Pub Date : 2024-10-16DOI: 10.1109/TNET.2024.3473571
{"title":"IEEE/ACM Transactions on Networking Society Information","authors":"","doi":"10.1109/TNET.2024.3473571","DOIUrl":"https://doi.org/10.1109/TNET.2024.3473571","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 5","pages":"C3-C3"},"PeriodicalIF":3.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720575","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1109/TNET.2024.3466245
Avi Mizrahi;Noam Koren;Ori Rottenstreich;Yuval Cassuto
Merkle trees play a crucial role in blockchain networks in organizing network state. They allow proving a particular value of an entry in the state to a node that maintains only the root of the Merkle trees, a hash-based signature computed over the data in a hierarchical manner. Verification of particular state entries is crucial in reaching a consensus on the execution of a block where state information is required in the processing of its transactions. For instance, a payment transaction should be based on the balance of the two involved accounts. The proof length affects the network communication and is typically logarithmic in the state size. In this paper, we take advantage of typical transaction characteristics for better organizing Merkle trees to improve blockchain network performance. We focus on the common transaction processing where Merkle proofs are jointly provided for multiple accounts. We first provide lower bounds for the communication cost that are based on the distribution of accounts involved in the transactions. We then describe algorithms that consider traffic patterns for significantly reducing it. The algorithms are inspired by various coding methods such as Huffman coding, partition and weight balancing. We also generalize our approach towards the encoding of smart contract transactions that involve an arbitrary number of accounts. Likewise, we rely on real blockchain data to show the savings allowed by our approach. The experimental evaluation is based on transactions from the Ethereum network and demonstrates cost reduction for both payment transactions and smart contract transactions.
{"title":"Traffic-Aware Merkle Trees for Shortening Blockchain Transaction Proofs","authors":"Avi Mizrahi;Noam Koren;Ori Rottenstreich;Yuval Cassuto","doi":"10.1109/TNET.2024.3466245","DOIUrl":"https://doi.org/10.1109/TNET.2024.3466245","url":null,"abstract":"Merkle trees play a crucial role in blockchain networks in organizing network state. They allow proving a particular value of an entry in the state to a node that maintains only the root of the Merkle trees, a hash-based signature computed over the data in a hierarchical manner. Verification of particular state entries is crucial in reaching a consensus on the execution of a block where state information is required in the processing of its transactions. For instance, a payment transaction should be based on the balance of the two involved accounts. The proof length affects the network communication and is typically logarithmic in the state size. In this paper, we take advantage of typical transaction characteristics for better organizing Merkle trees to improve blockchain network performance. We focus on the common transaction processing where Merkle proofs are jointly provided for multiple accounts. We first provide lower bounds for the communication cost that are based on the distribution of accounts involved in the transactions. We then describe algorithms that consider traffic patterns for significantly reducing it. The algorithms are inspired by various coding methods such as Huffman coding, partition and weight balancing. We also generalize our approach towards the encoding of smart contract transactions that involve an arbitrary number of accounts. Likewise, we rely on real blockchain data to show the savings allowed by our approach. The experimental evaluation is based on transactions from the Ethereum network and demonstrates cost reduction for both payment transactions and smart contract transactions.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"5326-5340"},"PeriodicalIF":3.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1109/TNET.2024.3446689
Chuwen Zhang;Yong Feng;Haoyu Song;Ying Wan;Wenquan Xu;Bin Liu
Software-based IP route lookup is a key component for packet forwarding in Software Defined Networks. Running lookup algorithms on commodity CPUs is flexible and scalable, which shows advantages on cost and power consumption over the hardware-based forwarding engines. However, dynamic network functions and services make route updates more frequent than ever. Existing algorithms often fall short of the incremental update requirements. In this paper, we propose the Overlay BitMap Algorithm (OBMA), which contains several variations, to support extraordinary update performance while maintaining the highest-in-class lookup speed and storage efficiency. Starting from the basic OBMA_B, we develop two variations with different tradeoffs for different application scenarios. OBMA_L supports faster lookups than OBMA_B at a small cost of update speed. OBMA_S achieves better storage efficiency than OBMA_B at a small cost of lookup throughput. We run our algorithms on a commodity CPU and evaluate them with real-world route tables and traces. The experiments show that OBMA achieves the lowest memory footprint, the highest update speed, and over 200 Mpps lookup throughput. Specifically, OBMA_S reduces the memory footprint to 3.98 bytes/prefix which is 25.33% smaller that of the state-of-the-art Poptrie; OBMA_L supports 252.02 Mpps lookup throughput with a single thread, and more than 600 Mpps with multiple parallel threads in a single CPU, significantly outperforming the state-of-the-art Poptrie and SAIL; OBMA_B supports updates at a rate of 14.58M updates/s which is 15 times faster than Poptrie. The tests show that the update process has little interference with the lookup process for OBMA, and achieves zero-interrupt to lookups with multiple threads.
{"title":"OBMA: Scalable Route Lookups With Fast and Zero-Interrupt Updates","authors":"Chuwen Zhang;Yong Feng;Haoyu Song;Ying Wan;Wenquan Xu;Bin Liu","doi":"10.1109/TNET.2024.3446689","DOIUrl":"https://doi.org/10.1109/TNET.2024.3446689","url":null,"abstract":"Software-based IP route lookup is a key component for packet forwarding in Software Defined Networks. Running lookup algorithms on commodity CPUs is flexible and scalable, which shows advantages on cost and power consumption over the hardware-based forwarding engines. However, dynamic network functions and services make route updates more frequent than ever. Existing algorithms often fall short of the incremental update requirements. In this paper, we propose the Overlay BitMap Algorithm (OBMA), which contains several variations, to support extraordinary update performance while maintaining the highest-in-class lookup speed and storage efficiency. Starting from the basic OBMA_B, we develop two variations with different tradeoffs for different application scenarios. OBMA_L supports faster lookups than OBMA_B at a small cost of update speed. OBMA_S achieves better storage efficiency than OBMA_B at a small cost of lookup throughput. We run our algorithms on a commodity CPU and evaluate them with real-world route tables and traces. The experiments show that OBMA achieves the lowest memory footprint, the highest update speed, and over 200 Mpps lookup throughput. Specifically, OBMA_S reduces the memory footprint to 3.98 bytes/prefix which is 25.33% smaller that of the state-of-the-art Poptrie; OBMA_L supports 252.02 Mpps lookup throughput with a single thread, and more than 600 Mpps with multiple parallel threads in a single CPU, significantly outperforming the state-of-the-art Poptrie and SAIL; OBMA_B supports updates at a rate of 14.58M updates/s which is 15 times faster than Poptrie. The tests show that the update process has little interference with the lookup process for OBMA, and achieves zero-interrupt to lookups with multiple threads.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"4842-4854"},"PeriodicalIF":3.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1109/TNET.2024.3471335
Ruixiang Li;Xiaoyun Yuan;Meijuan Yin;Xiangyang Luo
Mobile IP geolocation aims to obtain a mobile device’s geographic location by IP. This technology is widely used in preventing financial risk, investigating cybercrime, and delivering targeted information. Currently, there are three types of IP geolocation: based on cooperation, querying in database, or network measurement. However, since restricted cooperation, low-reliability databases, and unresponsive mobile IPs, existing technologies are hard to geolocate fine-grained location of mobile IP. In this paper, we propose the concept of district anchor, and propose a non-cooperative mobile IP geolocation scheme, including three parts: acquiring district anchors by clustering, evaluating the reliability of district anchors, and geolocating mobile IPs. We also give implemented approach of this scheme. Instead of using existing clustering algorithms treating IPs and geolocations in no particular order, we propose two-stages clustering algorithm (IPG2C) to acquire district anchors, and establish reliability evaluation mechanism by IP distribution and spatial distribution of cluster. Eventually, using obtained reliable district anchors, we use “subnet geolocation” strategy to geolocate mobile IPs. The experimental results in 10 cities show that: 1) our scheme can be used to geolocate mobile IPs without cooperation; 2) the mean geolocation error is 12.47km, where precision of 56.67% of mobile IPs is street-level and minimum error is only 13m; 3) that the mean geolocation error of the anchor-based method is smaller than that of the landmark-based method; 4) compared with 13 clustering algorithms (e.g., K-Means++, Mean Shift, DBSCAN, and GMM), mean geolocation error using IPG2C’s district anchors is reduced by 26.62%~50.77%.
{"title":"Mobile IP Geolocation Based on District Anchor Without Cooperation of Users or Internet Service Providers","authors":"Ruixiang Li;Xiaoyun Yuan;Meijuan Yin;Xiangyang Luo","doi":"10.1109/TNET.2024.3471335","DOIUrl":"https://doi.org/10.1109/TNET.2024.3471335","url":null,"abstract":"Mobile IP geolocation aims to obtain a mobile device’s geographic location by IP. This technology is widely used in preventing financial risk, investigating cybercrime, and delivering targeted information. Currently, there are three types of IP geolocation: based on cooperation, querying in database, or network measurement. However, since restricted cooperation, low-reliability databases, and unresponsive mobile IPs, existing technologies are hard to geolocate fine-grained location of mobile IP. In this paper, we propose the concept of district anchor, and propose a non-cooperative mobile IP geolocation scheme, including three parts: acquiring district anchors by clustering, evaluating the reliability of district anchors, and geolocating mobile IPs. We also give implemented approach of this scheme. Instead of using existing clustering algorithms treating IPs and geolocations in no particular order, we propose two-stages clustering algorithm (IPG2C) to acquire district anchors, and establish reliability evaluation mechanism by IP distribution and spatial distribution of cluster. Eventually, using obtained reliable district anchors, we use “subnet geolocation” strategy to geolocate mobile IPs. The experimental results in 10 cities show that: 1) our scheme can be used to geolocate mobile IPs without cooperation; 2) the mean geolocation error is 12.47km, where precision of 56.67% of mobile IPs is street-level and minimum error is only 13m; 3) that the mean geolocation error of the anchor-based method is smaller than that of the landmark-based method; 4) compared with 13 clustering algorithms (e.g., K-Means++, Mean Shift, DBSCAN, and GMM), mean geolocation error using IPG2C’s district anchors is reduced by 26.62%~50.77%.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"5507-5523"},"PeriodicalIF":3.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, there exists a lot of cross-region data transmission demand on the cloud. It is promising to use serverless computing for data compressing to save the total data size. However, it is challenging to estimate the data transmission time and monetary cost with serverless compression. In addition, minimizing the data transmission cost is non-trivial due to the enormous parameter space. This paper focuses on this problem and makes the following contributions: 1) We propose empirical data transmission time and monetary cost models based on serverless compression. It can also predict compression information, e.g., ratio and speed using chunk sampling and machine learning techniques. 2) For single-task cloud data transmission, we propose two efficient parameter search methods based on Sequential Quadratic Programming (SQP) and Eliminate then Divide and Conquer (EDC) with proven error upper bounds. Besides, we propose a parameter fine-tuning strategy to deal with transmission bandwidth variance. 3) Furthermore, for multi-task scenarios, a parameter search method based on dynamic programming and numerical computation is proposed. We have implemented the system called Fluid-Shuttle, which includes straggler optimization, cache optimization, and the autoscaling decompression mechanism. Finally, we evaluate the performance of Fluid-Shuttle with various workloads and applications on the real-world AWS serverless computing platform. Experimental results show that the proposed approach can improve the parameter search efficiency by over $3times $ compared with the state-of-art methods and achieves better parameter quality. In addition, our approach achieves higher time efficiency and lower monetary cost compared with competing cloud data transmission approaches.
{"title":"Fluid-Shuttle: Efficient Cloud Data Transmission Based on Serverless Computing Compression","authors":"Rong Gu;Shulin Wang;Haipeng Dai;Xiaofei Chen;Zhaokang Wang;Wenjie Bao;Jiaqi Zheng;Yaofeng Tu;Yihua Huang;Lianyong Qi;Xiaolong Xu;Wanchun Dou;Guihai Chen","doi":"10.1109/TNET.2024.3402561","DOIUrl":"https://doi.org/10.1109/TNET.2024.3402561","url":null,"abstract":"Nowadays, there exists a lot of cross-region data transmission demand on the cloud. It is promising to use serverless computing for data compressing to save the total data size. However, it is challenging to estimate the data transmission time and monetary cost with serverless compression. In addition, minimizing the data transmission cost is non-trivial due to the enormous parameter space. This paper focuses on this problem and makes the following contributions: 1) We propose empirical data transmission time and monetary cost models based on serverless compression. It can also predict compression information, e.g., ratio and speed using chunk sampling and machine learning techniques. 2) For single-task cloud data transmission, we propose two efficient parameter search methods based on Sequential Quadratic Programming (SQP) and Eliminate then Divide and Conquer (EDC) with proven error upper bounds. Besides, we propose a parameter fine-tuning strategy to deal with transmission bandwidth variance. 3) Furthermore, for multi-task scenarios, a parameter search method based on dynamic programming and numerical computation is proposed. We have implemented the system called Fluid-Shuttle, which includes straggler optimization, cache optimization, and the autoscaling decompression mechanism. Finally, we evaluate the performance of Fluid-Shuttle with various workloads and applications on the real-world AWS serverless computing platform. Experimental results show that the proposed approach can improve the parameter search efficiency by over \u0000<inline-formula> <tex-math>$3times $ </tex-math></inline-formula>\u0000 compared with the state-of-art methods and achieves better parameter quality. In addition, our approach achieves higher time efficiency and lower monetary cost compared with competing cloud data transmission approaches.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"4554-4569"},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1109/TNET.2024.3468350
Sen Zhao;Shouguo Yang;Zhen Wang;Yongji Liu;Hongsong Zhu;Limin Sun
Protocol reverse engineering (PRE) serves as an instrumental tool in various security research, such as protocol fuzzing and intrusion detection. Its primary objective lies in uncovering the format, semantics, and behavior of an unknown protocol without prior information. This paper presents DL-ProS2, a deep learning-based approach for binary protocol reversing, focusing on format segmentation and semantic inference from network traffic. Our approach is underpinned by highlighting the effectiveness of multi-scale features within the network traffic for identifying various types of fields and semantics. Based on this, DL-ProS2 employs a comprehensive end-to-end model that integrates U-Net, siamese network, and BiLSTM-CRF, which enables the effective analysis of unknown protocol traffic to extract the field boundaries and semantics. Meanwhile, to address the issue of limited data diversity and coverage, we implement an innovative knowledge-driven traffic simulation technique. This method harnesses the ChatGPT to extract protocol knowledge from publicly available protocol documents, such as RFCs, as the foundational rules for the simulation. Empirical results substantiate the efficacy of our approach, demonstrating precision rates exceeding 0.95 and recall rates surpassing 0.97 for partially unknown protocol format segmentation and semantic inference. It also retains effectiveness in the inference of completely unknown protocols, with average precision and recall rates of 0.69 and 0.62 for format segmentation, and 0.43 and 0.47 for semantic inference, respectively.
{"title":"Crafting Binary Protocol Reversing via Deep Learning With Knowledge-Driven Augmentation","authors":"Sen Zhao;Shouguo Yang;Zhen Wang;Yongji Liu;Hongsong Zhu;Limin Sun","doi":"10.1109/TNET.2024.3468350","DOIUrl":"https://doi.org/10.1109/TNET.2024.3468350","url":null,"abstract":"Protocol reverse engineering (PRE) serves as an instrumental tool in various security research, such as protocol fuzzing and intrusion detection. Its primary objective lies in uncovering the format, semantics, and behavior of an unknown protocol without prior information. This paper presents DL-ProS2, a deep learning-based approach for binary protocol reversing, focusing on format segmentation and semantic inference from network traffic. Our approach is underpinned by highlighting the effectiveness of multi-scale features within the network traffic for identifying various types of fields and semantics. Based on this, DL-ProS2 employs a comprehensive end-to-end model that integrates U-Net, siamese network, and BiLSTM-CRF, which enables the effective analysis of unknown protocol traffic to extract the field boundaries and semantics. Meanwhile, to address the issue of limited data diversity and coverage, we implement an innovative knowledge-driven traffic simulation technique. This method harnesses the ChatGPT to extract protocol knowledge from publicly available protocol documents, such as RFCs, as the foundational rules for the simulation. Empirical results substantiate the efficacy of our approach, demonstrating precision rates exceeding 0.95 and recall rates surpassing 0.97 for partially unknown protocol format segmentation and semantic inference. It also retains effectiveness in the inference of completely unknown protocols, with average precision and recall rates of 0.69 and 0.62 for format segmentation, and 0.43 and 0.47 for semantic inference, respectively.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"5399-5414"},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1109/TNET.2024.3465844
Yuchen Sun;Lailong Luo;Deke Guo;Li Liu;Junjie Xie
Edge storage promises to be crucial for edge computing infrastructure, which enables users to access data within a low delay from widespread storage nodes at the network edge. The key challenge is how to integrate massive geographically distributed weak edge nodes to form an efficient storage system, enabling users to launch data operations from any node or retrieve the desired data across the entire distributed system. To address this data-sharing problem, researchers from both the traditional peer-to-peer (P2P) overlay networking and emerging edge computing fields have proposed some decentralized indexing mechanisms. However, existing studies lack insightful descriptions and analyses about the nature of the data-sharing problem at the network edge. It motivates us to rethink the edge data-sharing framework and provide the problem reformulation for analyzing the limitations of existing schemes. We reveal that the existing data-sharing schemes fail in complex network topologies which can be regarded as high-dimensional network spaces beyond the representation of low-dimensional Euclidean spaces or other existing hash spaces. A better space abstraction is an urgent need to alleviate the performance degradation due to the dimensional mismatch between network spaces and virtual spaces. To fill this gap, this paper proposes the Kautz metric space, a novel space abstraction extended from Kautz graphs, where the coordinates and the metric are defined as Kautz strings and Kautz distances (i.e., the shortest distances in undirected Kautz graphs), respectively. We design a dynamic programming algorithm to directly compute the Kautz distances. Then, we propose KMSharing, an efficient edge data-sharing scheme: both nodes and data are represented in a Kautz metric space, where the Kautz distance of any two Kautz strings reflects the network delay of the corresponding nodes. The workflow of KMSharing consists of three core components: the virtual address allocation represents edge nodes in the Kautz metric space; the data-to-node mapping ensures the uniqueness of target nodes; and forwarding table construction ensures the data delivery. Theoretical analyses confirm that KMSharing ideally achieves <inline-formula> <tex-math>$mathcal {O}left ({{ tau }}right)$ </tex-math></inline-formula> network delays, <inline-formula> <tex-math>$mathcal {O}left ({{ log N }}right)$ </tex-math></inline-formula> overlay hops, and <inline-formula> <tex-math>$mathcal {O}left ({{ 1 }}right)$ </tex-math></inline-formula> forwarding entries in an N-node edge system with the network radius <inline-formula> <tex-math>$tau $ </tex-math></inline-formula> , while the successive ensuring data delivery. Its worst-case network delay <inline-formula> <tex-math>$mathcal {O}left ({{ tau log N }}right)$ </tex-math></inline-formula> is also much better than <inline-formula> <tex-math>${mathcal {O}left ({{ tau N^{alpha } }}right)},alpha mathrm {in }(0,1)$ </tex-math></inline-formula> , t
{"title":"KMSharing: The Framework and Space Abstraction for Efficient Data Sharing at the Network Edge","authors":"Yuchen Sun;Lailong Luo;Deke Guo;Li Liu;Junjie Xie","doi":"10.1109/TNET.2024.3465844","DOIUrl":"https://doi.org/10.1109/TNET.2024.3465844","url":null,"abstract":"Edge storage promises to be crucial for edge computing infrastructure, which enables users to access data within a low delay from widespread storage nodes at the network edge. The key challenge is how to integrate massive geographically distributed weak edge nodes to form an efficient storage system, enabling users to launch data operations from any node or retrieve the desired data across the entire distributed system. To address this data-sharing problem, researchers from both the traditional peer-to-peer (P2P) overlay networking and emerging edge computing fields have proposed some decentralized indexing mechanisms. However, existing studies lack insightful descriptions and analyses about the nature of the data-sharing problem at the network edge. It motivates us to rethink the edge data-sharing framework and provide the problem reformulation for analyzing the limitations of existing schemes. We reveal that the existing data-sharing schemes fail in complex network topologies which can be regarded as high-dimensional network spaces beyond the representation of low-dimensional Euclidean spaces or other existing hash spaces. A better space abstraction is an urgent need to alleviate the performance degradation due to the dimensional mismatch between network spaces and virtual spaces. To fill this gap, this paper proposes the Kautz metric space, a novel space abstraction extended from Kautz graphs, where the coordinates and the metric are defined as Kautz strings and Kautz distances (i.e., the shortest distances in undirected Kautz graphs), respectively. We design a dynamic programming algorithm to directly compute the Kautz distances. Then, we propose KMSharing, an efficient edge data-sharing scheme: both nodes and data are represented in a Kautz metric space, where the Kautz distance of any two Kautz strings reflects the network delay of the corresponding nodes. The workflow of KMSharing consists of three core components: the virtual address allocation represents edge nodes in the Kautz metric space; the data-to-node mapping ensures the uniqueness of target nodes; and forwarding table construction ensures the data delivery. Theoretical analyses confirm that KMSharing ideally achieves \u0000<inline-formula> <tex-math>$mathcal {O}left ({{ tau }}right)$ </tex-math></inline-formula>\u0000 network delays, \u0000<inline-formula> <tex-math>$mathcal {O}left ({{ log N }}right)$ </tex-math></inline-formula>\u0000 overlay hops, and \u0000<inline-formula> <tex-math>$mathcal {O}left ({{ 1 }}right)$ </tex-math></inline-formula>\u0000 forwarding entries in an N-node edge system with the network radius \u0000<inline-formula> <tex-math>$tau $ </tex-math></inline-formula>\u0000, while the successive ensuring data delivery. Its worst-case network delay \u0000<inline-formula> <tex-math>$mathcal {O}left ({{ tau log N }}right)$ </tex-math></inline-formula>\u0000 is also much better than \u0000<inline-formula> <tex-math>${mathcal {O}left ({{ tau N^{alpha } }}right)},alpha mathrm {in }(0,1)$ </tex-math></inline-formula>\u0000, t","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"5440-5458"},"PeriodicalIF":3.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/TNET.2024.3469396
Dian Shen;Bin Yang;Junxue Zhang;Fang Dong;John C. S. Lui
MPTCP provides the basic multipath support for network applications to deliver high throughput and robust communication. However, the original MPTCP is designed with limited extensibility. Various research works have tried to extend MPTCP to attain better performance or richer functionalities. These existing approaches either modify the kernel implementation of MPTCP, which involve considerable engineering efforts and may accidentally introduce safety issues, or control MPTCP via userspace tools, which suffer from restricted functionality support. To address this issue, we propose eMPTCP, an easy-to-use framework to fully extend MPTCP without safety risks. Internally, eMPTCP has a modular and pluggable model which allows operators to specify a comprehensive MPTCP extension as a chain of sub-policies. eMPTCP further enforces the policies through packet header manipulations. To ensure safety, eMPTCP is implemented using eBPF. Despite the stringent constraints of eBPF, we show that it is possible to implement an elaborated framework for a fully extensible MPTCP. Through verifying MPTCP in a number of real-world cases and extensive experiments, we show that eMPTCP is able to support a wide range of MPTCP extensions, while the overhead of eMPTCP operations in the kernel is in the scale of nanosecond, and the extra processing time accounts for only about 0.63% of flows’ transmission time.
{"title":"eMPTCP: A Framework to Fully Extend Multipath TCP","authors":"Dian Shen;Bin Yang;Junxue Zhang;Fang Dong;John C. S. Lui","doi":"10.1109/TNET.2024.3469396","DOIUrl":"https://doi.org/10.1109/TNET.2024.3469396","url":null,"abstract":"MPTCP provides the basic multipath support for network applications to deliver high throughput and robust communication. However, the original MPTCP is designed with limited extensibility. Various research works have tried to extend MPTCP to attain better performance or richer functionalities. These existing approaches either modify the kernel implementation of MPTCP, which involve considerable engineering efforts and may accidentally introduce safety issues, or control MPTCP via userspace tools, which suffer from restricted functionality support. To address this issue, we propose eMPTCP, an easy-to-use framework to fully extend MPTCP without safety risks. Internally, eMPTCP has a modular and pluggable model which allows operators to specify a comprehensive MPTCP extension as a chain of sub-policies. eMPTCP further enforces the policies through packet header manipulations. To ensure safety, eMPTCP is implemented using eBPF. Despite the stringent constraints of eBPF, we show that it is possible to implement an elaborated framework for a fully extensible MPTCP. Through verifying MPTCP in a number of real-world cases and extensive experiments, we show that eMPTCP is able to support a wide range of MPTCP extensions, while the overhead of eMPTCP operations in the kernel is in the scale of nanosecond, and the extra processing time accounts for only about 0.63% of flows’ transmission time.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":"32 6","pages":"5459-5474"},"PeriodicalIF":3.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/TNET.2024.3470649
Xiang Tian;Baoxian Zhang;Cheng Li;Jiguo Yu
Disseminating continuous packet flows injected at multiple location-random source nodes to all network nodes, known as the multi-source dynamic global broadcast problem, is a fundamental building block for wireless multi-hop networks to run smoothly and efficiently. Previous studies on dynamic global broadcast all assume reliable communications. However, in realistic wireless networks, there exist unpredictable transmission failures caused by the randomized signal interference from uncorrelated wireless networks sharing the same spectrum or even malicious attackers. In this paper, by integrating the Signal-to-Interference-plus-Noise-Ratio (SINR) model, multi-channel communication mode, and randomized malicious channel jamming controlled by an adaptive adversary, we present an SINR-based adversarial channel jamming model to capture the unpredictable transmission failures in a wireless multi-hop network. We first propose a distributed Jamming-resilient Multi-source Static Broadcast (JMSB) algorithm based on random channel selection and message transmissions for multi-hop wireless networks under the above SINR-based adversarial channel jamming model. We then propose a distributed stable Jamming-resilient Multi-source Dynamic Broadcast (JMDB) algorithm which iterates JMSB repeatedly and efficiently in a two-stage manner. We derive the maximum supportable broadcast throughput of JMDB under the stability guarantee, i.e., the expected boundedness on the queue length of each network node and expected broadcast latency for each injected packet. Simulation results shows the stability and throughput efficiency of our proposed JMDB algorithm.
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