Blockchain has emerged as a solution for ensuring accurate and truthful environmental variable monitoring needed for the management of pollutants and natural resources. The immutability property of blockchain helps protect the measured data on pollution and natural resources to enable truthful reporting and effective management and control of polluting agents. However, specifics on what to measure, how to use blockchain, and highlighting which blockchain frameworks have been adopted need to be explored to fill the research gaps. Therefore, we review existing works on the use of blockchain for monitoring and managing environmental variables in this paper. Specifically, we examine existing blockchain applications on greenhouse gas emissions, solid and plastic waste, food waste, food security, water usage, and the circular economy and identify what motivates the adoption of blockchain, features sought, used blockchain frameworks and consensus algorithms, and the adopted supporting technologies to complement data sensing and reporting. We conclude the review by identifying practical works that provide implementation details for rapid adoption and remaining challenges that merit future research.

Privacy laws in South Asian countries are still at a nascent stage. Therefore, South Asian websites are susceptible to user privacy violation. This paper presents an assessment of website privacy policies from 10 sectors in the three largest South Asian economies, namely, India, Pakistan, and Bangladesh. Using a manual qualitative analysis on a dataset of 284 popular websites, we assessed the policies based on accessibility, readability, and compliance with 11 privacy principles. Our findings show that overall, the privacy statement accessibility, and privacy compliance of websites from the three countries is low especially in the education, healthcare, and government sectors. Readability is quite low for websites in all 10 sectors of the three countries. Privacy compliance in each country is the highest for the principles of data processing and third-party transfer, whereas it is the lowest for protection of children’s data, data retention and portability. Indian websites performed comparatively better amongst the three countries on all three metrics, followed by Pakistan, and Bangladesh. Based on our results, we provide recommendations involving all stakeholders (i.e., website owners, privacy regulators, and users) to help improve privacy protection of user data in South Asia.

Determining the qualitative states of the Internet requires an accurate knowledge of queueing delay over an end-to-end path. However, the measurement of queueing delay in a large network is still considered a complex and open problem. Existing schemes that measure queueing delay compensate for this complexity using a high infrastructural support and administrative access to the path under test even though their feasibility and accuracy on the Internet are low. In this paper, we propose an active scheme, called COMPRESS: COMpound Probe compRESSion, to measure queueing delay on all routers over an end-to-end path. The proposed scheme performs per-hop measurement using UDP-based probing packets. It is both simple and self-sufficient in comparison to the existing schemes. We have implemented the proposed scheme in a simulation environment to present a controlled performance evaluation under different levels (e.g., light, moderate, and heavy) and types (e.g., symmetric and asymmetric) of queueing delays over single- and multiple-hop paths. Our simulation results show that the scheme is sensitive to the induced queueing delays and consistently provides a high measurement accuracy. Overall, the scheme has an average measurement error of around 20% or below over the simulated paths.

Carbon capture and storage (CCS) is one of the important initiatives widely used across different industries in reducing atmospheric carbon emissions, which is an essential environmental goal outlined in Sustainable Development Goal 13 (SDG 13) in 2015. In an effort to mitigate carbon-emission problem, CCS extracts (i.e., captures and compresses) and storesCO₂from industrial by-products as an alternative to releasing it directly into the atmosphere. CCS presents opportunities for the capturedCO₂to immediate utilization or to be stored at adjacent facilities for future utilization in different industrial productions. Despite its potential in reducing carbon emissions, its effectiveness and possible economic incentivization are unknown due to a lack of transparency in tracking the quantitative output concerning carbon reduction at different stages of CCS activities (capture, transportation, and storage) currently deployed in different industrial plants. In this paper, we propose an enhanced CCS for recording and tracking the quantitative output of CCS activities using blockchain (i.e., a distributed-ledger) technology that promotes transparency among stakeholders, e.g., government, regulatory body, technical experts, and general public, and facilitates rewards toward effective carbon-emission reductions. Although blockchain is a promising technology that can increase the efficiency of CCS, we also identify a few future challenges, such as data privacy and scalability, that have to be taken into account toward implementing the proposed architecture.

Recently, hosts connected to the Internet through network interface cards (NICs) are equipped with a hardware artifact called interrupt coalescence (IC). This artifact reduces the processing load of a host in exchange for an additional delay in the receiving of packets that arrive into its NIC. Even though the adoption of IC has its benefits, the additional delay negatively affects the hosts that are involved in the performance measurement of various network parameters and time-sensitive applications. Therefore, prior knowledge of IC-inflicted delay may be used to facilitate accurate delay and bandwidth measurements, IP geolocation, and traffic load-balancing. In this paper, we propose what we believe as the first scheme to measure the IC period (the additional delay) of remote hosts through the use of pairs of probing packets and a k-means clustering algorithm. We report the practicability of our scheme and the high accuracy through extensive experiments on both a controlled and production networks consisting of up to 1000-Mb/s links. Our experimental evaluations show that the proposed scheme measures IC period with 90% accuracy, quickly, and with a small probing load.