Pub Date : 2024-05-27DOI: 10.1109/tnet.2024.3403671
Jinbin Hu, Yi He, Wangqing Luo, Jiawei Huang, Jin Wang
{"title":"Enhancing Load Balancing With In-Network Recirculation to Prevent Packet Reordering in Lossless Data Centers","authors":"Jinbin Hu, Yi He, Wangqing Luo, Jiawei Huang, Jin Wang","doi":"10.1109/tnet.2024.3403671","DOIUrl":"https://doi.org/10.1109/tnet.2024.3403671","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141166240","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}
{"title":"HS-DCell: A Highly Scalable DCell-Based Server-Centric Topology for Data Center Networks","authors":"Guijuan Wang, Yazhi Zhang, Jiguo Yu, Meijie Ma, Chunqiang Hu, Jianxi Fan, Li Zhang","doi":"10.1109/tnet.2024.3398628","DOIUrl":"https://doi.org/10.1109/tnet.2024.3398628","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141147893","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 : 2024-05-20DOI: 10.1109/tnet.2024.3397309
Chengxin Li, Zhetao Li, Saiqin Long, Pengpeng Qiao, Ye Yuan, Guoren Wang
{"title":"Robust Data Inference and Cost-Effective Cell Selection for Sparse Mobile Crowdsensing","authors":"Chengxin Li, Zhetao Li, Saiqin Long, Pengpeng Qiao, Ye Yuan, Guoren Wang","doi":"10.1109/tnet.2024.3397309","DOIUrl":"https://doi.org/10.1109/tnet.2024.3397309","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141147918","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 : 2024-05-17DOI: 10.1109/tnet.2024.3397613
Shuyang Li, Qiang Wu, Ran Wang
{"title":"Dynamic Discrete Topology Design and Routing for Satellite-Terrestrial Integrated Networks","authors":"Shuyang Li, Qiang Wu, Ran Wang","doi":"10.1109/tnet.2024.3397613","DOIUrl":"https://doi.org/10.1109/tnet.2024.3397613","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058850","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 : 2024-05-15DOI: 10.1109/tnet.2024.3398814
Boya Liu, Chaojie Gu, Shibo He, Jiming Chen
{"title":"LoPhy: A Resilient and Fast Covert Channel Over LoRa PHY","authors":"Boya Liu, Chaojie Gu, Shibo He, Jiming Chen","doi":"10.1109/tnet.2024.3398814","DOIUrl":"https://doi.org/10.1109/tnet.2024.3398814","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058829","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 : 2024-05-14DOI: 10.1109/tnet.2024.3399212
Wei Chen, Ye Tian, Xin Yu, Bowen Zheng, Xinming Zhang
{"title":"Enhancing Fairness for Approximate Weighted Fair Queueing With a Single Queue","authors":"Wei Chen, Ye Tian, Xin Yu, Bowen Zheng, Xinming Zhang","doi":"10.1109/tnet.2024.3399212","DOIUrl":"https://doi.org/10.1109/tnet.2024.3399212","url":null,"abstract":"","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058770","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 : 2024-04-29DOI: 10.1109/TNET.2024.3392960
Yun-Hsin Chiang;Yi-Jheng Lin;Cheng-Shang Chang;Y.-W. Peter Hong
Due to its simplicity and scalability, the Irregular Repetition Slotted ALOHA (IRSA) system that uses the successive interference cancellation (SIC) technique is a promising solution for uncoordinated multiple access of a massive number of Internet-of-Things (IoT) devices. In this paper, we propose two parallel decoding algorithms for IRSA in an additive white Gaussian noise channel. Our first algorithm is limited to SIC-decoupling matrices that correspond to the SIC decoding process in IRSA. For this, we propose a message-passing algorithm to find the optimal SIC-decoupling matrix that can minimize the accumulated noise power when the induced user-slot bipartite graph of an IRSA system is acyclic. This includes the Contention Resolution Diversity Slotted ALOHA (CRDSA) system that sends exactly two copies for each packet as a special case. Our second algorithm extends the first one by finding the optimal decoupling matrix for CRDSA through an optimal combination of two SIC-decoupling matrices. Using a random graph analysis, we derive the throughput for the two parallel decoding algorithms of CRDSA in a threshold-based decoding model. We then conduct various numerical experiments to illustrate the tradeoffs between sequential decoding with a limited number of iterations and parallel decoding with a predefined signal-to-noise ratio (SNR) threshold. Finally, we demonstrate how to extend our parallel decoding scheme to bipartite graphs with cycles.
由于其简单性和可扩展性，使用连续干扰消除（SIC）技术的不规则重复开槽 ALOHA（IRSA）系统是大量物联网（IoT）设备非协调多路接入的一种有前途的解决方案。本文针对加性白高斯噪声信道中的 IRSA 提出了两种并行解码算法。我们的第一种算法仅限于与 IRSA 中 SIC 解码过程相对应的 SIC 解耦矩阵。为此，我们提出了一种消息传递算法，用于寻找最优 SIC 解耦矩阵，当 IRSA 系统的诱导用户时隙双方图为非循环图时，该矩阵可使累积噪声功率最小。这包括竞争解决分集槽式 ALOHA（CRDSA）系统，该系统作为一种特例，每个数据包正好发送两份拷贝。我们的第二种算法扩展了第一种算法，通过两个 SIC 解耦矩阵的优化组合，找到了 CRDSA 的最佳解耦矩阵。通过随机图分析，我们得出了基于阈值的解码模型中 CRDSA 两种并行解码算法的吞吐量。然后，我们进行了各种数值实验，以说明有限迭代次数的顺序解码与预定义信噪比 (SNR) 门限的并行解码之间的权衡。最后，我们演示了如何将并行解码方案扩展到具有循环的双方图。
{"title":"Throughput Analysis for Parallel Decoding of Irregular Repetition Slotted ALOHA With Noise","authors":"Yun-Hsin Chiang;Yi-Jheng Lin;Cheng-Shang Chang;Y.-W. Peter Hong","doi":"10.1109/TNET.2024.3392960","DOIUrl":"10.1109/TNET.2024.3392960","url":null,"abstract":"Due to its simplicity and scalability, the Irregular Repetition Slotted ALOHA (IRSA) system that uses the successive interference cancellation (SIC) technique is a promising solution for uncoordinated multiple access of a massive number of Internet-of-Things (IoT) devices. In this paper, we propose two parallel decoding algorithms for IRSA in an additive white Gaussian noise channel. Our first algorithm is limited to SIC-decoupling matrices that correspond to the SIC decoding process in IRSA. For this, we propose a message-passing algorithm to find the optimal SIC-decoupling matrix that can minimize the accumulated noise power when the induced user-slot bipartite graph of an IRSA system is acyclic. This includes the Contention Resolution Diversity Slotted ALOHA (CRDSA) system that sends exactly two copies for each packet as a special case. Our second algorithm extends the first one by finding the optimal decoupling matrix for CRDSA through an optimal combination of two SIC-decoupling matrices. Using a random graph analysis, we derive the throughput for the two parallel decoding algorithms of CRDSA in a threshold-based decoding model. We then conduct various numerical experiments to illustrate the tradeoffs between sequential decoding with a limited number of iterations and parallel decoding with a predefined signal-to-noise ratio (SNR) threshold. Finally, we demonstrate how to extend our parallel decoding scheme to bipartite graphs with cycles.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833614","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}
Consistent hashing is used in distributed systems and networking applications to spread data evenly and efficiently across a cluster of nodes. In this paper, we present MementoHash, a novel consistent hashing algorithm that eliminates known limitations of state-of-the-art algorithms while keeping optimal performance and minimal memory usage. We describe the algorithm in detail, provide a pseudo-code implementation, and formally establish its solid theoretical guarantees. To measure the efficacy of MementoHash, we compare its performance, in terms of memory usage and lookup time, to that of state-of-the-art algorithms, namely, AnchorHash, DxHash, and JumpHash. Unlike JumpHash, MementoHash can handle random failures. Moreover, MementoHash does not require fixing the overall capacity of the cluster (as AnchorHash and DxHash do), allowing it to scale indefinitely. The number of removed nodes affects the performance of all the considered algorithms. Therefore, we conduct experiments considering three different scenarios: stable (no removed nodes), one-shot removals (90% of the nodes removed at once), and incremental removals. We report experimental results that averaged a varying number of nodes from ten to one million. Results indicate that our algorithm shows optimal lookup performance and minimal memory usage in its best-case scenario. It behaves better than AnchorHash and DxHash in its average-case scenario and at least as well as those two algorithms in its worst-case scenario.
{"title":"MementoHash: A Stateful, Minimal Memory, Best Performing Consistent Hash Algorithm","authors":"Massimo Coluzzi;Amos Brocco;Alessandro Antonucci;Tiziano Leidi","doi":"10.1109/TNET.2024.3393476","DOIUrl":"10.1109/TNET.2024.3393476","url":null,"abstract":"Consistent hashing is used in distributed systems and networking applications to spread data evenly and efficiently across a cluster of nodes. In this paper, we present MementoHash, a novel consistent hashing algorithm that eliminates known limitations of state-of-the-art algorithms while keeping optimal performance and minimal memory usage. We describe the algorithm in detail, provide a pseudo-code implementation, and formally establish its solid theoretical guarantees. To measure the efficacy of MementoHash, we compare its performance, in terms of memory usage and lookup time, to that of state-of-the-art algorithms, namely, AnchorHash, DxHash, and JumpHash. Unlike JumpHash, MementoHash can handle random failures. Moreover, MementoHash does not require fixing the overall capacity of the cluster (as AnchorHash and DxHash do), allowing it to scale indefinitely. The number of removed nodes affects the performance of all the considered algorithms. Therefore, we conduct experiments considering three different scenarios: stable (no removed nodes), one-shot removals (90% of the nodes removed at once), and incremental removals. We report experimental results that averaged a varying number of nodes from ten to one million. Results indicate that our algorithm shows optimal lookup performance and minimal memory usage in its best-case scenario. It behaves better than AnchorHash and DxHash in its average-case scenario and at least as well as those two algorithms in its worst-case scenario.","PeriodicalId":13443,"journal":{"name":"IEEE/ACM Transactions on Networking","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833172","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}
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