Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-06-06 Cooperative journals: 《计算机应用研究》
Abstract： In Attribute-Based Access Control (ABAC) , how to respond quickly to the retrieved access control request is very important, and it is undoubtedly time-consuming to traverse all attribute values in each rule of the policy set until finding the appropriate rule. Therefore, the paper proposes an ABAC retrieval method based on binary sequence, and uses binary identification and binary coding to represent attribute based access control policies and access control requests. Through the logical operation of binary identification, select the appropriate group. In the group, find the appropriate rules by matching the binary code of access control request with the binary code of all rules, reduce the process of matching the attributes of rules in the policy set with the attributes of access control request, and improve the efficiency of policy retrieval. In the experiment, this paper compares the efficiency of similar retrieval methods from three aspects: strategy preprocessing, strategy evaluation time and total strategy retrieval time. The results show that the strategy retrieval method proposed in this paper has higher retrieval efficiency.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem of long time-consuming and high equipment energy consumption for task scheduling in mobile cloud computing environment, a task scheduling strategy based on improved bird group algorithm is proposed, a task scheduling strategy based on Improved Bird Swarm Algorithm (IBSA) is proposed. Firstly, a mobile cloud task scheduling model based on energy consumption and time is constructed. Secondly, adaptive sensing coefficients and social coefficients are proposed to prevent the algorithm from falling into a local optimum. Learning factors are optimized to optimize flight behavior and ensure that Superior ability. Finally, . the task scheduling objective function is used as the fitness function of the bird group to participate in the iterative updating of the algorithm. The simulation results show that the algorithm has good effects in mobile cloud computing task scheduling compared with ant colony algorithm, particle swarm algorithm, whale algorithm and bird swarm algorithm, which can effectively save time and reduce energy consumption.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： In order to address the current time-consuming process of cloud computing data center resource scheduling, high energy consumption, and low data transmission accuracy, we proposed a VR immersive virtual cloud computing data center resource energy-saving scheduling algorithm. Construction of cloud computing data centers resource sampling model, combined with VR (Virtual Reality) interactive device outputs, transformed, and dispatched central resources, extracted the characteristic quantities of the association rules of the central resources, and used embedded fuzzy clustering fusion analysis methods to reconstruct the central resources three-dimensionally to establish virtual cloud computing data center resources. The information fusion centers to adopt a decision correlation analysis method and combines differentiated fusion feature quantities to realize data center resource scheduling, and realizes real-time energy-saving scheduling for virtualized cloud computing data center resources. The experimental results show that the data transmission accuracy of the proposed algorithm is high, the time cost is short and the energy consumption is low, so it has a good application value in the resource scheduling of virtual cloud computing data center.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Mobile cloud computing can use the computation offloading to improve the energy efficiency of mobile devices and the execution delay of applications. However, in the face of the multiple service selection from cloud, the computation offloading decision is a NP problem. In order to address this problem, a genetic algorithm is designed to find the best application partitioning decision solution for computation offloading. In genetic population initialization, our algorithm combines of predefined and random chromosomes to intialize the population, which can reduce the generation of the inefficient chromosomes. At the same time, the algorithm designs a specific fitness function based on Hamming distance function for the predefined reserved populution, which can better measure the difference between chromosomes. The population crossover uses respectively the inbreeding and crossbreeding to enrich individual species. Our algorithm uses the modified genetic operations to reduce the ineffective solutions and obtain the best feasible solution in a reasonable time. We evaluated the efficiency of the proposed algorithm using graphs of real mobile applications in simulation experiments. The evaluated conclusions denote that our designed algorithm has a better performance than the comparision algorithms on the application execution energy, the execution time and the overall weight cost.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problems of low computational efficiency and low clustering performance of clustering algorithms for big data, a clustering algorithm of big data based on the improved artificial bee colony algorithm and MapReduce is presented. The grey wolf optimizer algorithm and artificial bee colony algorithm are combined, in order to improve the exploration and exploitation of the artificial bee colony algorithm simultaneously, this strategy helps to improve the clustering performance effectively. The chaotic map and backward learning are utilized as the initial strategy of ABC colony to improve the solution quality of search procedure. The clustering algorithm is realized based on MapReduce programming model, and the clustering process for big data is realized by minimizing the quadratic sum of inner class distances. Experimental results demonstrated that the proposed algorithm improves the clustering quality of big data, and it speedups the clustering procedure.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Mobile edge computing technology combines IT service environments and cloud computing technologies at the edge of the network to improve the computing and storage capabilities of edge networks while reducing network operations and service delivery delays. Vehicular networks integrating MEC, could meet the strict requirements of vehicle service delay and communication reliability, as well as improve the quality of service for vehicle users. This paper studied and analyzed MEC applications in vehicular networks. Firstly, it provided a brief on the basic concept and architecture of MEC, and its typical application scenarios. Thereafter, it described a comprehensive survey of relevant research in the area of MEC-based vehicular networks along with a focus on the current SDN-related works on MEC-based vehicular networks, as well as several use cases. Finally, this paper discussed the main problems and challenges to deploy MEC in vehicular networks; and analyzed the future research directions on these areas.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： In order to improve the efficiency of data scheduling and replica access in cloud computing, the paper studied the replica placement problem in replica strategy and proposed a replica placement strategy based on ant colony algorithm. According to the principle of ant colony foraging in nature, ant colony algorithm applies to the entire process of replica placement. The pheromone dynamic updating and Laplace probability distribution improves the ant colony algorithm, a set of optimal solutions is obtained for replica placement. Simulation is on the CloudSim platform. The experimental results show that the proposed scheme is superior to the original ant colony algorithm in average job completion time, network utilization and load balance, and reduces the copy placement time consumption and network load to a certain extent.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-12-13 Cooperative journals: 《计算机应用研究》
Abstract： When the user stores the data on an dishonest server, the integrity of the data needs to be verified, so the proof-of-retrievability (POR) system is proposed. Aiming at the problem of identity-based cryptosystem used in most of the existing solutions, a more intuitive and flexible attribute-based cryptosystem is adopted to design an attribute-based data recoverability proof scheme. This paper firstly proposed definition and model of an attribute-based proof of retrievability with public verifiability, then, constructed an attribute-based proof of retrievability with public verifiability, finally, proved its correctness and security.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-10-11 Cooperative journals: 《计算机应用研究》
Abstract： Workflow scheduling is a kind of economical and effective method in engineering management area. For optimizing the economical cost and scheduling efficiency of cloud workflow scheduling, a workflow scheduling algorithm based on Directed Acyclic Graph DAG partition PBWS is proposed. With the goal of optimizing synchronously the workflow scheduling efficiency and cost, our algorithm divides the scheduling solution into three stages: DAG partition of the workflow structure, partition structure adjustment and resource allocation. DAG partition of the workflow structure is to get the initial tasks partition graph when guarantees the execution order-dependency between tasks, the partition structure adjustemnt is to re-allocate tasks in different partitions with a goal of reducing execution makespan and the resource allocaiton is to determine the most cost-efficient mateches between tasks and resources ensuring the minization of the total idel time of resource. We construct some simulation experiments for algorithms by the five types of scientific workflow DAG model. The experimental results show PBWS can greatly reduce the execution cost of wrokflow in terms of cost by a large margin with litter overhead on execution makespan and realize the synchronous optimization of the scheuduling efficiency and the scheduling cost, whose overall performance performs better than the same type of algorithms.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the low efficiency and low utilization rate of traditional cloud computing task scheduling algorithms, this paper proposed an improved algorithm using the improved fruit fly optimization algorithm (IFOA) and genetic algorithm (GA) for task scheduling. Firstly, the task scheduling is converted into a DAG (Directed Acyclic Graph) , and the task scheduling sequence is simplified through the kruskal algorithm. Secondly, the population of Drosophila algorithm is initialized using orthogonal arrays and quantization techniques. The boundaries of the Drosophila algorithm algorithm are processed, the exploration step size is dynamically adjusted, and the individual selection is processed using the GA algorithm. Finally, the fusion algorithm IFOA-GA is used in cloud computing task scheduling in the simulation platform. Compared with IGA, IFOA and IPSO algorithm, it has certain advantages in the comparison of four indexes of QoS, which shows that the IFOA-GA algorithm can be effective in mproving cloud computing scheduling efficiency
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-07-23 Cooperative journals: 《计算机应用研究》
Abstract： Wearable medical devices with sensor continuously generate enormous data, due to the complexity of the data, it is difficult to process and analyze the big data for finding valuable information that can be useful in decision-making. In order to overcome this issue, this paper proposed a new architecture for the implementation of IoT to store and process scalable sensor data (big data) for health care applications. The proposed architecture consisted of two main sub architectures, namely, Meta Fog-Redirection (MF-R) and AWS key management mechanism. MF-R architecture used big data technologies such as Apache Pig and Apache HBase for collection and storage of the sensor data generated from different sensor devices and it also used kalman filter for removal of noise. AWS key management mechanism used a key management scheme to protect data in the cloud and prevent unauthorized access. When data was stored in the cloud, the proposed system could use stochastic gradient descent algorithms and logistic regression to develop a predictive model of heart disease. Simulation experiments show that compared with other algorithms, the proposed algorithm has smaller error and it has certain advantages in terms of throughput and accuracy.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： With the popularity of cloud computing, mobile devices can store and retrieve personal data anytime and anywhere. Attribute based encryption can be used to solve the problem of mobile cloud data security. At present, the research on attribute based encryption adapting to mobile cloud is mainly focused on single authority, which does not satisfy the real property authorization situation. This paper proposed a new multi-authority attribute based encryption scheme with no central authority, each authority in the scheme could not affect each other and attributes could be added independently. In addition, the scheme uses precomputation and outsourcing decryption to reduce the computation cost of the user side. Besides, the scheme was static secure under the random oracle model. Experimental results show that the scheme can reduce the computation cost of the user side by 20%, and it is more consistent with the data sharing application scenario in the mobile cloud environment.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： Due to the low efficiency of cloud computing resource task scheduling and uneven resource allocation, this paper combined the improved fireworks algorithm and artificial bee colony algorithm into IFWA-ABC. Firstly, this paper described the cloud computing resource task scheduling. Secondly, it used the chaotic reverse learning and Cauchy distribution to optimize the FWA initialization. The radii of the core fireworks and the non-core fireworks are optimized respectively. The optimal individuals in the FWA are obtained by improving the ABC algorithm. Finally, the IFWA-ABC algorithm is used for cloud computing task scheduling. In the simulation experiment, IFWA-ABC has obvious advantages compared with FWA and ABC in terms of virtual machine, execution time, consumption cost and Energy consumption index, which can effectively improve cloud computing resource allocation efficiency.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-24 Cooperative journals: 《计算机应用研究》
Abstract： How to schedule data-intensive workflow efficiently and reasonable has become one of the key issue in cloud computing. To address this issue, first, we build a directed hypergraph model for data-intensive workflow. And proposing a concept data supportive ability to help the presentation of data-intensive workflow application and provide the merge operation details considering the data supportive ability. By optimizing the hypergraph multi-level partitioning algorithm, proposing a data reduced scheduling policy HEFT-P for data-intensive workflow. Through simulation, the classical HEFT, CPOP and MCP scheduling policies was compared with HEFT-P. The results indicate that HEFT-P could obtain reduced data scheduling and reduce the makespan of executing data-intensive workflows.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： For implementing the synchronization optimization of tasks execution efficiency and execution cost, a multi-objective scheduling optimization algorithm of DAG tasks in cloud environment is presented. Our algorithm defines the multi-objective optimization problem as the trade-off optimal solutions set satisfying Pareto optimal and solves this model by the heuristic method. At the same time, for evaluating the quality of multi-objective trade-off solutions, a evaluation mechanism based on hypervolume method is designed, which can obtain the trade-off scheduling solutions with conflict objectives. Through setting cloud environment and three kinds of synthetic workflow and two kinds of real-world scientific workflow, we construct some simulation experiments. The results show that, compared with the same type of single objective algorithm and multi-objective heuristic algorithm, our algorithm not only has higher solving quality, but has better trade-off degree of solutions, which can conform to the mode of resource utility and workflow scheduling in real-world cloud.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the intrusion of untrusted users in remote sensing cloud platform, this paper designed a user behavior authentication scheme based on the characteristics of remote sensing cloud user behavior and Bayesian network algorithm. The scheme discussed the users' behavior authentication mechanism of remote sensing cloud platform, and according to the users' behavior characteristics, the scheme established an authentication set on users’ behavior. Combining with the predictive characteristics of bayesian network algorithm and user behavior properties to set up a Bayesian network model for authentication grade prediction. The weight information of user behavior attributes analyzed in this model is applied to the user grade prediction algorithm, which made the algorithm more secure and accurate for remote sensing cloud user authentication safer accurately, so as to realize the prediction of user behavior authentication level. Simulation examples show that the model is effective to identify untrusted users accurately, and can ensure the security of remote sensing cloud platform.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-18 Cooperative journals: 《计算机应用研究》
Abstract： Cloud storage system often adopts replica technique to guarantee availability and reliability, and replica placement is a key issue. In order to solve the problem of high access overhead to replicas, this paper proposed a replica placement algorithm based on discrete glowworm swarm optimization. Through mathematical mode establishment for user access overhead, this algorithm computed the fitness function of glowworm position, updated individual position and then obtained appropriate nodes for replica placement. It conducted several simulations and compared with the replica placement strategy based on ant algorithm. The results show that the proposed algorithm can select appropriate nodes for replica placement, have a better convergence and reduce the replica access overhead.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-24 Cooperative journals: 《计算机应用研究》
Abstract： By utilizing the characteristics of resource sharing in cloud computing, attackers can launch DoS attack by constantly consuming bandwidth resources so that other users on the same physical host can not receive normal services. This attack mode is different from the DoS attack in traditional network system, so it is difficult to apply traditional defense method to solve it. To solve this problem, this paper proposes a DoS attack defense method based on virtual machine migration. By selecting the migration target, designing the triggering mechanism and selecting the migration destination, a virtual machine migration strategy is proposed to mitigate the impact of DoS attacks. The experimental results demonstrate that this method can effectively defend DoS attack and ensure the normal operation of cloud service whatever different attack methods that attackers may use. Compared with other methods, the proposed strategy leads a litter more migration cost, however, it’s better in defense effect and feasibility.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-24 Cooperative journals: 《计算机应用研究》
Abstract： Mobile cloud computing can significantly enhance computation capability of mobile devices by offloading computation from the mobile devices onto the cloud. How to achieve energy-efficient computation offloading remains a challenge issue. For solving this problem, with reducing energy consumption and shorting application completion time as an objective, this algorithm was proposed. The algorithm will formulate computation offloading problem into the energy-eficiency cost minimization problem while satisfying the task-dependency requirements and the completion deadline constraint. And, a dynamic and energy-aware computation offloading algorithm is presented. The algorithm consists of three sub-algorithm of computation offloading selection, clock frequency control and transimission power allocation. Experimental results show that the algorithm can effective reduce the energy-eficiency cost by optimally adjusting the CPU clock frequency of mobile devices in local computing, and adapting the transmission power in cloud computing while ensures to satisfy the constraints and enhance the scheduling efficiency.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： There are lots of drawbacks in existing attribute-based encryption with keyword search scheme, such as privacy disclosure issues and when the authorized user is offline how effectively delegate decrypt and search right to other people. In order to solve these problems, this paper proposed an attribute-based ciphertext search scheme with hidden access structures, which support proxy re-encryption function by combing attribute-based encryption with hidden access structures and proxy re-encryption technology. This scheme not only effectively solves the problems mentioned above, but also supports the update of keywords. Finally, under the random oracle model, the researchers proved the security of the scheme based on DL (D-linear) and q-BDHE (decisional q-parallel bilinear Diffie-Hellman exponent) hypothesis.
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