Network virtualization (NV) is pushed forward by its proponents as a crucial attribute of next generation network, aiming at overcoming the gradual ossification of current networks, particularly to the worldwide Internet. Through virtualization, multiple customized virtual networks (VNs), requested by users, are allowed to coexist on the underlying substrate networks (SNs). In addition, the virtualization scheme contributes to sharing underlying physical resources simultaneously and seamlessly. However, multiple technical issues still stand in the way of NV successful implementation. One key technical issue is virtual network embedding (VNE), known as the resource allocation problem for NV. This paper conducts a survey of embedding algorithms for VNE problem. At first, the NV business model for VNE problem is presented. Then, the latest VNE problem description is presented. Main performance metrics for evaluating embedding algorithms are also involved. Afterwards, existing VNE algorithms are detailed, according to the novel proposed category approach. Next, key future research aspects of embedding algorithms are listed out. Finally, the paper is briefly concluded.

Dynamic spectrum access (DSA) in cognitive radio (CR) networks became a challenging research area recently. In CR technology, the DSA between primary users (PUs) and secondary users (SUs) simultaneously can be achieved without degrading the performance of the PUs by SUs interference. This can be achieved by donating incentive power to the PUs in order to compensate the interference caused by the SUs. Consequently, PUs allow SUs to share the spectrum. In this paper, orthogonal codes-based dynamic spectrum access (OC-DSA) technique is proposed. OC-DSA technique employs orthogonality between PUs and SUs transmitted data symbols in addition to the incentive power donation. Compared to other techniques, the proposed technique uses a simple encoder at the SU network for the same PU network infrastructure. By applying orthogonal codes, the interference caused by SUs is canceled and hence the donated power to incentivize the PUs is reduced. Also, the SU packet rate is increased significantly. The simulation results show that the proposed technique provides effective improvements over other existing techniques in the signal strength and the bit error rate performance of both the PU network and the SU network at the receiver side. Moreover, the proposed technique requires less donated power to incentivize the PU and has higher packet rate.

In this paper, proportional fairness (PF)-based energy-efficient power allocation is studied for multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. In our schemes, statistical channel state information (CSI) is utilized for perfect CSI is impossible to achieve in practice. PF is used to balance the transmission efficiency and user fairness. Energy efficiency (EE) is formulated under basic data rate requirements and maximum transmitting power constraints. Due to the non-convex nature of EE, a two-step algorithm is proposed to obtain sub-optimal solution with a low complexity. Firstly, power allocation is determined by golden section search for fixed power. Secondly total transmitting power is determined by fractional programming method in the feasible regions. Compared to the performance of MIMO-NOMA without PF constraint, fairness is obtained at expense of decreasing of EE.

The objective of the recently proposed fuzzy based hierarchical routing protocol F-SCH is to improve the lifetime of a Wireless Sensor Network. Though the performance of F-SCH is better than LEACH, the randomness in CH selection inhibits it from attaining enhanced lifetime. CBCH ensures maximum network lifetime when CH is close to the centroid of the cluster. However, for a widely distributed network, CBCH results in small sized clusters increasing the inter cluster communication cost. Hence, with an objective to enhance the network lifetime, a fuzzy based two-level hierarchical routing protocol is proposed. The novelty of the proposal lies in identification of appropriate parameters used in Cluster Head and Super Cluster Head selection. Experiments for different network scenarios are performed through both simulation and hardware to validate the proposal. The performance of the network is evaluated in terms of Node Death. The proposal is compared with F-SCH and the results reveal the efficacy of the proposal in enhancing the lifetime of network.

There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from underground to aboveground. The second is an underground medium such as tunnel, cave etc. and the data is transmitted from underground to the aboveground through partially solid medium. The quality of communication is greatly influenced by the humidity of the soil in both environments. The placement of wireless underground sensor nodes at hard-to-reach locations makes energy efficient work compulsory. In this paper, rule based collector station selection scheme is proposed for lossless data transmission in underground sensor networks. In order for sensor nodes to transmit energy-efficient lossless data, rule-based selection operations are carried out with the help of fuzzy logic. The proposed wireless underground sensor network is simulated using Riverbed software, and fuzzy logic-based selection scheme is implemented utilizing Matlab software. In order to evaluate the performance of the sensor network; the parameters of delay, throughput and energy consumption are investigated. Examining performance evaluation results, it is seen that average delay and maximum throughput are accomplished in the proposed underground sensor network. Under these conditions, it has been shown that the most appropriate collector station selection decision is made with the aim of minimizing energy consumption.

In the precision positioning system, NLOS (Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and positioning accuracy. So, in the NLOS environment, it has an important role to eliminate the clock synchronization problem in the positioning system. In order to solve this problem, this paper proposes an improved Kalman filter localization method NLOS-K (Non Line of Sight-Kalman filter). First, the maximum likelihood estimation algorithm is used to iterate. Then, the Kalman filter algorithm is implemented and the Kalman gain matrix is redefined. The clock drift is compensated so that the clock between the master and slave base stations remains synchronized. The experimental results show that in the non-line-of-sight environment, compared with other algorithms, the positioning accuracy error of the improved algorithm is about 5 cm, and the accuracy compared with other algorithms is 97%. In addition, the influence of bandwidth and spectral density on the method is analyzed, and the accuracy and stability of positioning are improved as a whole.

Hardware Trojan (HT) refers to a special module intentionally implanted into a chip or an electronic system. The module can be exploited by the attacker to achieve destructive functions. Unfortunately the HT is difficult to detecte due to its minimal resource occupation. In order to achieve an accurate detection with high efficiency, a HT detection method based on the electromagnetic leakage of the chip is proposed in this paper. At first, the dimensionality reduction and the feature extraction of the electromagnetic leakage signals in each group (template chip, Trojan-free chip and target chip) were realized by principal component analysis (PCA). Then, the Mahalanobis distances between the template group and the other groups were calculated. Finally, the differences between the Mahalanobis distances and the threshold were compared to determine whether the HT had been implanted into the target chip. In addition, the concept of the HT Detection Quality (HTDQ) was proposed to analyze and compare the performance of different detection methods. Our experiment results indicate that the accuracy of this detection method is 91.93%, and the time consumption is 0.042s in average, which shows a high HTDQ compared with three other methods.

Blockchain with these characteristics of decentralized structure, transparent and credible, time-series and immutability, has been considering as a promising technology. Consensus algorithm as one of the core techniques of blockchain directly affects the scalability of blockchain systems. Existing probabilistic finality blockchain consensus algorithms such as PoW, PoS, suffer from power consumptions and low efficiency; while absolute finality blockchain consensus algorithms such as PBFT, HoneyBadgerBFT, could not meet the scalability requirement in a large-scale network. In this paper, we propose a novel optimized practical Byzantine fault tolerance consensus algorithm based on EigenTrust model, namely T-PBFT, which is a multi-stage consensus algorithm. It evaluates node trust by the transactions between nodes so that the high quality of nodes in the network will be selected to construct a consensus group. To reduce the probability of view change, we propose to replace a single primary node with a primary group. By group signature and mutual supervision, we can enhance the robustness of the primary group further. Finally, we analyze T-PBFT and compare it with the other Byzantine fault tolerant consensus algorithms. Theoretical analysis shows that our T-PBFT can optimize the Byzantine fault-tolerant rate, reduce the probability of view change and communication complexity.

High peak-to-average power ratio (PAPR) is a concern in orthogonal frequency division multiplexing (OFDM) systems. Hadamard based selected mapping (HSLM) which uses Hadamard code as the phase sequence in selected mapping (SLM) is an attractive technique to reduce PAPR. But it requires sending side information (SI) to the receiver for each data block, and this results in a reduction in bandwidth efficiency. In this paper, we proposed a modified PAPR reduction method called semi-Hadamard based selected mapping (semi-HSLM) to decouple the phase information matrix into a phase rotation matrix for PAPR reduction and a SI matrix for side information hiding. We proposed a semi-hadamard matrix generation method to generate the phase rotation matrix, and designed a cyclic shift matrix as the SI matrix. Compared with the traditional HSLM, the semi-HSLM saves half of the phase storage and achieves good PAPR reduction performance.

In this paper, the statistical properties of parameters of each path in wireless channel models are analyzed to prove that there is the static part in channel state information (CSI) which can be extracted from huge amounts of CSI data. Based on the analysis, the concept of the Tomographic Channel Model (TCM) is presented. With cluster algorithms, the static CSI database can be built in an off-line manner. The static CSI database can provide prior information to help pilot design to reduce overhead and improve accuracy in channel estimation. A new CSI prediction method and a new channel estimation method between different frequency bands are introduced based on the static CSI database. Using measurement data, the performance of the new channel prediction method is compared with that of the Auto Regression (AR) predictor. The results indicate that the prediction range of the new method is better than that of the AR method and the new method can predict with fewer pilot symbols. Using measurement data, the new channel estimation method between different frequency bands can estimate the CSI of one frequency band based on known CSI of another frequency band without any feedback.

Sentiment Analysis, an un-abating research area in text mining, requires a computational method for extracting useful information from text. In recent days, social media has become a really rich source to get information about the behavioral state of people (opinion) through reviews and comments. Numerous techniques have been aimed to analyze the sentiment of the text, however, they were unable to come up to the complexity of the sentiments. The complexity requires novel approach for deep analysis of sentiments for more accurate prediction. This research presents a three-step Sentiment Analysis and Prediction (SAP) solution of Text Trend through K-Nearest Neighbor (KNN). At first, sentences are transformed into tokens and stop words are removed. Secondly, polarity of the sentence, paragraph and text is calculated through contributing weighted words, intensity clauses and sentiment shifters. The resulting features extracted in this step played significant role to improve the results. Finally, the trend of the input text has been predicted using KNN classifier based on extracted features. The training and testing of the model has been performed on publically available datasets of twitter and movie reviews. Experiments results illustrated the satisfactory improvement as compared to existing solutions. In addition, GUI (Hello World) based text analysis framework has been designed to perform the text analytics.

To integrate the satellite communications with the LTE/5G services, the concept of Hybrid Satellite Terrestrial Relay Networks (HSTRNs) has been proposed. In this paper, we investigate the secure transmission in a HSTRN where the eavesdropper can wiretap the transmitted messages from both the satellite and the intermediate relays. To effectively protect the message from wiretapping in these two phases, we consider cooperative jamming by the relays, where the jamming signals are optimized to maximize the secrecy rate under the total power constraint of relays. In the first phase, the Maximal Ratio Transmission (MRT) scheme is used to maximize the secrecy rate, while in the second phase, by interpolating between the sub-optimal MRT scheme and the null-space projection scheme, the optimal scheme can be obtained via an efficient one-dimensional searching method. Simulation results show that when the number of cooperative relays is small, the performance of the optimal scheme significantly outperforms that of MRT and null-space projection scheme. When the number of relays increases, the performance of the null-space projection approaches that of the optimal one.

Recently, integrated Satellite-Terrestrial (S-T) communication system, especially the integration of satellite communication with 5G/6G, is regarded as a research hotpot. Future integrated S-T communication systems are demanding a more compatible and robust physical layer waveform. Considering physical layer access waveform design, this paper proposed a novel Spread Spectrum Generalized Frequency Division Multiplexing (SS-GFDM) scheme for integrated S-T communication system. Traditional GFDM has many advantages such as excellent adaptability and low out-of-band (OOB) radiation. However, because of intrinsic inter carrier interference (ICI) and low signal-to-noise ratio (SNR), the multiple access performance is degraded. In this paper, we introduced CDMA technology into GFDM. Two different spread spectrum modes, Cyclic Code Shift Keying (CCSK) soft spread spectrum and Direct Sequence Spread Spectrum (DSSS), are considered and compared in this paper to illustrate the benefits of GFDM-CDMA in low SNR scenario. Moreover, this scheme integrates the slot-ALOHA protocol with GFDM-CDMA, which extends access freedom in frequency, time and code domain. The simulation and analysis results show that the proposed GFDM-CDMA scheme reduces the performance degradation caused by interference. It is effective in typical satellite channel with low complexity. Meanwhile, the peak-average-power-ratio (PAPR) and access performance has been enhanced significantly.

Providing end-to-end delay guarantees in traditional Internet is a complex task due to the distributed nature of TCP/IP protocols. Software Defined Networking (SDN) gives a new dimension to improve QoS(Quality of Service) as it can benefit from its flexibility, programmability and centralized view. In this paper, we provide delay-guaranteed data transmission service instead of “best efforts” service for a topic-based publish/subscribe system by means of exploring these specific features of SDN. We attribute this routing problem in such conditions to Delay-Constraint Lowest Cost Steiner Tree (DCLCST) problem. To solve it, we compute the shortest delay paths from source node to every subscribe node and the shortest cost paths from every subscribe node to any other node using dijkstra algorithm. Then we construct a delay-constraint least cost steiner tree for per-topic based on these paths as multicast tree. We also present experimental results to demonstrate the effectiveness of the algorithms and methods we proposed.