One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying que...One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.展开更多
It is universally acknowledged by network security experts that proactive peer-to-peer (P2P) worms may soon en-gender serious threats to the Internet infrastructures. These latent threats stimulate activities of model...It is universally acknowledged by network security experts that proactive peer-to-peer (P2P) worms may soon en-gender serious threats to the Internet infrastructures. These latent threats stimulate activities of modeling and analysis of the proactive P2P worm propagation. Based on the classical two-factor model,in this paper,we propose a novel proactive worm propagation model in unstructured P2P networks (called the four-factor model) by considering four factors:(1) network topology,(2) countermeasures taken by Internet service providers (ISPs) and users,(3) configuration diversity of nodes in the P2P network,and (4) attack and defense strategies. Simulations and experiments show that proactive P2P worms can be slowed down by two ways:improvement of the configuration diversity of the P2P network and using powerful rules to reinforce the most connected nodes from being compromised. The four-factor model provides a better description and prediction of the proactive P2P worm propagation.展开更多
It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only fo...It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.展开更多
Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received pa...Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.展开更多
This paper analyzes the characteristics of the Peer-to-Peer （P2P） active worm and its attacking mechanism, and then proposes a mathematical model of propagation of the P2P active worm applying Epidemiology. Based on...This paper analyzes the characteristics of the Peer-to-Peer （P2P） active worm and its attacking mechanism, and then proposes a mathematical model of propagation of the P2P active worm applying Epidemiology. Based on the analysis on the protocols of realistic P2P systems, a software which can be used to simulate the P2P network environment and the propagation of P2P active worm is imple- mented in this paper. A large number of simulation experiments are performed using the developed simulation software. The results from these simulation experiments validate the proposed model, which means that the model can be used to analyze the spreading behaviors of the P2P active worm and predict its trend.展开更多
Peer-to-peer(P2P)energy trading enables an efficient regulation of distributed renewable energy among prosumers,implicitly promoting low-carbon operation.This study proposes a novel P2P energy trading scheme with coup...Peer-to-peer(P2P)energy trading enables an efficient regulation of distributed renewable energy among prosumers,implicitly promoting low-carbon operation.This study proposes a novel P2P energy trading scheme with coupled electricity-carbon(E/C)market that co-optimizes both power and carbon emission flows.To facilitate the low-carbon operations in the market,we introduce a prosumer-driven carbon-aware distribution locational marginal price(PDC-DLMP)to serve as a pricing signal for the distribution system operator(DSO).To efficiently determine the optimal trading solutions,we adopt a two-layer data-driven approach.The first layer employs a reinforcement learning algorithm named multi-agent twin-delayed deep deterministic policy gradient(MATD3);the second layer uses a deep neural network(DNN)driven surrogate model,which is designed to map the PDC-DLMP signals,thereby eliminating the need for direct DSO intervention during market operation.This approach protects the physical model parameters of the distribution network and ensures multi-level privacy protection.Simulation results validate the effectiveness of the proposed P2P energy trading scheme with coupled E/C market,demonstrating its ability to achieve both reduced carbon emissions and lower operational costs for microgrid prosumers.展开更多
High-performance computing(HPC)systems are about to reach a new height:exascale.Application deployment is becoming an increasingly prominent problem.Container technology solves the problems of encapsulation and migrat...High-performance computing(HPC)systems are about to reach a new height:exascale.Application deployment is becoming an increasingly prominent problem.Container technology solves the problems of encapsulation and migration of applications and their execution environment.However,the container image is too large,and deploying the image to a large number of compute nodes is time-consuming.Although the peer-to-peer(P2P)approach brings higher transmission efficiency,it introduces larger network load.All of these issues lead to high startup latency of the application.To solve these problems,we propose the topology-aware execution environment service(TEES)for fast and agile application deployment on HPC systems.TEES creates a more lightweight execution environment for users,and uses a more efficient topology-aware P2P approach to reduce deployment time.Combined with a split-step transport and launch-in-advance mechanism,TEES reduces application startup latency.In the Tianhe HPC system,TEES realizes the deployment and startup of a typical application on 17560 compute nodes within 3 s.Compared to container-based application deployment,the speed is increased by 12-fold,and the network load is reduced by 85%.展开更多
文摘One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.
基金Project (No. 09511501600) partially supported by the Science and Technology Commission of Shanghai Municipality, China
文摘It is universally acknowledged by network security experts that proactive peer-to-peer (P2P) worms may soon en-gender serious threats to the Internet infrastructures. These latent threats stimulate activities of modeling and analysis of the proactive P2P worm propagation. Based on the classical two-factor model,in this paper,we propose a novel proactive worm propagation model in unstructured P2P networks (called the four-factor model) by considering four factors:(1) network topology,(2) countermeasures taken by Internet service providers (ISPs) and users,(3) configuration diversity of nodes in the P2P network,and (4) attack and defense strategies. Simulations and experiments show that proactive P2P worms can be slowed down by two ways:improvement of the configuration diversity of the P2P network and using powerful rules to reinforce the most connected nodes from being compromised. The four-factor model provides a better description and prediction of the proactive P2P worm propagation.
基金supported by National Natural Science Foundation of China (No.60873231)Research Fund for the Doctoral Program of Higher Education (No.20093223120001)+2 种基金Science and Technology Support Program of Jiangsu Province (No.BE2009158)Natural Science Fund of Higher Education of Jiangsu Province(No.09KJB520010)Special Fund for Fast Sharing of Science Paper in Net Era by CSTD (No.2009117)
文摘It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.
文摘Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.
文摘This paper analyzes the characteristics of the Peer-to-Peer （P2P） active worm and its attacking mechanism, and then proposes a mathematical model of propagation of the P2P active worm applying Epidemiology. Based on the analysis on the protocols of realistic P2P systems, a software which can be used to simulate the P2P network environment and the propagation of P2P active worm is imple- mented in this paper. A large number of simulation experiments are performed using the developed simulation software. The results from these simulation experiments validate the proposed model, which means that the model can be used to analyze the spreading behaviors of the P2P active worm and predict its trend.
基金supported in part by the National Natural Science Foundation of China(No.52107100)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX24-0657)。
文摘Peer-to-peer(P2P)energy trading enables an efficient regulation of distributed renewable energy among prosumers,implicitly promoting low-carbon operation.This study proposes a novel P2P energy trading scheme with coupled electricity-carbon(E/C)market that co-optimizes both power and carbon emission flows.To facilitate the low-carbon operations in the market,we introduce a prosumer-driven carbon-aware distribution locational marginal price(PDC-DLMP)to serve as a pricing signal for the distribution system operator(DSO).To efficiently determine the optimal trading solutions,we adopt a two-layer data-driven approach.The first layer employs a reinforcement learning algorithm named multi-agent twin-delayed deep deterministic policy gradient(MATD3);the second layer uses a deep neural network(DNN)driven surrogate model,which is designed to map the PDC-DLMP signals,thereby eliminating the need for direct DSO intervention during market operation.This approach protects the physical model parameters of the distribution network and ensures multi-level privacy protection.Simulation results validate the effectiveness of the proposed P2P energy trading scheme with coupled E/C market,demonstrating its ability to achieve both reduced carbon emissions and lower operational costs for microgrid prosumers.
基金Project supported by the National Natural Science Foundation of China(No.61902405)the Tianhe Supercomputer Project of China(No.2018YFB0204301)+1 种基金the PDL Research Fund of China(No.6142110190404)the National High-Level Personnel for Defense Technology Program,China(No.2017-JCJQ-ZQ-013)。
文摘High-performance computing(HPC)systems are about to reach a new height:exascale.Application deployment is becoming an increasingly prominent problem.Container technology solves the problems of encapsulation and migration of applications and their execution environment.However,the container image is too large,and deploying the image to a large number of compute nodes is time-consuming.Although the peer-to-peer(P2P)approach brings higher transmission efficiency,it introduces larger network load.All of these issues lead to high startup latency of the application.To solve these problems,we propose the topology-aware execution environment service(TEES)for fast and agile application deployment on HPC systems.TEES creates a more lightweight execution environment for users,and uses a more efficient topology-aware P2P approach to reduce deployment time.Combined with a split-step transport and launch-in-advance mechanism,TEES reduces application startup latency.In the Tianhe HPC system,TEES realizes the deployment and startup of a typical application on 17560 compute nodes within 3 s.Compared to container-based application deployment,the speed is increased by 12-fold,and the network load is reduced by 85%.
