Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environmen...Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environment to select its efforts in the future efficiently.DRL has been used in many application fields,including games,robots,networks,etc.for creating autonomous systems that improve themselves with experience.It is well acknowledged that DRL is well suited to solve optimization problems in distributed systems in general and network routing especially.Therefore,a novel query routing approach called Deep Reinforcement Learning based Route Selection(DRLRS)is proposed for unstructured P2P networks based on a Deep Q-Learning algorithm.The main objective of this approach is to achieve better retrieval effectiveness with reduced searching cost by less number of connected peers,exchangedmessages,and reduced time.The simulation results shows a significantly improve searching a resource with compression to k-Random Walker and Directed BFS.Here,retrieval effectiveness,search cost in terms of connected peers,and average overhead are 1.28,106,149,respectively.展开更多
Unstructured P2P has power-law link distribution, and the random walk in power-law networks is analyzed. The analysis results show that the probability that a random walker walks through the high degree nodes is high ...Unstructured P2P has power-law link distribution, and the random walk in power-law networks is analyzed. The analysis results show that the probability that a random walker walks through the high degree nodes is high in the power-law network, and the information on the high degree nodes can be easily found through random walk. Random walk spread and random walk search method （RWSS） is proposed based on the analysis result. Simulation results show that RWSS achieves high success rates at low cost and is robust to high degree node failure.展开更多
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
Decentralized and unstructured peer-to-peer applications such as Gnutella are attractive because they require no centralized directories and no precise control over network topology or data placement. Search algorithm...Decentralized and unstructured peer-to-peer applications such as Gnutella are attractive because they require no centralized directories and no precise control over network topology or data placement. Search algorithm is the major component of the distributed system and its efficiency also does influence the systems performance. However the flooding-based query algorithm used in Gnutella produces huge traffic and does not scale well. Gnutella-like P2P topology has power-law characteristic, so a search algorithm was proposed based on high degree nodes of power-law network, High Degree Nodes-Based Search （HDNBS）. Extensive simulation results show that this algorithm performs on power-law networks very well, achieves almost 100% success rates, produces O（logN） messages per query and can locate target file within O（lagN） hops.展开更多
IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this...IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.展开更多
Combining the characteristics of peer-to-peer （P2P） and grid, a super-peer selection algorithm--SSABC is presented in the distributed network merging P2P and grid. The algorithm computes nodes capacities using their...Combining the characteristics of peer-to-peer （P2P） and grid, a super-peer selection algorithm--SSABC is presented in the distributed network merging P2P and grid. The algorithm computes nodes capacities using their resource properties provided by a grid monitoring and discovery system, such as available bandwidth, free CPU and idle memory, as well as the number of current connections and online time. when a new node joins the network and the super-peers are all saturated, it should select a new super-peer from the new node or joined nodes with the highest capacity. By theoretical analyses and simulation experiments, it is shown that super-peers selected by capacity can achieve higher query success rates and shorten the average hop count when compared with super-peers selected randomly, and they can also balance the network load when all super-peers are saturated. When the number of total nodes changes, the conclusion is still valid, which explains that the algorithm SSABC is feasible and stable.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
Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one...Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.展开更多
A P2P approaches to extend the ability of Video on Demand systems to serve more users. In the proposed system users share with each other the media data obtained and the media server is no longer the only source to ge...A P2P approaches to extend the ability of Video on Demand systems to serve more users. In the proposed system users share with each other the media data obtained and the media server is no longer the only source to get data from, thereby, the load on the media server could be greatly alleviated and the overall system capacity increases and more users could be served. The P2P streaming system introduces efficient searching;data transfer dynamically monitoring and initial buffering to maintain a high quality of playback. Its provider selection policy helps to reduce the load of the underlying network by avoiding remote data transfer.展开更多
For Peer-to-Peer (P2P) streaming services in mobile networks, the selection of appropriate neighbour peers from candidate peers with demanding data is an important approach to improve Quality-of-Service (QoS). This pa...For Peer-to-Peer (P2P) streaming services in mobile networks, the selection of appropriate neighbour peers from candidate peers with demanding data is an important approach to improve Quality-of-Service (QoS). This paper proposes a novel Effective Capacity Peer Selection (ECPS) scheme based on effective capacity. In the ECPS scheme, the neighbour peer selection problem was modeled using the Multiple Attribute Decision Making (MADM) theory, which considered multiple factors of candidate peers, including Signal to Interference and Noise Ratio (SINR), residency time, power level, security, moving speed, and effective capacity. This model could increase the suitability of ECPS for wireless mobile environments. Then, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to solve the MADM problem and identify the preferred neighbour peers. Simulation results show that the ECPS scheme can improve the network throughput, reduce packet delay by about 82%, and almost double the packet delivery ratio of the mobile P2P streaming service.展开更多
在分析现有P2P(peer to peer)路由算法的基础上,提出了一种基于二阶矩定位、支持多维资源数据描述的高效资源路由算法——FAN(flabellate addressable network)路由算法.FAN算法将节点映射到统一的多维笛卡尔空间,并以节点相对空间原点...在分析现有P2P(peer to peer)路由算法的基础上,提出了一种基于二阶矩定位、支持多维资源数据描述的高效资源路由算法——FAN(flabellate addressable network)路由算法.FAN算法将节点映射到统一的多维笛卡尔空间,并以节点相对空间原点的二阶矩作为子空间管理和资源搜索的依据.FAN路由算法具有O(log(N/k))的高路由效率,在节点加入和退出FAN网络时,更新路由信息的代价为O(klog(N/k)).实验结果表明,FAN路由算法具有路由效率高、维护代价小的优点,是一种P2P环境中支持多维资源数据描述的高效结构化资源路由算法.而且,目前部分基于CAN(content-addressable network)网络的改进算法也可以在FAN网络中适用,并获得更好的路由效率和更低的维护代价.展开更多
基金Authors would like to thank the Deanship of Scientific Research at Shaqra University for supporting this work under Project No.g01/n04.
文摘Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environment to select its efforts in the future efficiently.DRL has been used in many application fields,including games,robots,networks,etc.for creating autonomous systems that improve themselves with experience.It is well acknowledged that DRL is well suited to solve optimization problems in distributed systems in general and network routing especially.Therefore,a novel query routing approach called Deep Reinforcement Learning based Route Selection(DRLRS)is proposed for unstructured P2P networks based on a Deep Q-Learning algorithm.The main objective of this approach is to achieve better retrieval effectiveness with reduced searching cost by less number of connected peers,exchangedmessages,and reduced time.The simulation results shows a significantly improve searching a resource with compression to k-Random Walker and Directed BFS.Here,retrieval effectiveness,search cost in terms of connected peers,and average overhead are 1.28,106,149,respectively.
文摘Unstructured P2P has power-law link distribution, and the random walk in power-law networks is analyzed. The analysis results show that the probability that a random walker walks through the high degree nodes is high in the power-law network, and the information on the high degree nodes can be easily found through random walk. Random walk spread and random walk search method （RWSS） is proposed based on the analysis result. Simulation results show that RWSS achieves high success rates at low cost and is robust to high degree node failure.
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.
文摘Decentralized and unstructured peer-to-peer applications such as Gnutella are attractive because they require no centralized directories and no precise control over network topology or data placement. Search algorithm is the major component of the distributed system and its efficiency also does influence the systems performance. However the flooding-based query algorithm used in Gnutella produces huge traffic and does not scale well. Gnutella-like P2P topology has power-law characteristic, so a search algorithm was proposed based on high degree nodes of power-law network, High Degree Nodes-Based Search （HDNBS）. Extensive simulation results show that this algorithm performs on power-law networks very well, achieves almost 100% success rates, produces O（logN） messages per query and can locate target file within O（lagN） hops.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60672124 and 60832009)Hi-Tech Research and Development Program(National 863 Program)(Grant No.2007AA01Z221)
文摘IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.
基金The National High Technology Research and Development Program of China (863 Program) (No.2007AA01Z422)the NaturalFoundation of Anhui Provincial Education Department (No.2006KJ041B,KJ2007B073)
文摘Combining the characteristics of peer-to-peer （P2P） and grid, a super-peer selection algorithm--SSABC is presented in the distributed network merging P2P and grid. The algorithm computes nodes capacities using their resource properties provided by a grid monitoring and discovery system, such as available bandwidth, free CPU and idle memory, as well as the number of current connections and online time. when a new node joins the network and the super-peers are all saturated, it should select a new super-peer from the new node or joined nodes with the highest capacity. By theoretical analyses and simulation experiments, it is shown that super-peers selected by capacity can achieve higher query success rates and shorten the average hop count when compared with super-peers selected randomly, and they can also balance the network load when all super-peers are saturated. When the number of total nodes changes, the conclusion is still valid, which explains that the algorithm SSABC is feasible and stable.
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.
基金Project supported by the National Natural Science Foundation of China (No. 60302004)the Natural Science Foundation of HubeiProvince, China (No. 2005ABA264)
文摘Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.
文摘A P2P approaches to extend the ability of Video on Demand systems to serve more users. In the proposed system users share with each other the media data obtained and the media server is no longer the only source to get data from, thereby, the load on the media server could be greatly alleviated and the overall system capacity increases and more users could be served. The P2P streaming system introduces efficient searching;data transfer dynamically monitoring and initial buffering to maintain a high quality of playback. Its provider selection policy helps to reduce the load of the underlying network by avoiding remote data transfer.
基金supported in part by the National Natural Science Foundation of China under Grant No. 60902047the Fundamental Research Funds for the Central Universities under Grant No. BUPT2013RC0111
文摘For Peer-to-Peer (P2P) streaming services in mobile networks, the selection of appropriate neighbour peers from candidate peers with demanding data is an important approach to improve Quality-of-Service (QoS). This paper proposes a novel Effective Capacity Peer Selection (ECPS) scheme based on effective capacity. In the ECPS scheme, the neighbour peer selection problem was modeled using the Multiple Attribute Decision Making (MADM) theory, which considered multiple factors of candidate peers, including Signal to Interference and Noise Ratio (SINR), residency time, power level, security, moving speed, and effective capacity. This model could increase the suitability of ECPS for wireless mobile environments. Then, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to solve the MADM problem and identify the preferred neighbour peers. Simulation results show that the ECPS scheme can improve the network throughput, reduce packet delay by about 82%, and almost double the packet delivery ratio of the mobile P2P streaming service.
基金国家高技术研究发展计划(863)(the National High- Tech Research and Development Plan of China under Grant No.2005AA1032)中国下一代互联网示范项目(the China Next Generation Internet(CNGI) under Grant No.CNGI-04-15-2A)
