Wireless sensor network (WSN) consists of a large number of sensor nodes distributed over a certain target area. The WSN plays a vital role in surveillance, advanced healthcare, and commercialized industrial automation. Enhancing energy-efficiency of the WSN is a prime concern because higher energy consumption restricts the lifetime (LT) of the network. Clustering is a powerful technique widely adopted to increase LT of the network and reduce the transmission energy consumption. In this article (LT) we develop a novel ARSH-FATI-based Cluster Head Selection (ARSH-FATI-CHS) algorithm integrated with a heuristic called novel ranked-based clustering (NRC) to reduce the communication energy consumption of the sensor nodes while efficiently enhancing LT of the network. Unlike other population-based algorithms ARSH-FATI-CHS dynamically switches between exploration and exploitation of the search process during run-time to achieve higher performance trade-off and significantly increase LT of the network. ARSH-FATI-CHS considers the residual energy, communication distance parameters, and workload during cluster heads (CHs) selection. We simulate our proposed ARSH-FATI-CHS and generate various results to determine the performance of the WSN in terms of LT. We compare our results with state-of-the-art particle swarm optimization (PSO) and prove that ARSH-FATI-CHS approach improves the LT of the network by ~ 25%.

The interlinked processing units in modern Cyber-Physical Systems (CPS) creates a large network of connected computing embedded systems. Network-on-Chip (NoC)-based Multiprocessor System-on-Chip (MPSoC) architecture is becoming a de facto computing platform for real-time applications due to its higher performance and Quality-of-Service (QoS). The number of processors has increased significantly on the multiprocessor systems in CPS; therefore, Voltage Frequency Island (VFI) has been recently adopted for effective energy management mechanism in the large-scale multiprocessor chip designs. In this article, we investigated energy-efficient and contention-aware static scheduling for tasks with precedence and deadline constraints on intelligent edge devices deploying heterogeneous VFI-based NoC-MPSoCs (VFI-NoC-HMPSoC) with DVFS-enabled processors. Unlike the existing population-based optimization algorithms, we proposed a novel population-based algorithm called ARSH-FATI that can dynamically switch between explorative and exploitative search modes at run-time. Our static scheduler ARHS-FATI collectively performs task mapping, scheduling, and voltage scaling. Consequently, its performance is superior to the existing state-of-the-art approach proposed for homogeneous VFI-based NoC-MPSoCs. We also developed a communication contention-aware Earliest Edge Consistent Deadline First (EECDF) scheduling algorithm and gradient descent--inspired voltage scaling algorithm called Energy Gradient Decent (EGD). We introduced a notion of Energy Gradient (EG) that guides EGD in its search for island voltage settings and minimize the total energy consumption. We conducted the experiments on eight real benchmarks adopted from Embedded Systems Synthesis Benchmarks (E3S). Our static scheduling approach ARSH-FATI outperformed state-of-the-art technique and achieved an average energy-efficiency of ∼24% and ∼30% over CA-TMES-Search and CA-TMES-Quick, respectively.

Quantum cryptography is anticipated to drive substantial advancements in the field of cybersecurity. The impending arrival of quantum cryptography has the potential to compromise current encryption methods, thereby possibly compromising the effectiveness of traditional key management-based security protocols. Quantum cryptography represents a burgeoning area that necessitates thorough examination and scrutiny to validate its efficacy in safeguarding data and securely distributing secret keys. One fundamental quantum key distribution protocol, BB84, encounters challenges when operating with fewer quantum bits (qubits) and bases that only support up to 8 qubits. This limitation weakens the system’s security, making brute force, intercept, and resend attacks less challenging. Consequently, this study proposes a method to enhance the security of the BB84 protocol, to reduce susceptibility to attacks and eavesdropping. The proposed improved BB84 protocol utilizes 9, 12, and 16 quantum bits along with two, and three bases to significantly bolster security, allowing authorized parties to prevent the key distribution process and eliminate the use of compromised keys. Additionally, this study has implemented the E91 quantum key distribution protocol utilizing the Entanglement Pair Generation method to produce secure keys. While the existing E91 protocol ensures security through Bell’s theorem and Bell’s inequality, it overlooks the impact of noise, leading to inaccuracies in eavesdropper detection. Hence, this study introduces an additional security measure. Whenever an eavesdropper attempts to measure the quantum state, the proposed E91 protocol collapses its state from |10⟩ to |11⟩, setting the first qubit to |1⟩ and the other qubit to |0⟩, thus providing the eavesdropper with incorrect information, accompanied by a phase angle of 15π/8. This leads to misconception and misconfiguration, preventing eavesdroppers from obtaining useful details about transferred quantum states and compromising the keys. Additionally, considering that the proposed E91 protocol relies on entangled particles and utilizes double qubit gates, which are inherently noisier than single qubit gates and susceptible to quantum decoherence, this study employs error mitigation techniques in the final measurement to predict outcomes more efficiently.

The reliance on Network-on-Chip (NoC) based Multiprocessor Systems-on-Chips (MPSoCs) is proliferating in modern embedded systems to satisfy the higher performance requirement of multimedia streaming applications. Task level coarse grained software pipeling also called re-timing when combined with Dynamic Voltage and Frequency Scaling (DVFS) has shown to be an effective approach in significantly reducing energy consumption of the multiprocessor systems at the expense of additional delay. In this paper we develop a novel energy-aware scheduler considering tasks with conditional constraints on Voltage Frequency Island (VFI) based heterogeneous NoC-MPSoCs deploying re-timing integrated with DVFS for real-time streaming applications. We propose a novel task level re-timing approach called R-CTG and integrate it with non linear programming based scheduling and voltage scaling approach referred to as ALI-EBAD. The R-CTG approach aims to minimize the latency caused by re-timing without compromising on energy-efficiency. Compared to R-DAG, the state-of-the-art approach designed for traditional Directed Acyclic Graph (DAG) based task graphs, R-CTG significantly reduces the re-timing latency because it only re-times tasks that free up the wasted slack. To validate our claims we performed experiments on using 12 real benchmarks, the results demonstrate that ALI-EBAD out performs CA-TMES-Search and CA-TMES-Quick task schedulers in terms of energy-efficiency.

Blockchain technology is increasingly recognised for its potential to enhance the security, reliability, and resilience of distributed systems. By ensuring data integrity and protecting against unauthorised access, blockchain creates immutable and transparent records, making it an appealing option for various applications. In the current healthcare landscape, secure data sharing is essential for improving patient outcomes, streamlining healthcare operations, and ensuring compliance with legal standards. This paper conducts a systematic literature review to explore how blockchain can be utilised as a security solution for health data sharing. We assess the strengths and weaknesses of blockchain-based solutions in areas such as secure data management, data sharing, access control, trust and transparency, and authentication and authorisation. Our findings indicate that blockchain has significant potential to secure health data sharing, although we identify certain limitations in blockchain-based access control systems and propose potential solutions. Additionally, this paper provides detailed insights into future research directions in this domain.