Attestation of Improved SimBlock Node Churn Simulation

Node churn, or the constant joining and leaving of nodes in a network, can impact the performance of a blockchain network. The difficulties of performing research on the actual blockchain network, particularly on a live decentralized global network like Bitcoin, pose challenges that good simulators can overcome. While various tools, such as NS-3 and OMNet++, are useful for simulating network behavior, SimBlock is specifically designed to simulate the complex Bitcoin blockchain network. However, the current implementation of SimBlock has limitations when replicating actual node churn activity. In this study, the SimBlock simulator was improved to simulate node churn more accurately by removing churning nodes and dropping their connections and increasing additional instrumentation for validation. The methodology used in the study involved modeling the Bitcoin node churn behavior based on previous studies and using the enhanced SimBlock simulator to simulate node churn. Empirical studies were then conducted to determine the suitability and limitations of the node churn simulation. This study found that the improved SimBlock could produce results similar to observed indicators in a 100-node network. However, it still had limitations in replicating node churn behavior accurately. It was discovered that SimBlock limits all nodes to operate as mining nodes and that mining is simulated in a way that does not depict churn accurately at any time but only at specific intervals or under certain conditions. Despite these limitations, the study’s improvements to SimBlock and the identification of its limitations can be useful for future research on node churn in blockchain networks and the development of more effective simulation tools

Enhanced multicore load balancer with core-to-task ratio based trigger level

This work described here then proceeds to evaluate (1) the cost of migration using an industry standard micro-benchmark ‘lmbench’ on a uniquely configured piece of hardware to ensure fair comparison, (2) the number of migrations on a representative operating system used for departmental HPC (dominated by the GNU Linux operating system) using a GNU Linux Scheduler simulator, and finally (3) proposes, implements and evaluates a dynamic load balancer triggering, based on the number of tasks in the system and the number of processing cores for a most effective utilisation of the processing cores. The benefits is illustrated using synthetic benchmarks and standard HPC benchmarks, the NASA Parallel Benchmarks. In this work, the proposed method achieved up to a 27% improvement

Preface for IOP Conference Series: Earth and Environmental Science

The 2020 5th International Conference on Renewable Energy and Environmental Protection (ICREEP 2020) was planned to be held on October 23-25, 2020 in Shenzhen, China. Currently, the entire world is struggling against the virulent pandemic COVID-19. Unfortunately, each of us is affected, either overtly or covertly. Our conference, 2020 5th International Conference on Renewable Energy and Environmental Protection (ICREEP 2020) was not an exception. Nowadays, mass gatherings are not permitted by the government. It is uncertain when the COVID-19 would end, so it remains unclear for postponement time, while many scholars and researchers wanted to attend this long-waited conference and have academic exchanges with their peers. Therefore, in order to actively respond the call of the government, and meet author's request, the ICREEP 2020, which was planned to be held in Shenzhen, China from October 23-25, 2020, was changed to be held online through Zoom software. This approach not only reduces people gathering, but also meets their communication needs

Red-black tree architecture for P2P media streaming

With the recent surge of Internet enabled portable devices, such as smart phones and tablets, it has resulted in a much faster growth of the global Internet usage. Most of the usage is due to the use of social media platforms where streaming media is used heavily. Most of the researches conducted were to address the issues related to overall delivered quality in a resource-constraint streaming environment as well as the issues related to the scalability of the overall media streaming system. While there are other areas of research that have seen significant work in addressing the limitations posed by the current network infrastructure, devices capabilities and also on the characteristics of the streaming media themselves. These research projects address different factors that lead to alleviating network capacity bottlenecks. The success of Peer-to-Peer (P2P) file sharing systems inspired the development of P2P streaming systems for delivering online multimedia service in the last few years. P2P networks are broadly categorized into two main network architecture; a tree-based architecture and a mesh-based architecture. Despite the advantages offered by tree-based streaming architecture, it is lacking in maintaining a balanced tree architecture which is needed to ensure a consistent quality of service. In this paper, we investigate and evaluate our proposed red-black tree-based streaming architecture as compared to a traditional tree-based architecture for media streaming performance. The simulations were conducted under various real-world scenarios and evaluated using different critical performance metrics that affect the overall streaming quality and performance

Predicting Shopper Volume Using ARIMA on Public Wi-Fi Signals

Shopping malls are being built at a rapid pace in many South East Asia countries and it has become competitive to attract and maintain shoppers.Being able to know the volume of shoppers and predicting the volume will greatly benefit mall management. In this paper, we present shopper volume monitoring using Wi-Fi signal detectors and use the data obtained from it to derive an Auto-Regressive Integrated Moving Average (ARIMA) model for shopper volume prediction

On the trade-offs of Proof-of-Work algorithms in blockchains

There are many different protocols that regulate the way in which each node on a blockchain network is able to reach consensus that a newly created block is valid. One of the protocols, Proof-of-Work (PoW) gained popularity when it was implemented in a blockchain-based cryptocurrency known as Bitcoin. However, there are inherent deficiencies in its current implementation. This paper discusses these deficiencies, as well as the parameters that directly and indirectly affect its efficacy and performance so that possible enhancements to the protocol can be investigated

Genetic-Algorithm-Inspired Difficulty Adjustment for Proof-of-Work Blockchains

In blockchains, the principle of proof-of-work (PoW) is used to compute a complex mathematical problem. The computation complexity is governed by the difficulty, adjusted periodically to control the rate at which new blocks are created. The network hash rate determines this, a phenomenon of symmetry, as the difficulty also increases when the hash rate increases. If the hash rate grows or declines exponentially, the block creation interval cannot be maintained. A genetic algorithm (GA) is proposed as an additional mechanism to the existing difficulty adjustment algorithm for optimizing the blockchain parameters. The study was conducted with four scenarios in mind, including a default scenario that simulates a regular blockchain. All the scenarios with the GA were able to achieve a lower standard deviation of the average block time and difficulty compared to the default blockchain network without GA. The scenario of a fixed difficulty adjustment interval with GA was able to reduce the standard deviation of the average block time by 80.1%, from 497.1 to 98.9, and achieved a moderate median block propagation time of 6.81 s and a stale block rate of 6.67%

SINR-based conversion and prediction approach for handover performance evaluation of video communication in Proxy Mobile IPv6

Proxy Mobile IPv6 is an operational cluster of network-based localized mobility management protocol. This protocol has numerous advantages but still suffers from long latency and degradation in performance during the handover of video transmissions. In order to minimize the latency and improve performance during handover, this paper proposes a Signal to Interference and Noise Ratio (SINR)-based conversion and prediction approach. The approach sets up a prior connection based on the mobility prediction, reduces the time to acquire information, eliminates on-the-fly packet loss, and executes horizontal and vertical handover using SINR conversion. The motivation of this paper is to simulate, analyze and evaluate the video performance over Proxy Mobile IPv6 protocol. Simulations were conducted on packet and frame metrics which are latency, cumulative jitter, packet loss, frame loss and video quality measurements that analyzes and evaluates the network performances at the mobile host and during the handover