Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content.In light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of location.If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of resources.Hence,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate prediction.The findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 s.Within a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G networks.These improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving congestion.By improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

Hybrid Optimization Algorithm for Resource Allocation in LTE-Based D2D Communication

In a cellular network,direct Device-to-Device(D2D)communication enhances Quality of Service(QoS)in terms of coverage,throughput and amount of power consumed.Since theD2D pairs involve cellular resources for communication,the chances of interference are high.D2D communications demand minimum interference along with maximum throughput and sum rate which can be achieved by employing optimal resources and efficient power allocation procedures.In this research,a hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization(GA-ABO)algorithm is proposed for efficient resource allocation in a cellular network with D2D communication.Simulation analysis demonstrates that the proposed model involves reduced interference with maximum sum rate and throughput.The performance of the proposed model is compared with the existing Ant Colony Optimization-based resource exchange and GAME(ACO-GAME)theory models,Trader-assistedResource EXchange mechanism-RadioAccess Network(TREX-RAN)and De-centralized Radio Access Network(TREXDRAN),and greedy CYcle-Complete preferences(CYC)models.The proposed model offers a maximum sum rate of 83 kB/s,which is much better than the existing techniques.

Simulated annealing algorithm for the optimal translation sequence of the jth agent in rough communication

In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.

Coded Multicasting for Content Delivery over Predictable Time-Varying Satellite Communication Networks

With the development of astronautic technology, communication satellites now have a tremendous gain in both quantity and quality, and have already shown their capability on multi-functional converged communication other than telecommunication. Under this circumstance, increasing the transmission efficiency of satellite communication network becomes a top priority. In this paper, we focus on content delivery service on satellite networks, where each ground station may have prefetched some file fragments. We cast this problem into a coded caching framework so as to exploit the coded multicast gain for minimizing the satellite communication load. We first propose an optimization-based coded multicast scheme by considering the special property that the satellite network topology is predictable and timevariant. Then, a greedy based fast algorithm is proposed, which can tremendously reduce the computation complexity with a small loss in optimality. Simulation experiments conducted on two Walker constellation satellite networks show that our proposed coded multicast method can efficiently reduce the communication load of satellite networks.

PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks

In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability.

Algorithmof communication network reliability combining links,nodes and capacity

The conception of the normalized reliability index weighted by capacity is introduced, which combing the communication capacity, the reliability probability of exchange nodes and the reliability probability of the transmission links, in order to estimate the reliability performance of communication network comprehensively and objectively. To realize the full algebraic calculation, the key problem should be resolved, which is to find an algorithm to calculate all the routes between nodes of a network. A kind of logic algebraic algorithm of network routes is studied and based on this algorithm, the full algebraic algorithm of normalized reliability index weighted by capacity is studied. For this algorithm, it is easy to design program and the calculation of reliability index is finished, which is the foundation of the comprehensive and objective estimation of communication networks. The calculation procedure of the algorithm is introduced through typical examples and the results verify the algorithm.

A Recovery Algorithm for Self-Stabilizing Communication Protocols

This paper presents a recovery algorithm for self-stabilizing communication protocols. It first describes some concepts and a formal description method for the algorithm. Then it proposes the algorithm procedures, proves its correctness and analyses its complexity. Finally, it also verifies the availability and efficiency of the algorithm by illustrating an example protocol with multi-processes.

Communication Mechanism and Algorithm of Composite Location Analysis of Emergency Communication based on Rail

The emergency communication system based on rail is an unconventional emergency communication mode,it is a complement equipment for that conventional communication system can’t work while tunnel mine accident occurs.Medium of transmission channel is the widely existing rail in the tunnel.In this paper we analyzed the characteristics of the rail transmission channel,verified the feasibility that information is transmitted by vibration signal in rail,we proposed the realization plan of the system.Communication protocol and processing mechanism suitable for rail transmission are designed according to the characteristics of channel bandwidth and low data transmission.Information communication with low bit rate and low bit error is realized in the communication simulation model.In the simplified model,we realized to transmit recognition speech information,and the error rate of the key text information is low to accept.The most concerned problem of personnel location in the mine disaster rescue is proposed,the composite algorithm is based on the model of signal amplitude attenuation,key node information and data frame transmission delay.Location information of hitting point can be achieved within the simplified model of the experiment.Furthermore,we discuss the characteristics of vibration signals passing through different channels.

Enhanced Energy Efficient Multipath Routing Protocol for Wireless Sensor Communication Networks Using Cuckoo Search Algorithm

Energy efficient routing is one of the major thrust areas in Wireless Sensor Communication Networks (WSCNs) and it attracts most of the researchers by its valuable applications and various challenges. Wireless sensor networks contain several nodes in its terrain region. Reducing the energy consumption over the WSCN has its significance since the nodes are battery powered. Various research methodologies were proposed by researchers in this area. One of the bio-inspired computing paradigms named Cuckoo search algorithm is used in this research work for finding the energy efficient path and routing is performed. Several performance metrics are taken into account for determining the performance of the proposed routing protocol such as throughput, packet delivery ratio, energy consumption and delay. Simulation is performed using NS2 and the results shows that the proposed routing protocol is better in terms of average throughput, and average energy consumption.

Research on a Secure Communication Protocol Based on National Secret SM2 Algorithm

Most of the public key algorithms used in the exchange of information for power data transmission protocols are RSA. The core of the key part of this kind of algorithm system has not been announced. For the domestic sensitive information data field, there are threats such as preset backdoors and security vulnerabilities. In response to the above problems, the article introduces a secure communication protocol based on the optimized Secret SM2 algorithm, which uses socket programming to achieve two-way encrypted communication between clients and services, and is able to complete the security protection of data encryption transmission, authentication, data tampering, etc., and proves through experiments that the security protocol is more secure than traditional methods, can effectively identify each other, carry out stable and controllable data encryption transmission, and has good applicability.

Novel joint encoding/decoding algorithms of fountain codes for underwater acoustic communication

Fountain codes are considered to be a promising coding technique in underwater acoustic communication（UAC） which is challenged with the unique propagation features of the underwater acoustic channel and the harsh marine environment. And Luby transform（LT） codes are the first codes fully realizing the digital fountain concept. However, in conventional LT encoding/decoding algorithms, due to the imperfect coverage（IC） of input symbols and short cycles in the generator matrix, stopping sets would occur and terminate the decoding. Thus, the recovery probability is reduced,high coding overhead is required and decoding delay is increased.These issues would be disadvantages while applying LT codes in underwater acoustic communication. Aimed at solving those issues, novel encoding/decoding algorithms are proposed. First,a doping and non-uniform selecting（DNS） encoding algorithm is proposed to solve the IC and the generation of short cycles problems. And this can reduce the probability of stopping sets occur during decoding. Second, a hybrid on the fly Gaussian elimination and belief propagation（OFG-BP） decoding algorithm is designed to reduce the decoding delay and efficiently utilize the information of stopping sets. Comparisons via Monte Carlo simulation confirm that the proposed schemes could achieve better overall decoding performances in comparison with conventional schemes.

Algebraic algorithm for reliability index weighted capacity of communication network

Communication network has communication capacity and connection reliability of the links. They canbe independently defined and can be used separately, and when the reliability of a communication network isanalyzed from a macroscopical angle of view, it is more objective to express the performance index of a commu-nication network as a whole. The reliability index weighted capacity is just obtained by integrating these two pa-rameters. It is necessary to further study the algorithm to calculate the reliability index of the communicationnetwork with a complicated topologic structure and a whole algebraic algorithm is therefore proposed for calcula-tion of the reliability index weighted capacity of a communication network with a topologic structure. The wholecomputational procedure of the algorithm is illustrated with a typical example.

Multi-Objective Bacterial Foraging Optimization Algorithm Based on Effective Area in Cognitive Emergency Communication Networks

Cognitive emergency communication net-works can meet the requirements of large capac-ity,high density and low delay in emergency com-munications.This paper analyzes the properties of emergency users in cognitive emergency communi-cation networks,designs a multi-objective optimiza-tion and proposes a novel multi-objective bacterial foraging optimization algorithm based on effective area(MOBFO-EA)to maximize the transmission rate while maximizing the lifecycle of the network.In the algorithm,the effective area is proposed to prevent the algorithm from falling into a local optimum,and the diversity and uniformity of the Pareto-optimal solu-tions distributed in the effective area are used to eval-uate the optimization algorithm.Then,the dynamic preservation is used to enhance the competitiveness of excellent individuals and the uniformity and diversity of the Pareto-optimal solutions in the effective area.Finally,the adaptive step size,adaptive moving direc-tion and inertial weight are used to shorten the search time of bacteria and accelerate the optimization con-vergence.The simulation results show that the pro-posed MOBFO-EA algorithm improves the efficiency of the Pareto-optimal solutions by approximately 55%compared with the MOPSO algorithm and by approx-imately 60%compared with the MOBFO algorithm and has the fastest and smoothest convergence.

Parallel Expectation-Maximization Algorithm for Large Databases

A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in generic statistical problems, the EM algorithm has been widely used in many domains. But it often requires significant computational resources. So it is needed to develop more elaborate methods to adapt the databases to a large number of records or large dimensionality. The parallel EM algorithm is based on partial Esteps which has the standard convergence guarantee of EM. The algorithm utilizes fully the advantage of parallel computation. It was confirmed that the algorithm obtains about 2.6 speedups in contrast with the standard EM algorithm through its application to large databases. The running time will decrease near linearly when the number of processors increasing.

Scheduling Algorithm Based on Storage Capacity of Communication in Hardware/Software Integrated System

In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution process, the maximum storage requirements for communication are minimized. Experimental results with various directed acyclic graph models showed that compared with the earliest-task-first algorithm, the storage requirements for communication were reduced by 22.46%, on average, while the average of makespan only increased by 0.82%,.

Genetic algorithm for λ-optimal translation sequence of rough communication

In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a less or rougher concept. With different translation sequences the amount of the missed knowledge is varied. The λ-optimal translation sequence of rough communication, which concerns both every agent and the last agent taking part in rough communication to get information as much as he （or she） can, is given. In order to get the λ-optimal translation sequence, a genetic algorithm is used. Analysis and simulation of the algorithm demonstrate the effectiveness of the approach.

The Algorithms for Achieving Global States and Self-Stabilization for Communication Protocols

This paper discusses the algorithms for achieving global states and self-stabilizationfor communication protocols. It first describes a primary algorithm including its suitability forachieving global states and limitation of self-stabilization for communication protocols, and thenpresents an improved algorithm that can be suitable to achieve global states and can be also usedto self-stabilizing communication protocols. Filially, it gives the proof of correctness and analysis ofcomplexity of the improved algorithm, and verifies its availability and efficiency by illustrating anexample protocol.

Switched-Beam Optimization for an Indoor Visible Light Communication Using Genetic Algorithm

Nowadays, Visible Light Communication (VLC) is an attractivealternative technology for wireless communication because it can use somesimple Light Emitting Diodes (LEDs) instead of antennas. Typically, indoorVLC is designed to transmit only one dataset through multiple LED beams at atime. As a result, the number of users per unit of time (throughput) is relativelylow. Therefore, this paper proposes the design of an indoor VLC system usingswitched-beam technique through computer simulation. The LED lamps aredesigned to be arranged in a circular array and the signal can be transmittedthrough the beam of each LED lamp with the method of separating the datasetto increase the number of simultaneous users for enhancing the indoor VLC.The coverage area is determined from the area where the communication canbe performed at a location on the receiving plane with a Bit Error Rate lessthan or equal to the specified value based on coverage illuminance accordingto International Commission on Illumination (CIE) standards. In this paper,Genetic Algorithm is used to find the suitable solution for designing parameters to achieve maximum coverage area. The results show that a GeneticAlgorithm can be used to find a suitable solution and reduce the computationaltime approximately 382 min in proposed scenarios.

THE NOVEL COMMUNICATION ALGORITHM AND THE THROUGHPUT ANALYSIS FOR WIRELESS SENSOR NETWORKS

Aiming at the significance of the energy controls of wireless sensor networks, an economical energy consumption algorithm for wireless communicating in Wireless Sensor Networks (WSN) is presented. Based on the algorithm, the maximal system throughput of WSN is analyzed, and the upper bound of throughput of WSN is proposed and proved. Some numerical simulations are conducted and analyzed. The conclusions include that the transmitting radius of sensor node and the parameters of the energy cost function have significant influence upon the throughput, but the monitoring region radius has little influence. For the same transmitting distance, the more the hopping of information trans- mitting, the better the throughput of WSN. On the other hand, for the energy optimization of the whole WSN, the trade-off problem between the throughput capacity and the relay nodes is proposed, and the specific expression of relay hops that minimized the energy consumptions and the maximal throughput of WSN under the specific situation is derived.