Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive systems.Secured group communication p...Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive systems.Secured group communication plays a vital role in case of providing the integrity,authenticity,confidentiality,and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the group.In secure group communications,the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service,particularly in the large groups with highly active membership.Hence,the paper is aimed to achieve better cost and time efficiency through an improved DC multicast routing protocol which is used to expose the path between the nodes participating in the group communication.During this process,each node constructs an adaptive Ptolemy decision tree for the purpose of generating the contributory key.Each of the node is comprised of three keys which will be exchanged between the nodes for considering the group key for the purpose of secure and cost-efficient group communication.The rekeying process is performed when a member leaves or adds into the group.The performance metrics of novel approach is measured depending on the important factors such as computational and communicational cost,rekeying process and formation of the group.It is concluded from the study that the technique has reduced the computational and communicational cost of the secure group communication when compared to the other existing methods.展开更多
Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every s...Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.展开更多
Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Anta...Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Antarctica region, and sequenced the whole genome through the next generation sequencing platform. The assembly yielded three contigs representing two chromosomes and one plasmid with the sizes of 3.2 Mb, 636 kb and 1.8 kb, respectively. The G＋C contents of genome were 40.83% and included 3 589 ORFs. Functional annotation indicated some potential roles in enzymatic activity and environmental adaptability. This study may help for understanding the population diverse, evolutionary ecology and the microbial interaction.展开更多
In this paper,an immersed boundary algorithm is developed by combining the ghost cell method with adaptive tree Cartesian grid method.Furthermore,the proposed method is successfully used to evaluate various inviscid c...In this paper,an immersed boundary algorithm is developed by combining the ghost cell method with adaptive tree Cartesian grid method.Furthermore,the proposed method is successfully used to evaluate various inviscid compressible flow with immersed boundary.The extension to three dimensional cases is also achieved.Numerical examples demonstrate the proposed method is effective.展开更多
A 4×4 64-QAM multiple-input multiple-output （MIMO） detector is presented for the application of an IEEE 802.1 In wireless local area network. The detector is the implementation of a novel adaptive tree search ...A 4×4 64-QAM multiple-input multiple-output （MIMO） detector is presented for the application of an IEEE 802.1 In wireless local area network. The detector is the implementation of a novel adaptive tree search （ATS） algorithm, and multiple ATS cores need to be instantiated to achieve the wideband requirement in the 802.11 n standard. Both the ATS algorithm and the architectural considerations are explained. The latency of the detector is 0.75 μs, and the detector has a gate count of 848 k with a total of 19 parallel ATS cores. Each ATS core runs at 67 MHz. Measurement results show that compared with the floating-point ATS algorithm, the fixed-point imple- mentation achieves a loss of 0.9 dB at a BER of 10^-3.展开更多
Adaptive Radix Tree(ART)is an efficient data structure for key-based lookup and insertion operations.It finds extensive applications in various domains,including database management systems,network routing,operating s...Adaptive Radix Tree(ART)is an efficient data structure for key-based lookup and insertion operations.It finds extensive applications in various domains,including database management systems,network routing,operating systems,and storage systems.Compared to traditional prefix trees,its aim is to provide enhanced space and time efficiency.By utilizing appropriate node types and efficient search strategies,it optimizes the time and space complexities of search and insertion operations.During the construction of ART,frequent memory allocations and deallocations result in suboptimal performance,introducing additional memory overhead.Traditional methods struggle to address these drawbacks.To mitigate this issue,we draw inspiration from Deep Reinforcement Learning(DRL)and develop aDRLbased model to determine howto select node types for creating new nodes,rather than relying on currently employed manual heuristics.Importantly,the ART constructed using DRL-based methods doesn’t necessitate replacing the existing index and query processing algorithms deployed in the current database infrastructure.Experimental results on both real and synthetic datasets containing 200 million objects clearly indicate the superiority of our DRL-based index construction approach over conventional methods for building ART in terms of performance.展开更多
The attack of false data injection can con-taminate the measurements acquired from the supervi-sory control and data acquisition(SCADA)system,which can seriously endanger the safety and stability of power system opera...The attack of false data injection can con-taminate the measurements acquired from the supervi-sory control and data acquisition(SCADA)system,which can seriously endanger the safety and stability of power system operations.The conventional machine learning attack detection methods use a single strong classifier and are difficult to solve the problem of overfitting,making them lack of generalization ability.On the other hand,most existing dimension reduction approaches based on feature extraction can change the original physical meanings of measurements.Here,a novel method is proposed based on feature selection and ensemble learn-ing to solve the above problems.Squirrel search algo-rithm combines Latin hypercube sampling and opposi-tion-based learning to form an improved algorithm with strong global search ability for feature selection.This avoids the problem of feature extraction changing the original physical meanings of measurements.Besides,the classifier based on adaptive boosting decision tree en-semble learning algorithm with stronger generalization ability is used to distinguish the false data injection.Sim-ulation results using the IEEE 14-bus and IEEE 57-bus test systems verify the proposed method with higher per-formance of detection compared with other widely adopted methods.展开更多
Massive data is written to blockchain systems for the destination of keeping safe. However, existing blockchain protocols still demand that each full node has to contain the entire chain. Most nodes quit because they ...Massive data is written to blockchain systems for the destination of keeping safe. However, existing blockchain protocols still demand that each full node has to contain the entire chain. Most nodes quit because they are unable to grow their storage space with the size of data. As the number of nodes decreases, the security of blockchains would significantly reduce. We present SE-Chain, a novel scale-out blockchain model that improves storage scalability under the premise of ensuring safety and achieves efficient retrieval. The SE-Chain consists of three parts:the data layer, the processing layer and the storage layer. In the data layer, each transaction is stored in the AB-M tree (Adaptive Balanced Merkle tree), which adaptively combines the advantages of balanced binary tree (quick retrieval) and Merkle tree (quick verification). In the processing layer, the full nodes store the part of the complete chain selected by the duplicate ratio regulation algorithm. Meanwhile, the node reliability verification method is used for increasing the stability of full nodes and reducing the risk of imperfect data recovering caused by the reduction of duplicate number in the storage layer. The experimental results on real datasets show that the query time of SE-Chain based on the AB-M tree is reduced by 17% when 16 nodes exist. Overall, SE-Chain improves the storage scalability extremely and implements efficient querying of transactions.展开更多
The content-based addressing method of Interplanetary File System(IPFS)leads to the lack of the function of retrieving relevant data through key information.To solve this problem,this paper proposes an efficient IPFS ...The content-based addressing method of Interplanetary File System(IPFS)leads to the lack of the function of retrieving relevant data through key information.To solve this problem,this paper proposes an efficient IPFS keyword retrieval model–IPFS-DKRM(IPFS-Distributed keyword retrieval model).This model combines the global index with Adaptive Radix Tree,and optimizes the storage mode of IPFS network and node-local data index:The model adopts the global index method and uses ART to store the key information of global index locally and stores the complete index information in IPFS to reduce the time of data retrieval and update;The nodes of network through the Publish-Subscribe Pattern synchronization index,and the use of Conflict-free Replication Data Type(CRDT)to maintain the final consistency of the global index of each node,to ensure that all nodes in the local to provide efficient retrieval services.In the simulation experiment,the index of open source data set Crosswikis was constructed,and the performance was analyzed based on the results of Siva data.The experimental results showed that compared with the Siva model,the response retrieval time of IPFS-DKRM was reduced by 75%,and the space occupied by node local storage index was reduced by 70%.It proves that the model only needs to occupy a small amount of space to store the global index information in the system to provide efficient retrieval function for IPFS,so that IPFS canmeet more application scenarios in the future.展开更多
文摘Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive systems.Secured group communication plays a vital role in case of providing the integrity,authenticity,confidentiality,and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the group.In secure group communications,the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service,particularly in the large groups with highly active membership.Hence,the paper is aimed to achieve better cost and time efficiency through an improved DC multicast routing protocol which is used to expose the path between the nodes participating in the group communication.During this process,each node constructs an adaptive Ptolemy decision tree for the purpose of generating the contributory key.Each of the node is comprised of three keys which will be exchanged between the nodes for considering the group key for the purpose of secure and cost-efficient group communication.The rekeying process is performed when a member leaves or adds into the group.The performance metrics of novel approach is measured depending on the important factors such as computational and communicational cost,rekeying process and formation of the group.It is concluded from the study that the technique has reduced the computational and communicational cost of the secure group communication when compared to the other existing methods.
文摘Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.
基金The National Natural Science Foundation of China under contract Nos 31200097,41576187,U1406402-5 and31202024the Basic Scientific Fund for National Public Research Institutes of China under contract Nos 2013G33 and 2015G10
文摘Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Antarctica region, and sequenced the whole genome through the next generation sequencing platform. The assembly yielded three contigs representing two chromosomes and one plasmid with the sizes of 3.2 Mb, 636 kb and 1.8 kb, respectively. The G＋C contents of genome were 40.83% and included 3 589 ORFs. Functional annotation indicated some potential roles in enzymatic activity and environmental adaptability. This study may help for understanding the population diverse, evolutionary ecology and the microbial interaction.
基金supported partly by National Science Foundation of China(10728026)National Basic Research Program of China(2007CB714600).
文摘In this paper,an immersed boundary algorithm is developed by combining the ghost cell method with adaptive tree Cartesian grid method.Furthermore,the proposed method is successfully used to evaluate various inviscid compressible flow with immersed boundary.The extension to three dimensional cases is also achieved.Numerical examples demonstrate the proposed method is effective.
文摘A 4×4 64-QAM multiple-input multiple-output （MIMO） detector is presented for the application of an IEEE 802.1 In wireless local area network. The detector is the implementation of a novel adaptive tree search （ATS） algorithm, and multiple ATS cores need to be instantiated to achieve the wideband requirement in the 802.11 n standard. Both the ATS algorithm and the architectural considerations are explained. The latency of the detector is 0.75 μs, and the detector has a gate count of 848 k with a total of 19 parallel ATS cores. Each ATS core runs at 67 MHz. Measurement results show that compared with the floating-point ATS algorithm, the fixed-point imple- mentation achieves a loss of 0.9 dB at a BER of 10^-3.
文摘Adaptive Radix Tree(ART)is an efficient data structure for key-based lookup and insertion operations.It finds extensive applications in various domains,including database management systems,network routing,operating systems,and storage systems.Compared to traditional prefix trees,its aim is to provide enhanced space and time efficiency.By utilizing appropriate node types and efficient search strategies,it optimizes the time and space complexities of search and insertion operations.During the construction of ART,frequent memory allocations and deallocations result in suboptimal performance,introducing additional memory overhead.Traditional methods struggle to address these drawbacks.To mitigate this issue,we draw inspiration from Deep Reinforcement Learning(DRL)and develop aDRLbased model to determine howto select node types for creating new nodes,rather than relying on currently employed manual heuristics.Importantly,the ART constructed using DRL-based methods doesn’t necessitate replacing the existing index and query processing algorithms deployed in the current database infrastructure.Experimental results on both real and synthetic datasets containing 200 million objects clearly indicate the superiority of our DRL-based index construction approach over conventional methods for building ART in terms of performance.
基金supported by the National Natural Sci-ence Foundation of China(No.52477104).
文摘The attack of false data injection can con-taminate the measurements acquired from the supervi-sory control and data acquisition(SCADA)system,which can seriously endanger the safety and stability of power system operations.The conventional machine learning attack detection methods use a single strong classifier and are difficult to solve the problem of overfitting,making them lack of generalization ability.On the other hand,most existing dimension reduction approaches based on feature extraction can change the original physical meanings of measurements.Here,a novel method is proposed based on feature selection and ensemble learn-ing to solve the above problems.Squirrel search algo-rithm combines Latin hypercube sampling and opposi-tion-based learning to form an improved algorithm with strong global search ability for feature selection.This avoids the problem of feature extraction changing the original physical meanings of measurements.Besides,the classifier based on adaptive boosting decision tree en-semble learning algorithm with stronger generalization ability is used to distinguish the false data injection.Sim-ulation results using the IEEE 14-bus and IEEE 57-bus test systems verify the proposed method with higher per-formance of detection compared with other widely adopted methods.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61472069,61402089 and U1401256China Postdoctoral Science Foundation under Grant Nos.2019T120216 and 2018M641705the Fundamental Research Funds for the Central Universities of China under Grant Nos.N2019007,N180408019 and N180101028.
文摘Massive data is written to blockchain systems for the destination of keeping safe. However, existing blockchain protocols still demand that each full node has to contain the entire chain. Most nodes quit because they are unable to grow their storage space with the size of data. As the number of nodes decreases, the security of blockchains would significantly reduce. We present SE-Chain, a novel scale-out blockchain model that improves storage scalability under the premise of ensuring safety and achieves efficient retrieval. The SE-Chain consists of three parts:the data layer, the processing layer and the storage layer. In the data layer, each transaction is stored in the AB-M tree (Adaptive Balanced Merkle tree), which adaptively combines the advantages of balanced binary tree (quick retrieval) and Merkle tree (quick verification). In the processing layer, the full nodes store the part of the complete chain selected by the duplicate ratio regulation algorithm. Meanwhile, the node reliability verification method is used for increasing the stability of full nodes and reducing the risk of imperfect data recovering caused by the reduction of duplicate number in the storage layer. The experimental results on real datasets show that the query time of SE-Chain based on the AB-M tree is reduced by 17% when 16 nodes exist. Overall, SE-Chain improves the storage scalability extremely and implements efficient querying of transactions.
文摘The content-based addressing method of Interplanetary File System(IPFS)leads to the lack of the function of retrieving relevant data through key information.To solve this problem,this paper proposes an efficient IPFS keyword retrieval model–IPFS-DKRM(IPFS-Distributed keyword retrieval model).This model combines the global index with Adaptive Radix Tree,and optimizes the storage mode of IPFS network and node-local data index:The model adopts the global index method and uses ART to store the key information of global index locally and stores the complete index information in IPFS to reduce the time of data retrieval and update;The nodes of network through the Publish-Subscribe Pattern synchronization index,and the use of Conflict-free Replication Data Type(CRDT)to maintain the final consistency of the global index of each node,to ensure that all nodes in the local to provide efficient retrieval services.In the simulation experiment,the index of open source data set Crosswikis was constructed,and the performance was analyzed based on the results of Siva data.The experimental results showed that compared with the Siva model,the response retrieval time of IPFS-DKRM was reduced by 75%,and the space occupied by node local storage index was reduced by 70%.It proves that the model only needs to occupy a small amount of space to store the global index information in the system to provide efficient retrieval function for IPFS,so that IPFS canmeet more application scenarios in the future.
