The Role of Private Blockchain Architectures and Smart Contracts for Decentralized 5G Militarized Networks

Packet retransmissions due to packet losses reduce transmission performance in wireless networks obviously. Multi-hop wireless networks suffer from packet losses more than one-hop wireless networks. High bit-error rate of wireless channel and frequent channel collision due to shared channel are the most important ingredients of packet loss in multi-hop wireless networks. When bit error rate is between 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ~10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> , fragment size control is efficient to enhance transmission performance. After analyzing the packet loss reason in wireless mesh networks, a prediction-based link-layer dynamic frame fragmentation and aggregation scheme called PDFA is proposed for 802.11-based wireless mesh networks. The size of sending fragment is optimized based on the prediction of channel BER. Simulation experiments validate that PDFA enhances transmission performance in wireless mesh networks efficiently.

Blockchain is a decentralized cryptocurrency framework which has gained considerable attention in research and many industries. Ethereum is an implementation based on blockchain technology. Ethereum blockchain offers smart contracts, a piece of program codes which can execute and record the transactions in blockchain. Users can use smart contracts to create their own tokens based on ERC-20 standard, and token smart contracts have been used to manage and transfer tokens, carrying millions dollars worth of virtual currencies. However, keeping token smart contracts secure can be difficult. When smart contracts are deployed on Ethereum successfully, they cannot be changed. Due to the openness of Ethereum, both users and attackers can invoke contracts. So errors in smart contracts have led and will lead to a loss. For example, the DAO bug led to a 60 million US dollar loss in June 2016. Therefore, the researches on security of smart contracts are urgently important. In this paper, we use a formal approach to verify smart contracts. We apply formal verification on a concrete smart contract example, BNB contract, which is one of the most popular token contracts. We analyze the contract and discover the two attributes in the contract, one is transfer attribute involving the functions of transferring tokens operations, and the other is owner attribute which involves the authority of contract owner. We verify these two attributes respectively. We model the contract using SAPIC, the applied pi calculus and then verify by Tamarin prover. We specify the processes of modeling and verifying. The results show we cannot find an attack path. The research method reduces the complexity of verifying smart contracts and can be used to analyze complex contracts.

Smart contracts on the blockchain – A bibliometric analysis and review

As blockchain technology advances, so has the deployment of smart contracts on blockchain platforms, making it exceedingly challenging for users to explicitly identify application services. Unlike traditional contracts, smart contracts are not written in a natural language, making it difficult to determine their provenance. Automatic classification of smart contracts offers blockchain users keyword-based contract queries and a streamlined effective management of smart contracts. In addition, the advancement in smart contracts is accompanied by security challenges, which are generally caused by domain-specific security breaches in smart contract implementation. The development of secure and reliable smart contracts can be extremely challenging due to domain-specific vulnerabilities and constraints associated with various business logics. Accordingly, contract classification based on the application domain and the transaction context offers greater insight into the syntactic and semantic properties of that class. However, despite initial attempts at classifying Ethereum smart contracts, there has been no research on the identification of smart contracts deployed in transactive energy systems for energy exchange purposes. In this article, in response to the widely recognized prospects of blockchain-enabled smart contracts towards an economical and transparent energy sector, we propose a methodology for the detection and analysis of energy smart contracts. First, smart contracts are parsed by transforming code elements into vectors that encapsulate the semantic and syntactic characteristics of each term. This generates a corpus of annotated text as a balanced, representative collection of terms in energy contracts. The use of a domain corpus builder as an embedding layer to annotate energy smart contracts in conjunction with machine learning models results in a classification accuracy of 98.34%. Subsequently, a source code analysis scheme is applied to identified energy contracts to uncover patterns in code segment distribution, predominant adoption of certain functions, and recurring contracts across the Ethereum network.

The rise of digital currency and the public ledger Block Chain has led to the development of a new type of electronic contract known as "smart contracts." For these contracts to be considered valid, they must adhere to traditional contract rules and be concluded without any impediments. Once written, encrypted, and signed, smart contracts are recorded in the Block Chain Ledger, providing transparent and secure record-keeping. Smart contracts offer several benefits, including their ability to execute automatically without requiring human intervention, their provision of public visibility of contract provisions on the Block Chain, their avoidance of financial crimes like Money Laundering, and their prevention of contract abuses. However, disputes arising from smart contracts still require human intervention, presenting unique challenges in enforcing these contracts, such as evidentiary issues, enforceability of waivers of defenses, and jurisdictional and choice-of-law considerations. Due to the novel nature of smart contracts, there are currently no standardized regulations that apply to them. Countries that have approved them have turned to customary law to legitimize their use. The Delphi method was used to identify critical success factors for applying blockchain transactions in a manufacturing company. Stepwise Weight Assessment Ratio Analysis (SWARA) was then utilized to determine the most influential factors. The proposed methodology was implemented, and results show that the most influential factors for the successful application of blockchain transactions as smart contracts in a manufacturing company are: turnover, the counter argument, vision, components for building, and system outcome quality. Conversely, connections with government entities and subcontractors, and the guarantee of quality have the least influence on successful implementation. These findings can contribute to the development of a legal framework for smart contracts in a manufacturing company.

The rise of digital currency and the public ledger Block Chain has led to the development of a new type of electronic contract known as "smart contracts." For these contracts to be considered valid, they must adhere to traditional contract rules and be concluded without any impediments. Once written, encrypted, and signed, smart contracts are recorded in the Block Chain Ledger, providing transparent and secure record-keeping. Smart contracts offer several benefits, including their ability to execute automatically without requiring human intervention, their provision of public visibility of contract provisions on the Block Chain, their avoidance of financial crimes like Money Laundering, and their prevention of contract abuses. However, disputes arising from smart contracts still require human intervention, presenting unique challenges in enforcing these contracts, such as evidentiary issues, enforceability of waivers of defenses, and jurisdictional and choice-of-law considerations. Due to the novel nature of smart contracts, there are currently no standardized regulations that apply to them. Countries that have approved them have turned to customary law to legitimize their use. The Delphi method was used to identify critical success factors for applying blockchain transactions in a manufacturing company. Stepwise Weight Assessment Ratio Analysis (SWARA) was then utilized to determine the most influential factors. The proposed methodology was implemented, and results show that the most influential factors for the successful application of blockchain transactions as smart contracts in a manufacturing company are: turnover, the counter argument, vision, components for building, and system outcome quality. Conversely, connections with government entities and subcontractors, and the guarantee of quality have the least influence on successful implementation. These findings can contribute to the development of a legal framework for smart contracts in a manufacturing company.

Fabric is currently the most popular consortium chain platform with a modular architecture that provides high security, elasticity, flexibility and scalability. Smart contracts realize the automatic execution of transactions and the operation of reconciliation data. The Fabric platform supports general programming languages ​​to write smart contracts. However, in the development process of smart contracts, due to insufficient understanding of the underlying operating logic of smart contracts, developers are prone to introduce some risky operations, resulting in a mismatch between the execution logic of smart contracts and business logic, resulting in a lot of losses. The read-after-write risk is a relatively complex and common security risk in smart contracts. Currently, many detection tools cannot detect this risk. There is an urgent need for a solution that can quickly and accurately detect the read-after-write risk in smart contracts. This paper proposes a static analysis smart contract read-after-write risk detection method based on key methods and call chains. The scheme extracts key method patterns on the abstract syntax tree, identifies and locates key methods with risks, greatly reduces the interference of useless nodes on detection, and realizes rapid detection. By constructing the key method call chain, the real call scene is restored according to the call type and attribute of the key method. After experimental verification, compared with the current popular smart contract risk detection tool Revive^CC, the tool proposed in this paper has higher detection accuracy and can more accurately locate the read-after-write risk in smart contracts.

Wireless networking is a crucial component of communication in this era of digitization. The key characteristics that determine a wireless network's performance are smooth connectivity, quicker communication, and increased customer satisfaction. Scalability deals with the erratic workload and new resources that are added to the network. Scalability is crucial for both Quality of Experience (QoE) and Quality of Service (QoS) in such a power-constrained environment because wireless devices are battery-operated. Managing power consumption and network performance simultaneously in scalable networking scenario is quite challenging, especially during handover. This research proposed a methodology to assess the impact of scalability on wireless node power consumption and network performance in order to develop energy-efficient handoff mechanisms. The Type-I and Type-II wireless node sets were used between the WiFI and WiMAX networks in a vertical handover scenario. In the study, two distinct scalability scenarios were taken into account. Three distinct voltage levels—cutoff voltage, nominal voltage, and charge voltage —had been used to examine the consumption of power. Throughput, residual energy, and Packet Delivery Ratio (PDR) were computed to examine the network's performance in a scalable, power-constrained context. Two different scalability scenarios were considered in the study. The power consumption was investigated using three different voltage levels: charge voltage, nominal voltage, and cutoff voltage. The network's performance under scalable, power-constrained conditions was investigated by computing throughput, packet delivery ratio (PDR), and residual energy. The result obtained in the study showed the variation in battery drainage of wireless nodes under the effect of various scalability factors. This study will provide a blueprint for developing novel algorithms which eventually will improvise network performance and strengthen the base of Green Networking.

Blockchain technology along with Internet of Things (IoT) and Cloud Computing is expected to cause disruption in the existing business processes at unprecedented scale. Smart Contracts which represent business logic are consolidated by blockchain architecture. A smart contract is a self-executing program that may be triggered on events generated by IoT sensors, actuators or tags. Blockchain and smart contracts which find their optimum suitability in multiparty arrangements are anticipated to bring a paradigm shift in the domains of Supply-chain and logistics. This paper presents a comprehensive analysis of the disruptive innovation happening in the logistics processes due to blockchain, smart contracts and Internet of Things. We highlight the some of the most important Key Performance Indicators (KPIs) of the logistics domain being positively affected due to this digital disruption and the required characteristics in the blockchain technologies for this paradigm shift to take place.

The post-deployment challenges in developing and upgrading blockchain smart contracts necessitate a high level of accuracy in their development and business logic. However, current methodologies for verifying the business logic of smart contracts frequently fail to address their alignment with end-user business requirements. This paper introduces a two-step language transformation process to bridge this gap. Initially, we establish a transformation rule from the Business Process Model and Notation (BPMN) to Prolog, enabling the translation of business processes into a Prolog representation. This step not only validates the business process logic but also ensures it meets user specifications. Subsequently, we introduce a transformation rule from the BPMN to Go, which facilitates the transformation of the BPMN model, once validated, into a Go language smart contract. To enhance usability, we have engineered a dedicated tool that streamlines this transformation process. We present a case study involving a banking loan process to exemplify the utility of our tool in creating BPMN diagrams, conducting requirement and syntax validations, and effecting the transformation to Go smart contracts. The case study and empirical results suggest that our methodology and the accompanying tool mitigate the complexities inherent in smart contract development. They also ensure the fidelity of business logic to user demands, thereby promoting the broader adoption of blockchain smart contract technology.

A survey on routing algorithms for wireless Ad-Hoc and mesh networks

Infostation, hotspot, and drive‐thru internet are examples of sparse coverage‐based wireless networks. These wireless communication networks provide low‐cost, delay insensitive high data rate services intermittently with discontinuous coverage. Radio propagation parameters, velocity of the user, distance between the user, and access point are the key factors that affect the throughput and the amount of information downloaded from such sparse coverage‐based wireless networks. To evaluate the performance of such wireless communication networks analytically the impact of above mentioned factors can be modeled with simplified relationship model such as received signal strength versus distance or signal to noise ratio versus throughput. In the paper, we exploit the relationship between throughput and distance and develop two throughput distance relationship models to evaluate the performance of multirate wireless networks. These two throughput distance relationship models are used in calculation of average throughput as well as downloaded file size. Numerical values are presented for the IEEE 802.11n standard. The numerical results verify that the new proposed technique can be used as an alternative to the simulations to evaluate the performance of sparse coverage‐based wireless networks.

Transmission power plays a crucial role in the design and performance of wireless networks. The issue is therefore complex since an increase in transmission power implies that a high quality signal is received at the receiver and hence an increase in channel capacity. Conversely, due to the shared nature of the wireless medium an increase in transmission power also implies high interference in the surrounding region and hence a quadratic reduction in the capacity of wireless networks. Recent literatures indicate that employing multiple channels can mitigate the negative effects of wireless interference and thus greatly improve the overall network capacity. Therefore, it is worth investigating the effect of exploiting power on the capacity of multi-channel multi-radio (MC-MR) wireless networks. Specifically, in this paper we address the following questions: (a) Can we maximize the capacity of MC-MR wireless networks by exploiting power? (b) Under what criteria can we increase the transmission power of the nodes in a MC-MR network? %In this paper, we address these issues and investigate the impact of employing high transmission power and multiple channels in a static wireless network when node placements are chosen arbitrarily. When $n$ nodes each with $m$ half-duplex interfaces are optimally deployed in a torus of unit area, traffic patterns are optimally assigned, each transmission's range is optimally chosen and in the presence of $c$ channels, we show that in contrast to the setting where nodes transmit at minimum power level $P_0$ the transport capacity, measured in bit-meters per second, of MC-MR network exploiting power is increased by $\Theta(\frac{c}{c_{min}})$ in region $c_{min} mn/2$ when nodes tune to transmit power level of $P_0(\frac{c}{c_{min}})^(\frac{\alpha}{2})$ and $P_0n^{\frac{\alpha}{2}}$ respectively. Where $c_{min}$ is the minimum number of channels required to achieve conflict-free transmissions in a network. Our analysis also sheds light into several insights that designers may want to consider to improve the performance of energy-efficient bandwidth-constrained wireless networks.

Wireless adhoc networks consist of users that want to communicate with each other over a shared wireless medium. The users have transmitting and receiving capabilities but there is no additional infrastructure for assisting communication. This is in contrast to existing wireless systems, cellular networks for example, where communication between wireless users heavily relies on an additional infrastructure of base stations connected with a high-capacity wired backbone. The fact that they are infrastructureless makes wireless adhoc networks inexpensive, easy to build and robust but at the same time technically more challenging. The fundamental challenge is how to deal with interference: many simultaneous transmissions have to be accommodated on the same wireless channel when each of these transmissions constitutes interference for the others, degrading the quality of the communication. The traditional approach to wireless adhoc networks is to organize users so that they relay information for each other in a multi-hop fashion. Such multi-hopping strategies face scalability problems at large system size. As shown by Gupta and Kumar in their seminal work in 2000, the maximal communication rate per user under such strategies scales inversely proportional to the square root of the number of users in the network, hence decreases to zero with increasing system size. This limitation is due to interference that precludes having many simultaneous point-to-point transmissions inside the network. In this thesis, we propose a multiscale hierarchical cooperation architecture for distributed MIMO communication in wireless adhoc networks. This novel architecture removes the interference limitation at least as far as scaling is concerned: we show that the per-user communication rate under this strategy does not degrade significantly even if there are more and more users entering into the network. This is in sharp contrast to the performance achieved by the classical multi-hopping schemes. However, the overall picture is much richer than what can be depicted by a single scheme or a single scaling law formula. Nowadays, wireless adhoc networks are considered for a wide range of practical applications and this translates to having a number of system parameters (e.g., area, power, bandwidth) with large operational range. Different applications lie in different parameter ranges and can therefore exhibit different characteristics. A thorough understanding of wireless adhoc networks can only be obtained by exploring the whole parameter space. Existing scaling law formulations are insufficient for this purpose as they concentrate on very small subsets of the system parameters. We propose a new scaling law formulation for wireless adhoc networks that serves as a mathematical tool to characterize their fundamental operating regimes. For the standard wireless channel model where signals are subject to power path-loss attenuation and random phase changes, we identify four qualitatively different operating regimes in wireless adhoc networks with large number of users. In each of these regimes, we characterize the dependence of the capacity on major system parameters. In particular, we clarify the impact of the power and bandwidth limitations on performance. This is done by deriving upper bounds on the information theoretic capacity of wireless adhoc networks in Chapter 3, and constructing communication schemes that achieve these upper bounds in Chapter 4. Our analysis identifies three engineering quantities that together determine the operating regime of a given wireless network: the short-distance signal-to-noise power ratio (SNRs), the long-distance signal-to-noise power ratio (SNRl) and the power path-loss exponent of the environment. The right communication strategy for a given application is dictated by its operating regime. We show that conventional multi-hopping schemes are optimal when the power path-loss exponent of the environment is larger than 3 and SNRs ≪ 0 dB. Such networks are extremely power-limited. On the other hand, the novel architecture proposed in this thesis, based on hierarchical cooperation and distributed MIMO, is the fundamentally right strategy for wireless networks with SNRl ≫ 0 dB. Such networks experience no power limitation. In the intermediate cases, captured by the remaining two operating regimes, neither multi-hopping nor hierarchical-MIMO achieves optimal performance. We construct new schemes for these regimes that achieve capacity. The proposed characterization of wireless adhoc networks in terms of their fundamental operating regimes, is analogous to the familiar understanding of the two operating regimes of the point-to-point additive white Gaussian noise (AWGN) channel. From an engineering point of view, one of the most important contributions of Shannon's celebrated capacity formula is to identify two qualitatively different operating regimes on this channel. Determined by its signal-to-noise power ratio (SNR), an AWGN channel can be either in a bandwidth-limited (SNR ≫ 0 dB) or a power-limited (SNR ≪ 0 dB) regime. Communication system design for this channel has been primarily driven by the operating regime one is in.

Blockchain shows great potential to be applied in wireless IoT ecosystems for establishing the trust and consensus mechanisms without central authority's involvement. Based on RAFT consensus mechanism, this letter investigates the security performance of wireless blockchain networks in the presence of malicious jamming. We first map and model the blockchain transaction as a wireless network composed of uplink and downlink transmissions by assuming the follower nodes' position as a Poisson Point Process (PPP) with selected leader location. The probability of achieving successful blockchain transactions is derived and verified by extensive simulations. The results provide analytical guidance for the practical deployment of wireless blockchain networks.