International Journal of High Performance Computing and Networking (5 papers in press)
PFSS: a privacy-friendly and secure smart metering for time of
use operational data collection in a smart grid network
by Oladayo Olakanmi
Abstract: Advanced metering infrastructure (AMI) is an integral part of a smart grid network which involves transmission of finest grain operational data of consumers' load profiles on wireless facilities. These operational data are used for effective load balancing, billing, and analysis of the smart grid network. Unauthorised access to these operational data can easily disrupt the smart grid network or create distrust among consumers. Meanwhile, the vulnerabilities of AMI wireless facilities encourage unauthorised access to this sensitive information, making AMI a soft target for adversaries in the smart grid network. Many security schemes have been proposed for AMI to detect and prevent attacks in order to achieve the required security and privacy properties expected. However, some of them only focus on specific attack(s), leaving other attacks, and most of them cannot be efficiently used to secure energy profiles from different time of use without increasing communication overhead. In this paper, a provably lightweight security scheme to secure metering and information exchange, and consumers privacy, irrespective of the attacking points and nature of the attacks is proposed for AMI. To achieve this, we developed a chain-based pseudonym and shadow key approach to preserve privacy. We also develop low-cost cryptographic approach using Shamir secret sharing to evolve effective grouping and authentication approaches that classify consumers energy profiles based on time of use. Our scheme ensures data security and cooperative aggregation among m number of consumers of the same service provider. The security analysis and performance evaluation of the scheme are also presented. The results illustrate that the approach secures metering at a low computational overhead.
Keywords: smart grid; operational data; time of use; aggregation; metering.
A survey on the applications of machine learning in wireless sensor networks
by Lokesh Chouhan, Nancy Chauhan, Amitosh Swain Mahapatra, Vidushi Agarwal
Abstract: Wireless sensor networks (WSNs) are used to observe, explore, and control the physical world. They are generally deployed in environments that are dynamic in nature. To avoid unnecessary redesign, sensor networks use machine learning techniques. Machine learning is also used to maximise the security, efficiency, lifetime, and resource usage in such networks. In this paper, we present a literature survey of various machine learning applications that are used or are in research to address the operational and non-operational challenges in WSNs.
Keywords: clustering; data aggregation; machine learning; operational and non-operational challenges; security; wireless sensor networks.
Looking at performance metrics and scalability challenges in the context of microservices: a survey
by Igor Fontana, Cristiano Costa, Jorge Barbosa, Rodrigo Da Rosa Righi, Thiago Lopes, Kleinner Farias
Abstract: The use of microservices is a new trend in software engineering, dividing an application into several services, each one with a small and self-contained function. This concept allows programmers to write each microservice code using the better language and framework they know based on the microservice functionality. We perceive that research on microservices aims mainly at composability, portability, and interface, leaving uncovered in surveys relevant quality concerns, such as performance and scalability. This article, therefore, reports a survey focused on providing a classification and an analysis of studies on the evaluation and improvement of performance in microservice-based applications. In this process, we identified research gaps and trends. After conducting the review method, we found 45 studies, published between 2015 and 2019. Our contributions are threefold: (i) an in-depth analysis of the state of the art on microservices through the lens of performance; (ii) a novel taxonomy to reclassify the current microservices initiatives, looking at software and hardware aspects that interfere in the execution of the application; (iii) an analysis of trends and open research opportunities in the joint combination of performance and scalability applied to microservices.
Keywords: microservices; performance; scalability; metrics; quality of service.
Infinite impulse response system identification using antlion optimisation algorithm
by Sandeep Singh, Alpana Shekhar, Chakshu Kalra, Shubham Kaushik, Tarun Kumar Rawat, Alaknanda Ashok
Abstract: This paper focuses on infinite impulse response (IIR) system identification using a recent nature-inspired algorithm called antlion optimisation (ALO). The system identification problem concerns determining the viable parameters by minimising the cost function. Generally, gradient-based techniques are mostly used for IIR system identification. However, these traditional algorithms face the problem of getting trapped in local solution. So to get rid of this problem, a novel ALO algorithm is used for IIR system identification. The ALO is inspired by the preying process of antlions on the ants. The algorithm is free of the issues faced by the traditional techniques. The performance of the ALO algorithm is measured using two measures, the mean square error, which is taken as cost function, and the convergence profile. The results obtained using ALO are compared with that of the particle swarm optimisation algorithm and cat swarm optimisation algorithm. The obtained results confirmed that the ALO algorithm surpasses the performance of the existing algorithms.
Keywords: antlion algorithm; system identification; mean square error; convergence profile.
A survey of blockchain as a service platform
by Samer Muneer Alshurafa, Derar Eleyan, Amna Eleyan
Abstract: Blockchain provides more security and decentralised systems. However, it is difficult for startups and small companies to build and deploy their blockchain networks. So, cloud computing providers make it easy for those to work with blockchain using their networks and cloud infrastructure through using blockchain as a service platform. There are many blockchain as a service providers and platforms. This survey provides an overview of 23 such platforms and provides a comparison based on provider, blockchain protocol, blockchain type, cost, security, and support of smart contract.
Keywords: blockchain; blockchain as a service; cloud computing; distributed ledger technology.