Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

Software defined intelligent satellite-terrestrial integrated networks:Insights and challenges

Satellite-Terrestrial integrated Networks(STNs)have been advocated by both academia and industry as a promising network paradigm to achieve service continuity and ubiquity.However,STNs suffer from problems including poor flexibility of network architecture,low adaptability to dynamic environments,the lack of network intelligence,and low resource utilization.To handle these challenges,a Software defined Intelligent STN(SISTN)architecture is introduced.Specifically,the hierarchical architecture of the proposal is described and a distributed deployment scheme for SISTNs controllers is proposed to realize agile and effective network management and control.Moreover,three use cases in SISTNs are discussed.Meanwhile,key techniques and their corresponding solutions are presented,followed by the identification of several open issues in SISTNs including compatibility with existing networks,the tradeoff between network flexibility and performance,and so on.

Stochastic programming based multi-arm bandit offloading strategy for internet of things

In order to solve the high latency of traditional cloud computing and the processing capacity limitation of Internet of Things(IoT)users,Multi-access Edge Computing(MEC)migrates computing and storage capabilities from the remote data center to the edge of network,providing users with computation services quickly and directly.In this paper,we investigate the impact of the randomness caused by the movement of the IoT user on decision-making for offloading,where the connection between the IoT user and the MEC servers is uncertain.This uncertainty would be the main obstacle to assign the task accurately.Consequently,if the assigned task cannot match well with the real connection time,a migration(connection time is not enough to process)would be caused.In order to address the impact of this uncertainty,we formulate the offloading decision as an optimization problem considering the transmission,computation and migration.With the help of Stochastic Programming(SP),we use the posteriori recourse to compensate for inaccurate predictions.Meanwhile,in heterogeneous networks,considering multiple candidate MEC servers could be selected simultaneously due to overlapping,we also introduce the Multi-Arm Bandit(MAB)theory for MEC selection.The extensive simulations validate the improvement and effectiveness of the proposed SP-based Multi-arm bandit Method(SMM)for offloading in terms of reward,cost,energy consumption and delay.The results showthat SMMcan achieve about 20%improvement compared with the traditional offloading method that does not consider the randomness,and it also outperforms the existing SP/MAB based method for offloading.

Efficient Certificateless Authenticated Key Agreement for Blockchain-Enabled Internet of Medical Things

Internet of Medical Things(IoMT)plays an essential role in collecting and managing personal medical data.In recent years,blockchain technology has put power in traditional IoMT systems for data sharing between different medical institutions and improved the utilization of medical data.However,some problems in the information transfer process between wireless medical devices and mobile medical apps,such as information leakage and privacy disclosure.This paper first designs a cross-device key agreement model for blockchain-enabled IoMT.This model can establish a key agreement mechanism for secure medical data sharing.Meanwhile,a certificateless authenticated key agreement(KA)protocol has been proposed to strengthen the information transfer security in the cross-device key agreement model.The proposed KA protocol only requires one exchange of messages between the two parties,which can improve the protocol execution efficiency.Then,any unauthorized tampering of the transmitted signed message sent by the sender can be detected by the receiver,so this can guarantee the success of the establishment of a session key between the strange entities.The blockchain ledger can ensure that the medical data cannot be tampered with,and the certificateless mechanism can weaken the key escrow problem.Moreover,the security proof and performance analysis are given,which show that the proposed model and KA protocol are more secure and efficient than other schemes in similar literature.

A Machine Learning-Based Attack Detection and Prevention System in Vehicular Named Data Networking

Named Data Networking(NDN)is gaining a significant attention in Vehicular Ad-hoc Networks(VANET)due to its in-network content caching,name-based routing,and mobility-supporting characteristics.Nevertheless,existing NDN faces three significant challenges,including security,privacy,and routing.In particular,security attacks,such as Content Poisoning Attacks(CPA),can jeopardize legitimate vehicles with malicious content.For instance,attacker host vehicles can serve consumers with invalid information,which has dire consequences,including road accidents.In such a situation,trust in the content-providing vehicles brings a new challenge.On the other hand,ensuring privacy and preventing unauthorized access in vehicular(VNDN)is another challenge.Moreover,NDN’s pull-based content retrieval mechanism is inefficient for delivering emergency messages in VNDN.In this connection,our contribution is threefold.Unlike existing rule-based reputation evaluation,we propose a Machine Learning(ML)-based reputation evaluation mechanism that identifies CPA attackers and legitimate nodes.Based on ML evaluation results,vehicles accept or discard served content.Secondly,we exploit a decentralized blockchain system to ensure vehicles’privacy by maintaining their information in a secure digital ledger.Finally,we improve the default routing mechanism of VNDN from pull to a push-based content dissemination using Publish-Subscribe(Pub-Sub)approach.We implemented and evaluated our ML-based classification model on a publicly accessible BurST-Asutralian dataset for Misbehavior Detection(BurST-ADMA).We used five(05)hybrid ML classifiers,including Logistic Regression,Decision Tree,K-Nearest Neighbors,Random Forest,and Gaussian Naive Bayes.The qualitative results indicate that Random Forest has achieved the highest average accuracy rate of 100%.Our proposed research offers the most accurate solution to detect CPA in VNDN for safe,secure,and reliable vehicle communication.

Genuine Einstein-Podolsky-Rosen steering of generalized three-qubit states via unsharp measurements

We aim to explore all possible scenarios of(1→2)(where one wing is untrusted and the others two wings are trusted)and(2→1)(where two wings are untrusted,and one wing is trusted)genuine tripartite Einstein-Podolsky-Rosen(EPR)steering.The generalized Greenberger-Horne-Zeilinger(GHZ)state is shared between three spatially separated parties,Alice,Bob and Charlie.In both(1→2)and(2→1),we discuss the untrusted party and trusted party performing a sequence of unsharp measurements,respectively.For each scenario,we deduce an upper bound on the number of sequential observers who can demonstrate genuine EPR steering through the quantum violation of tripartite steering inequality.The results show that the maximum number of observers for the generalized GHZ states can be the same with that of the maximally GHZ state in a certain range of state parameters.Moreover,both the sharpness parameters range and the state parameters range in the scenario of(1→2)steering are larger than those in the scenario of(2→1)steering.

Cryptanalysis and Improvement of Two GHZ-State-Based QSDC Protocols

在一份最近的报纸[J。朝鲜语。Phys。Soc。49 (2006 ) 459 ] ，二 GHZ-state-based 量安全直接通讯协议被介绍。这里，我们指出一个偷听者能利用 GHZ 状态的一个特殊性质，即。“ correlation-elicitable ”到没有在两个协议被检测，获得播送秘密的半信息。特别攻击策略详细被表明。而且，可能的改进被建议，它对这种攻击使协议安全。[从作者抽象]

Cryptanalysis of Quantum Secure Direct Communication and Authentication Scheme via Bell States

The security of the quantum secure direct communication(QSDC)and authentication protocol based on Bell states is analyzed.It is shown that an eavesdropper can invalidate the authentication function,and implement a successful man-in-the-middle attack,where he/she can obtain or even modify the transmitted secret without introducing any error.The particular attack strategy is demonstrated and an improved protocol is presented.

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.

Robustness self-testing of states and measurements in the prepare-and-measure scenario with 3 → 1 random access code

Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(2018)].They realized the self-testing of preparations and measurements in an N → 1(N ≥ 2) random access code(RAC), and provided robustness bounds in a 2 → 1 RAC.Since all N → 1 RACs with shared randomness are combinations of 2 → 1 and 3 → 1 RACs, the3 → 1 RAC is just as important as the 2 → 1 RAC.In this paper, we find a set of preparations and measurements in the3 → 1 RAC, and use them to complete the robustness self-testing analysis in the prepare-and-measure scenario.The method is robust to small but inevitable experimental errors.

Steganalysis and improvement of a quantum steganography protocol via a GHZ_4 state

Quantum steganography that utilizes the quantum mechanical effect to achieve the purpose of information hiding is a popular topic of quantum information. Recently, E1 Allati et al. proposed a new quantum steganography using the GHZ4 state. Since all of the 8 groups of unitary transformations used in the secret message encoding rule change the GHZ4 state into 6 instead of 8 different quantum states when the global phase is not considered, we point out that a 2-bit instead of a 3-bit secret message can be encoded by one group of the given unitary transformations. To encode a 3-bit secret message by performing a group of unitary transformations on the GHZ4 state, we give another 8 groups of unitary transformations that can change the GHZ4 state into 8 different quantum states. Due to the symmetry of the GHZ4 state, all the possible 16 groups of unitary transformations change the GHZ4 state into 8 different quantum states, so the improved protocol achieves a high efficiency.

Performance analysis of diffusion-based decode-and-forward relay with depleted molecule shift keying

The distance-decay effect of molecular signals makes communication range a major challenge for diffusion-based Molecular Communication(MC).To solve this problem,the intermediate nano-machine is deployed as a relay between the transmitter and its intended receiver nano-machines.In this work,we employ the Depleted Molecule Shift Keying(D-MoSK)to model a Decode-and-Forward(DF)relay communication scheme.The closed-form expression of Bit Error Rate(BER)for the concerned DF relay with D-MoSK is derived.Meanwhile,the maximum a posteriori probability,minimum error probability,and maximum likelihood schemes are formulated for data detection.The relationships between BER and other key parameters,including the number of released molecules,receiving radius,and relay position,are investigated in detail.Simulation results show that the proposed scheme can improve communication reliability significantly.Moreover,the performance gain can be maximized by optimizing the position of the relay and the receiving radius.

Coordination of networking and computing: toward new information infrastructure and new services mode

Computing,serving as the cornerstone of information processing,plays a pivotal role in the digital service era.The"network"and"computing,"responsible for information transmission and processing respectively,traditionally belong to different stakeholders and have evolved separately.However,the recent trend toward the coordination and integration of computing and networks has garnered significant attention from both industry and academia.Concepts such as"computility network"and"computing force network"have emerged,and the International Telecommunication Union-Telecommunication Standardization(ITU-T)has initiated efforts to develop standards for the coordination of networking and computing(CNC),focusing on the architecture and framework.

Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G networks.Such hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological innovations.To this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G network.In particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network architecture.In the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information flows.The proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in 6G.It features a lower bandwidth requirement,less redundancy,and more accurate intent identification.We also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.

A Survey on Information-Centric Networking: Rationales, Designs and Debates

The basic function of the Internet is to delivery data(what) to serve the needs of all applications. IP names the attachment points(where) to facilitate ubiquitous interconnectivity as the current way to deliver data. The fundamental mismatch between data delivery and naming attachment points leads to a lot of challenges, e.g., mapping from data name to IP address, handling dynamics of underlying topology, scaling up the data distribution, and securing communication, etc. Informationcentric networking(ICN) is proposed to shift the focus of communication paradigm from where to what, by making the named data the first-class citizen in the network, The basic consensus of ICN is to name the data independent from its container(space dimension) and session(time dimension), which breaks the limitation of point-to-point IP semantic. It scales up data distribution by utilizing available resources, and facilitates communication to fit diverse connectivity and heterogeneous networks. However, there are only a few consensuses on the detailed design of ICN, and quite a few different ICN architectures are proposed. This paper reveals the rationales of ICN from the perspective of the Internet evolution, surveys different design choices, and discusses on two debatable topics in ICN, i.e.,self-certifying versus hierarchical names, and edge versus pervasive caching. We hope this survey helps clarify some mis-understandings on ICN and achieve more consensuses.

Performance analysis and comparison of PoW,PoS and DAG based blockchains

In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application.To this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure probability.The results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load conditions.In addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.

Probabilistic teleportation of multi-particle partially entangled state

Utilizing the generalized measurement described by positive operator-wlued measure, this paper comes up with a protocol for teleportation of an unknown multi-particle entangled （GHZ） state with a certain probability. The feature of the present protocol is to weaken requirement for the quantum channel initially shared by sender and receiver. All unitary transformations performed by receiver are summarized into a formula. On the other hand, this paper explicitly constructs the efficient quantum circuits for implementing the proposed teleportation by means of universal quantum logic operations in quantum computation.

Joint Design of Coalition Formation and Semi-Blind Channel Estimation in Fog Radio Access Networks

Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance.Thus,a joint cluster formation and channel estimation scheme is proposed in this paper.Considering research remote radio heads(RRHs)centred serving scheme,a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation.As the cost influences to the necessary consumption of training length and estimation error.Particularly,an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm,where the channel estimation process is initialized by subspace method with lower pilot length.Finally,the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.

Implementation Framework and Validation of Cluster-Nuclei Based Channel Model Using Environmental Mapping for 6G Communication Systems

With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.