Renewable energy projects, particularly wind and solar farms, have garnered significant attention as a potential solution to global energy challenges. Despite the energy production obstacles, the steady availability of fossil fuels continues to compete due to established distribution systems, as societies increasingly rely on electricity. Hydrogen fuel emerges as a promising avenue for energy production, storage, and distribution, involving converting surplus renewable electricity into hydrogen through electrolysis, storing it, and distributing it. Our novel approach leverages blockchain technology to enhance the efficiency and traceability of hydrogen fuel production, offering a unique synergy of transparency, security, and decentralized governance. We showcase its viability and effectiveness using the ERC-1155 token standard to tokenize renewable resources and convert them into hydrogen fuel. Within our tokenized fuel blockchain architecture, we simulate the forecasted growth in hydrogen production and vehicle demand, highlighting our approach's efficiency, traceability, and transparency. This integration showcases the potential for a sustainable hydrogen fuel ecosystem. The gas consumption data analysis indicates that the daily gas consumption remains below 194 million Gas for refilling 3245 vehicles (including the cost of one-time contract deployment), demonstrating the feasibility and efficiency of our approach.

Peak mitigation is of interest to power companies as peak periods may require the operator to over provision supply in order to meet the peak demand. Flattening the usage curve can result in cost savings, both for the power companies and the end users. Integration of renewable energy into the energy infrastructure presents an opportunity to use excess renewable generation to supplement supply and alleviate peaks. In addition, demand side management can shift the usage from peak to off-peak times and reduce the magnitude of peaks. In this work, we present a data driven approach for incentive-based peak mitigation. Understanding user energy profiles is an essential step in this process. We begin by analysing a popular energy research dataset published by the Ausgrid corporation. Extracting aggregated user energy behavior in temporal contexts and semantic linking and contextual clustering give us insight into consumption and rooftop solar generation patterns. We implement, and performance test a blockchain-based prosumer incentivization system. The smart contract logic is based on our analysis of the Ausgrid dataset. Our implementation is capable of supporting 792,540 customers with a reasonably low infrastructure footprint.

Abstract The rapid development of internet of things (IoT) is to be the next generation of the IoT devices are a simple target for attackers due to the lack of security. Attackers can easily hack the IoT devices that can be used to form botnets, which can be used to launch distributed denial of service (DDoS) attack against networks. Botnets are the most dangerous threat to the security systems. Software‐defined networking (SDN) is one of the developing filed, which introduce the capacity of dynamic program to the network. Use the flexibility and multidimensional characteristics of SDN used to prevent DDoS attacks. The DDoS attack is the major attack to the network, which makes the entire network down, so that normal users might not avail the services from the server. In this article, we proposed the DDoS attack detection model based on SDN environment by combining support vector machine classification algorithm is used to collect flow table values in sampling time periods. From the flow table values, the five‐tuple characteristic values extracted and based on it the DDoS attack can be detected. Based on the experimental results, we found the average accuracy rate is 96.23% with a normal amount of traffic flow. Proposed research offers a better DDoS detection rate on SDN.

Regenerating codes based on the approach of interference alignment for wireless interference channel achieve the cut-set bound for distributed storage systems. These codes provide data reliability, and perform efficient exact node repair when some node fails. Interference alignment as a concept is especially important to improve the repair efficiency of a failed node in a minimum storage regenerating (MSR) code. In addition it can improve the stored data security in presence of passive intruders. In this paper we construct a new code resilient against a threat model where a passive eavesdropper can access the data stored on a subset of nodes and the downloaded data during the repair process of a subset of failed nodes. We achieve an optimal secrecy capacity for the new explicit construction of MSR interference alignment code. Hence, we show that the eavesdropper obtains zero information from the original message stored across the distributed storage, i.e., a perfect secrecy.

In this study, the authors present an infinite‐series‐based approach for the performance analysis of n ‐diversity receivers operating over Rayleigh correlated fading channels in the presence of correlated phase difference. The performance analysis is based on error probability and signal‐to‐noise ratio (SNR) criteria. The authors propose a model to investigate the impact of phase difference between n ‐correlated Rayleigh fading channels. We have derived the closed form expression for phase distribution in a Rayleigh fading environment with the help of some statistical properties. The authors have also derived the joint density function of phase difference and its associated correlated envelopes. With the help of probability distribution function, the authors have observed two cases of equally spaced and loosely spaced antennas and showed that imperfect phase estimation lowers the SNR. The authors also present statistical analysis and the effectiveness of the proposed approximation to predict the variance of the phase difference. The authors have performed Monte Carlo simulation for a subcarrier‐based spectrum to analyse error probability with respect to phase and correlation.

This paper proposes code for secure distributed storage systems (sDSS), called secure shortened product-matrix minimum storage regenerating code (PM-ssMSR). The code uses shortening technique applied on the mother code, product-matrix minimum storage regenerating (PM-MSR), for maintenance of the DSS efficiency and two different methods for achieving the system security. The first method enables by performing random keys technique on the PM-ssMSR code to guarantee perfectly secure system. Hence, the second technique using an outer code achieves weakly secure system. For both cases, their information-theoretic secrecy is proven and is shown that the weakly secure code achieve higher secrecy bandwidth than the perfectly secure code.

The perceptual adaptation of the image (PAI) is introduced by inspiration from Chevreul–Mach Bands (CMB) visual phenomenon. By boosting the CMB assisting illusory effect on boundaries of the regions, PAI adapts the image to the perception of the human visual system and thereof increases the quality of the image. PAI is proposed for application to standard images or the output of any image processing technique. For the implementation of the PAI on the image, an algorithm of morphological filters (MFs) is presented, which geometrically adds the model of CMB effect. Numerical evaluation by improvement ratios of four no-reference image quality assessment (NR-IQA) indexes approves PAI performance where it can be noticeably observed in visual comparisons. Furthermore, PAI is applied as a postprocessing block for classical morphological filtering, weighted morphological filtering, and median morphological filtering in cancelation of salt and pepper, Gaussian, and speckle noise from MRI images, where the above specified NR-IQA indexes validate it. PAI effect on image enhancement is benchmarked upon morphological image sharpening and high-boost filtering.

The asynchronous capacity region of memoryless multiple-access channels is the union of certain polytopes. It is well known that vertices of such polytopes may be approached via a technique called successive decoding. It is also known that an extension of successive decoding applies to the dominant face of such polytopes. The extension consists of forming groups of users in such a way that users within a group are decoded jointly whereas groups are decoded successively. This paper goes one step further. It is shown that successive decoding extends to every face of the aforementioned polytopes. The group composition as well as the decoding order for all rates on a face of interest is obtained from a label assigned to that face. From the label, one can extract a number of structural properties, such as the dimension of the corresponding face and whether or not two faces intersect. Expressions for the number of faces of any given dimension are also derived from the labels.

A simple four node network in which cooperation improves the information-theoretic secrecy is studied. The channel consists of two senders, a receiver, and an eavesdropper. One or both senders transmit confidential messages to the receiver, while the eavesdropper tries to decode the transmitted message. The main result is the derivation of a newly achievable rate-equivocation region that is shown to be larger than a rate-equivocation region derived by Lai and El Gamal for the relay-eavesdropper channel. When the rate of the helping interferer is zero, the new rate-equivocation region reduces to the capacity-equivocation region over the wire-tap channel; hence, the new achievability scheme can be seen as a generalization of a coding scheme proposed by Csiszár and Körner.

Security is an important aspect for the future wireless networks. Since the number of network nodes increases constantly, and, in addition, the networks are decentralized and ad-hoc in nature, it becomes more challenging to apply the current cryptographic methods that require exchange of keys between the communicating parties. Information-theoretic secrecy is an emerging security field that explores the possibility of achieving perfect secrecy data transmission between the intended network nodes, while possible malicious nodes (also called eavesdroppers) are kept ignorant of the transmitted information. In other words, that is the ability of the physical layer to provide security (beside the reliability) of the transmitted (broadcasted) data. For that reason, it is often called physical layer security. In this paper we observe how a simple cooperative network with one relay node can improve the physical layer security by decreasing the area in which the eavesdropper can reside and listen to the information transmitted to the destination. This region is called vulnerability region and we provide its characterization. Under certain conditions, the vulnerability region vanishes, which makes our wireless system perfectly secure for any position of the eavesdropper within the wireless network.

In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.

Physical layer security is an emerging security area that explores possibilities of achieving perfect secrecy data transmission between the intended network nodes, while possible malicious nodes that eavesdrop the communication obtain zero information. The so-called secrecy rate can be improved using friendly jammers that introduce extra interference to the eavesdroppers. Here, we investigate the interaction between the multiple source-destination links and a friendly jammer who assists by ''masking" the eavesdropper. In order to obtain a distributed solution, one possibility is to introduce a distributed auction theoretic approach. The auction is defined such that the source-destination links provide bids for the jammer to interfere the eavesdropper, therefore increasing their secrecy capacities. We propose a distributed auction using the share auction and iteratively updating the bids. To compare with the performances, we construct a centralized solution and a VCG auction, which cannot be implemented in practice. Our analysis and simulation results show the effectiveness of friendly jamming and convergence of the proposed scheme. The distributed game solution is shown to have similar performances to those of the centralized ones.

Physical layer security is an emerging security field that explores the possibilities of achieving perfect secrecy data transmission between the intended network nodes, while possible malicious nodes that eavesdrop the communication obtain zero information. In this paper, we observe how node cooperation improves the physical layer security of a simple wireless network by reducing the surface of the geographical area in which the malicious nodes can listen to the transmitted data from the source to the destination. Our analysis and simulation results show a dramatic improvement even by cooperation with only one relay node. The improvement gets better by adding more cooperating nodes. We also observe that if cooperating nodes are closer to the line that connects the source and the destination node, the region in which the malicious node can profit from the eavesdropping gets smaller.

In this paper we initially study degraded relay channels with finite-length intersymbol interference (ISI). For such channels, we show that the decode-and-forward strategy achieves the capacity, and prove a special structure for the capacity achieving distributions of the source and relay signals. We also prove that a general memoryless relay channel used with delayed feedback from the destination node to the relay node is an instance of a degraded relay channel with ISI, and observe that the delayed feedback from the destination node to the relay node does not decrease the capacity compared to instantaneous feedback. In all cases where the channel is used with delayed feedback from the destination node to the relay node the decode-and-forward scheme is optimal and the capacity is not decreased by delaying the feedback from the destination node. We extend these results to general (non-degraded) relay channels with ISI to obtain upper and lower bounds on their capacities.

The memoryless noncoherent single-input-single-output (SISO) Rayleigh-fading channel is considered. Closed-form expressions are derived for the mutual information between the output and the input of this channel when the input magnitude distribution is discrete and is restricted to having two mass points. It is subsequently shown how these expressions can be used to obtain closed-form expressions for the capacity of this channel for signal to noise ratio (SNR) values of up to approximately 0 dB, and a tight capacity lower bound for SNR values between 0 dB and 10 dB. The expressions for the channel capacity and its lower bound are given as functions of a parameter which can be obtained via numerical root-finding algorithms.

It is well-known that the capacity region of an M-user Gaussian multiple access channel is an M-dimensional polytope and the capacity region of a general discrete memoryless multiple-access channel contains a union of such polytopes. An expression for the number of vertices, edges, and more generally faces of any dimension D, of the capacity region of a Gaussian multiple access channel is derived in this paper.