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Current state of the art application profilers for function/loop (process) based execution paths perform static profiling during design space exploration. Dynamic optimization is a must for heterogenous platforms to achieve low silicon area and better performance in real-time. Hence, it becomes necessary to have a mechanism in the target platform hardware to identify run-time characteristics of various processes of the application code in execution. This should be at both, an individual process level and in the relationship with other co-processes. This paper proposes DynPath - a hardware-based execution path profiler capable of detecting and identifying the processes along with the execution paths, both in a static and dynamic context. It has a rich set of features in comparison to other process-based profilers reported in the literature. Being non-intrusive it does not cause any run-time overheads. To handle the dynamic nature of input data size versus fixed memory row width, the paper proposes a unique approach based on Content Addressable Memory (CAM) for path identification and optimal hardware utilization. Considering that a process can be part of multiple executions paths, the profiler tracks both, the path invocation count, as well as, path-specific process invocation count (PSPIC) for each process. PSPIC logic being computationally intensive, it also proposes an alternative implementation of the PSPIC logic based on resource sharing which helps reduce the total area overhead of the execution path profiler by 87%.

It has been proven that Internet of Things (IoT) platforms can improve the performance and efficiency of a wide range of processes. With the acceptance of IoT as a major part of the technology of Industry 4.0, the notion of leveraging the Internet in industries to enable automation and reconfigure existing industrial processes has greatly evolved. By introducing smart technology and intelligent processes, the Industrial Internet of Things (IIoT) is committed to bringing high operational efficiency, enhanced productivity, and effective management to industrial assets. Despite this, the reliance of IIoT on central architecture presents numerous challenges, including the security and maintenance of smart devices, privacy issues owing to third-party participation, and massive computations conducted by a central entity, all of which prevent its widespread adoption in businesses. Emerging blockchain technologies have the potential to transform IIoT platforms and applications. A distributed and decentralized approach followed by blockchain might offer interesting solutions to the challenges raised by IIoT. Furthermore, 5G networks are expected to deliver excellent solutions to meet the demands of decentralized systems, with a focus on application-specific vulnerabilities. Blockchain and IIoT, enabled by 5G, is a viable option to fully explore the potential of contemporary industry. In this context, this article analyzes and examines recent achievements to highlight the major obstacles in blockchain–IIoT convergence and presents a framework for potential solutions. A well-organized literature review by analyzing the existing work in three primary areas: blockchain consensus algorithms used in existing IoT and IIoT applications, blockchain for 5G-enabled IoT networks, and blockchain in industry have been performed, with major findings summarized in each area. Directions for the future are also provided and intend to assist researchers in understanding the full potential of these innovations.

As Blockchain innovation picks up popularity in many areas, it is frequently hailed as a sound innovation. Because of the decentralization and encryption, many imagine that data put away in a Blockchain is and will consistently be protected. Among various abstraction layers of Blockchain architecture, the consensus layer is the core component behind the performance and security measures of the Blockchain network. Consensus mechanisms are a critical component of a Blockchain system’s long-term stability. Consensus forms the core of blockchain technology. Therefore, a range of consensus protocols has been introduced to maximize Blockchain systems’ efficiency and meet application domains’ individual needs. This research paper describes the layered architecture of Blockchain. A comprehensive review of mainstream consensus protocols mainly Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Activity (PoA) is presented in the paper. These mainstream consensus protocols have been explained and detailed performance analysis of these consensus protocols has been done. We have proposed a performance matrix of these consensus protocols based on different parameters like Degree of decentralization, Latency, Fault Tolerance Rate, Scalability, etc. Consensus protocols being the core of a strong fault-tolerant secured blockchain system, the proposed work intends to help inappropriate protocol selection and further research on strengthening trust and ownership in the technology. Depending upon different parameters like decentralization which is low in POA compared to other protocols, whereas POW is non-scalable, so depending on the priority of a particular performance parameter, the paper will help in the selection of a specific protocol.