is implemented which demonstrates accountability, traceability and liability for asset handling across the supply chain by various parties involved in a logistics scenario.

Hybrid checkpointing for parallel applications in cluster federations

Abstract: Cluster federations are attractive for executing applications like large scale code coupling. However faults may appear frequently in such architectures. Thus, checkpointing long-running applications is desirable to avoid to restart them from the beginning in the event of a node failure. To take into account the constraints of a cluster federation architecture, an hybrid checkpointing protocol is proposed. It uses global coordinated checkpointing inside clusters but only quasi-synchronous checkpointing techniques between clusters. The proposed protocol has been evaluated by simulation and fits well for applications that can be divided into modules with lots of communications within modules but few between them.

SOA-PE: A service-oriented architecture for Planning and Execution in cyber-physical systems

Abstract: In this paper, we suggest a service-oriented architecture for planning and execution (SOA-PE) in large scale cyber-physical systems (CPS). SOA-PE provides a clean separation between domain modeling, planning, execution, monitoring and actuation services. This approach helps realize the system-of-systems paradigm allowing the decomposition of system goals into smaller subgoals, thus enhancing the scalability of the proposed solution. In addition to supporting large scale, autonomous systems, the service-oriented approach provides several benefits such as reusability, independent development and deployment, platform independence, transparency and flexibility, to the core services of Planning and Execution in these systems. The architecture targets decentralized, multi-agent systems for solutions like smart transportation and logistics and can scale to larger IoT use cases like smart cities. We illustrate the functionalities of the architecture through a prototype implementation and a case study from the logistics domain.

Automated Planning: Theory and Practice.

Abstract: A translation apparatus is provided which comprises: an inputting section for inputting a source document in a natural language; a layout analyzing section for analyzing layout information including cascade information, itemization information, numbered itemization information, labeled itemization information and separator line information in the source document inputted by the inputting section and specifying a translation range on the basis of the layout information; a translation processing section for translating a source document text in the specified translation range into a second language; and an outputting section for outputting a translated text provided by the translation processing section.

Kakusan4 and Aminosan: two programs for comparing nonpartitioned, proportional and separate models for combined molecular phylogenetic analyses of multilocus sequence data.

Abstract: Proportional and separate models able to apply different combination of substitution rate matrix (SRM) and among-site rate variation model (ASRVM) to each locus are frequently used in phylogenetic studies of multilocus data A proportional model assumes that branch lengths are proportional among partitions and a separate model assumes that each partition has an independent set of branch lengths However, the selection from among nonpartitioned (ie, a common combination of models is applied to all-loci concatenated sequences), proportional and separate models is usually based on the researcher’s preference rather than on any information criteria This study describes two programs, ‘Kakusan4’ (for DNA sequences) and ‘Aminosan’ (for amino-acid sequences), which allow the selection of evolutionary models based on several types of information criteria The programs can handle both multilocus and single-locus data, in addition to providing an easy-to-use wizard interface and a noninteractive command line interface In the case of multilocus data, SRMs and ASRVMs are compared at each locus and at all-loci concatenated sequences, after which nonpartitioned, proportional and separate models are compared based on information criteria The programs also provide model configuration files for MRBAYES, PAUP*, PHYML, RAXML and Treefinder to support further phylogenetic analysis using a selected model When likelihoods are optimized by Treefinder, the best-fit models were found to differ depending on the data set Furthermore, differences in the information criteria among nonpartitioned, proportional and separate models were much larger than those among the nonpartitioned models These findings suggest that selecting from nonpartitioned, proportional and separate models results in a better phylogenetic tree Kakusan4 and Aminosan are available at http://wwwfifthdimensionjp/ They are licensed under GNU GPL Ver2, and are able to run on Windows, MacOS X and Linux

Blockchain and Machine Learning for Communications and Networking Systems

Abstract: Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices may bring serious security, privacy, services provisioning, and network management challenges. In order to achieve decentralized, secure, intelligent, and efficient network operation and management, the joint consideration of blockchain and machine learning (ML) may bring significant benefits and have attracted great interests from both academia and industry. On one hand, blockchain can significantly facilitate training data and ML model sharing, decentralized intelligence, security, privacy, and trusted decision-making of ML. On the other hand, ML will have significant impacts on the development of blockchain in communications and networking systems, including energy and resource efficiency, scalability, security, privacy, and intelligent smart contracts. However, some essential open issues and challenges that remain to be addressed before the widespread deployment of the integration of blockchain and ML, including resource management, data processing, scalable operation, and security issues. In this paper, we present a survey on the existing works for blockchain and ML technologies. We identify several important aspects of integrating blockchain and ML, including overview, benefits, and applications. Then we discuss some open issues, challenges, and broader perspectives that need to be addressed to jointly consider blockchain and ML for communications and networking systems.

A survey on resource allocation in high performance distributed computing systems

Abstract: Classification of high performance computing (HPC) systems is provided.Current HPC paradigms and industrial application suites are discussed.State of the art in HPC resource allocation is reported.Hardware and software solutions are discussed for optimized HPC systems. An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.