Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229051
Pratiksha Thaker, M. Zaharia, Tatsunori Hashimoto
When congestion control algorithms compete on shared links, unfair outcomes can result, especially between algorithms that aim to prioritize different objectives. For example, a throughput-maximizing application could make the link completely unusable for a latency-sensitive application. In order to study these outcomes formally, we model the congestion control problem as a game in which applications have heterogeneous utility functions. We draw on the comparative statics literature in economics to derive simple and practically useful conditions under which all applications achieve at least ε utility at equilibrium, a minimal safety condition for the network to be useful for any application. Compared to prior analyses of similar games, we show that our framework supports a more realistic class of utility functions that includes highly latency-sensitive applications such as teleconferencing and online gaming.
{"title":"Congestion Control Safety via Comparative Statics","authors":"Pratiksha Thaker, M. Zaharia, Tatsunori Hashimoto","doi":"10.1109/INFOCOM53939.2023.10229051","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229051","url":null,"abstract":"When congestion control algorithms compete on shared links, unfair outcomes can result, especially between algorithms that aim to prioritize different objectives. For example, a throughput-maximizing application could make the link completely unusable for a latency-sensitive application. In order to study these outcomes formally, we model the congestion control problem as a game in which applications have heterogeneous utility functions. We draw on the comparative statics literature in economics to derive simple and practically useful conditions under which all applications achieve at least ε utility at equilibrium, a minimal safety condition for the network to be useful for any application. Compared to prior analyses of similar games, we show that our framework supports a more realistic class of utility functions that includes highly latency-sensitive applications such as teleconferencing and online gaming.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228883
C. A. Caldeira, O. A. D. O. Souza, Olga Goussevskaia, Stefan Schmid
Demand-aware reconfigurable datacenter networks can be modeled as a ToR-Matching-ToR (TMT) two-layer architecture, in which each top-of-rack (ToR) is represented by a static switch, and n ToRs are connected by a set of reconfigurable optical circuit switches (OCS). Each OCS internally connects a set of in-out ports via a matching that may be updated at runtime. The matching model is a formalization of such networks, where the datacenter topology is defined by the union of matchings over the set of nodes, each of which can be reconfigured at unit cost.In this work we propose a scalable matching model for scenarios where OCS have a constant number of ports. Furthermore, we present OpticNet, a framework that maps a set of n static ToR switches to a set of p-port OCS to form any constant-degree topology. We prove that OpticNet uses a minimal number of reconfigurable switches to realize any desired network topology and allows to apply any existing self-adjusting network (SAN) algorithm on top of it, also preserving amortized performance guarantees. Our experimental results based on real workloads show that OpticNet is a flexible and efficient framework to design efficient SANs.
{"title":"OpticNet: Self-Adjusting Networks for ToR-Matching-ToR Optical Switching Architectures","authors":"C. A. Caldeira, O. A. D. O. Souza, Olga Goussevskaia, Stefan Schmid","doi":"10.1109/INFOCOM53939.2023.10228883","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228883","url":null,"abstract":"Demand-aware reconfigurable datacenter networks can be modeled as a ToR-Matching-ToR (TMT) two-layer architecture, in which each top-of-rack (ToR) is represented by a static switch, and n ToRs are connected by a set of reconfigurable optical circuit switches (OCS). Each OCS internally connects a set of in-out ports via a matching that may be updated at runtime. The matching model is a formalization of such networks, where the datacenter topology is defined by the union of matchings over the set of nodes, each of which can be reconfigured at unit cost.In this work we propose a scalable matching model for scenarios where OCS have a constant number of ports. Furthermore, we present OpticNet, a framework that maps a set of n static ToR switches to a set of p-port OCS to form any constant-degree topology. We prove that OpticNet uses a minimal number of reconfigurable switches to realize any desired network topology and allows to apply any existing self-adjusting network (SAN) algorithm on top of it, also preserving amortized performance guarantees. Our experimental results based on real workloads show that OpticNet is a flexible and efficient framework to design efficient SANs.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122057342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing develops rapidly in recent years and provides service to many applications, in which job scheduling becomes more and more important to improve the quality of service. Parallel processing on cloud requires different machines starting simultaneously on the same job and brings processing slowdown due to communications overhead, defined as synchronization constraint and parallel slowdown. This paper investigates a new job scheduling problem of makespan minimization on uniform machines and identical machines with synchronization constraint and parallel slowdown. We first conduct complexity analysis proving that the problem is difficult in the face of adversarial job allocation. Then we propose a novel job scheduling algorithm, United Wrapping Scheduling (UWS), and prove that UWS admits an O(logm)-approximation for makespan minimization over m uniform machines. For the special case of identical machines, UWS is simplified to Sequential Allocation, Refilling and Immigration algorithm (SARI), proved to have a constant approximation ratio of 8 (tight up to a factor of 4). Performance evaluation implies that UWS and SARI have better makespan and realistic approximation ratio of 2 compared to baseline methods United-LPT and FIFO, and lower bounds.
{"title":"An Approximation for Job Scheduling on Cloud with Synchronization and Slowdown Constraints","authors":"Dejun Kong, Zhongrui Zhang, Yangguang Shi, Xiaofeng Gao","doi":"10.1109/INFOCOM53939.2023.10229078","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229078","url":null,"abstract":"Cloud computing develops rapidly in recent years and provides service to many applications, in which job scheduling becomes more and more important to improve the quality of service. Parallel processing on cloud requires different machines starting simultaneously on the same job and brings processing slowdown due to communications overhead, defined as synchronization constraint and parallel slowdown. This paper investigates a new job scheduling problem of makespan minimization on uniform machines and identical machines with synchronization constraint and parallel slowdown. We first conduct complexity analysis proving that the problem is difficult in the face of adversarial job allocation. Then we propose a novel job scheduling algorithm, United Wrapping Scheduling (UWS), and prove that UWS admits an O(logm)-approximation for makespan minimization over m uniform machines. For the special case of identical machines, UWS is simplified to Sequential Allocation, Refilling and Immigration algorithm (SARI), proved to have a constant approximation ratio of 8 (tight up to a factor of 4). Performance evaluation implies that UWS and SARI have better makespan and realistic approximation ratio of 2 compared to baseline methods United-LPT and FIFO, and lower bounds.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122164160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229023
János Tapolcai, P. Babarczi, P. Ho, Lajos Rónyai
Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.
{"title":"Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences","authors":"János Tapolcai, P. Babarczi, P. Ho, Lajos Rónyai","doi":"10.1109/INFOCOM53939.2023.10229023","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229023","url":null,"abstract":"Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117034466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228992
Huayi Qi, Minghui Xu, Xiuzhen Cheng, Weifeng Lyu
Blockchain systems can become overwhelmed by a large number of transactions, leading to increased latency. As a consequence, latency-sensitive users must bid against each other and pay higher fees to ensure that their transactions are processed in priority. However, most of the time of a blockchain system (78% in Ethereum), there is still a lot of unused computational power, with few users sending transactions. To address this issue and reduce latency for users, we propose the latency-first smart contract model in this paper, which optimistically accepts committed transactions. This allows users to submit a commitment during times of high demand, and then complete the rest of the work at a lower priority. From the perspective of the blockchain, this temporarily "overclocks" the system. We have developed a programming tool for our model, and our experiments show that the proposed latency-first smart contract model can greatly reduce latency during the periods of high demand.
{"title":"Latency-First Smart Contract: Overclock the Blockchain for a while","authors":"Huayi Qi, Minghui Xu, Xiuzhen Cheng, Weifeng Lyu","doi":"10.1109/INFOCOM53939.2023.10228992","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228992","url":null,"abstract":"Blockchain systems can become overwhelmed by a large number of transactions, leading to increased latency. As a consequence, latency-sensitive users must bid against each other and pay higher fees to ensure that their transactions are processed in priority. However, most of the time of a blockchain system (78% in Ethereum), there is still a lot of unused computational power, with few users sending transactions. To address this issue and reduce latency for users, we propose the latency-first smart contract model in this paper, which optimistically accepts committed transactions. This allows users to submit a commitment during times of high demand, and then complete the rest of the work at a lower priority. From the perspective of the blockchain, this temporarily \"overclocks\" the system. We have developed a programming tool for our model, and our experiments show that the proposed latency-first smart contract model can greatly reduce latency during the periods of high demand.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128383274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229101
Lan Yang, Yangming Zhao, Liusheng Huang, C. Qiao
In Distributed Quantum Computing (DQC), quantum bits (qubits) used in a quantum circuit may be distributed on multiple Quantum Computers (QCs) connected by a Quantum Data Network (QDN). To perform a quantum gate operation involving two qubits on different QCs, we have to establish an Entanglement Connection (EC) between their host QCs. Existing EC establishment schemes result in a long EC establishment time, and low quantum resource utilization.In this paper, we propose an Asynchronous Entanglement Routing and Provisioning (AEPR) scheme to minimize the task completion time in DQC systems. AEPR has three distinct features: (i). Entanglement Paths (EPs) for a given SD pair are predetermined to eliminate the need for runtime calculation; (ii). Entanglement Links (ELs) are created proactively to reduce the time needed create EL on demand; and (iii). For a given EC request, quantum swapping along an EP is performed by a repeater whenever two adjacent ELs are created, so precious quantum resources at the repeater can be released immediately thereafter for other ELs and ECs. Extensive simulations show that AEPR can save up to 76.05% of the average task completion time in DQC systems compared with the state-of-the-art entanglement routing schemes designed to maximize QDN throughput.
{"title":"Asynchronous Entanglement Provisioning and Routing for Distributed Quantum Computing","authors":"Lan Yang, Yangming Zhao, Liusheng Huang, C. Qiao","doi":"10.1109/INFOCOM53939.2023.10229101","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229101","url":null,"abstract":"In Distributed Quantum Computing (DQC), quantum bits (qubits) used in a quantum circuit may be distributed on multiple Quantum Computers (QCs) connected by a Quantum Data Network (QDN). To perform a quantum gate operation involving two qubits on different QCs, we have to establish an Entanglement Connection (EC) between their host QCs. Existing EC establishment schemes result in a long EC establishment time, and low quantum resource utilization.In this paper, we propose an Asynchronous Entanglement Routing and Provisioning (AEPR) scheme to minimize the task completion time in DQC systems. AEPR has three distinct features: (i). Entanglement Paths (EPs) for a given SD pair are predetermined to eliminate the need for runtime calculation; (ii). Entanglement Links (ELs) are created proactively to reduce the time needed create EL on demand; and (iii). For a given EC request, quantum swapping along an EP is performed by a repeater whenever two adjacent ELs are created, so precious quantum resources at the repeater can be released immediately thereafter for other ELs and ECs. Extensive simulations show that AEPR can save up to 76.05% of the average task completion time in DQC systems compared with the state-of-the-art entanglement routing schemes designed to maximize QDN throughput.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128665140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229045
Jingzong Li, Libin Liu, Hongchang Xu, Shudeng Wu, Chun Jason Xue
The proliferation of edge devices has pushed computing from the cloud to the data sources, and video analytics is among the most promising applications of edge computing. Running video analytics is compute- and latency-sensitive, as video frames are analyzed by complex deep neural networks (DNNs) which put severe pressure on resource-constrained edge devices. To resolve the tension between inference latency and resource cost, we present Polly, a cross-camera inference system that enables co-located cameras with different but overlapping fields of views (FoVs) to share inference results between one another, thus eliminating the redundant inference work for objects in the same physical area. Polly’s design solves two basic challenges of cross-camera inference: how to identify overlapping FoVs automatically, and how to share inference results accurately across cameras. Evaluation on NVIDIA Jetson Nano with a real-world traffic surveillance dataset shows that Polly reduces the inference latency by up to 71.4% while achieving almost the same detection accuracy with state-of-the-art systems.
{"title":"Cross-Camera Inference on the Constrained Edge","authors":"Jingzong Li, Libin Liu, Hongchang Xu, Shudeng Wu, Chun Jason Xue","doi":"10.1109/INFOCOM53939.2023.10229045","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229045","url":null,"abstract":"The proliferation of edge devices has pushed computing from the cloud to the data sources, and video analytics is among the most promising applications of edge computing. Running video analytics is compute- and latency-sensitive, as video frames are analyzed by complex deep neural networks (DNNs) which put severe pressure on resource-constrained edge devices. To resolve the tension between inference latency and resource cost, we present Polly, a cross-camera inference system that enables co-located cameras with different but overlapping fields of views (FoVs) to share inference results between one another, thus eliminating the redundant inference work for objects in the same physical area. Polly’s design solves two basic challenges of cross-camera inference: how to identify overlapping FoVs automatically, and how to share inference results accurately across cameras. Evaluation on NVIDIA Jetson Nano with a real-world traffic surveillance dataset shows that Polly reduces the inference latency by up to 71.4% while achieving almost the same detection accuracy with state-of-the-art systems.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129349388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228899
Abdalaziz Sawwan, Jie Wu
Stochastic Multi-Armed Bandit (MAB) has recently been studied widely due to its vast range of applications. The classic model considers the reward of a pulled arm to be observed after a time delay that is sampled from a random distribution assigned for each arm. In this paper, we propose an extended framework in which pulling an arm gives both an instant (short-term) reward and a delayed (long-term) reward at the same time. The distributions of reward values for short-term and long-term rewards are related with a previously known relationship. The distribution of time delay for an arm is independent of the reward distributions of the arm. In our work, we devise three UCB-based algorithms, where two of them are near-optimal-regret algorithms for this new model, with the corresponding regret analysis for each one of them. Additionally, the random distributions for time delay values are allowed to yield infinite time, which corresponds to a case where the arm only gives a short-term reward. Finally, we evaluate our algorithms and compare this paradigm with previously known models on both a synthetic data set and a real data set that would reflect one of the potential applications of this model.
{"title":"A New Framework: Short-Term and Long-Term Returns in Stochastic Multi-Armed Bandit","authors":"Abdalaziz Sawwan, Jie Wu","doi":"10.1109/INFOCOM53939.2023.10228899","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228899","url":null,"abstract":"Stochastic Multi-Armed Bandit (MAB) has recently been studied widely due to its vast range of applications. The classic model considers the reward of a pulled arm to be observed after a time delay that is sampled from a random distribution assigned for each arm. In this paper, we propose an extended framework in which pulling an arm gives both an instant (short-term) reward and a delayed (long-term) reward at the same time. The distributions of reward values for short-term and long-term rewards are related with a previously known relationship. The distribution of time delay for an arm is independent of the reward distributions of the arm. In our work, we devise three UCB-based algorithms, where two of them are near-optimal-regret algorithms for this new model, with the corresponding regret analysis for each one of them. Additionally, the random distributions for time delay values are allowed to yield infinite time, which corresponds to a case where the arm only gives a short-term reward. Finally, we evaluate our algorithms and compare this paradigm with previously known models on both a synthetic data set and a real data set that would reflect one of the potential applications of this model.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123495294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10228918
Jihong Yu, Caihui Du, Jiahao Liu, Rongrong Zhang, Shuai Wang
OFDM backscatter is crucial in passive IoT. Most of the existing works adopt phase-modulated schemes to embed tag data, which suffer from three drawbacks: symbol-level modulation limitation, heavy synchronization accuracy reliance, and small symbol time offset (STO) / carrier frequency (CFO) offset tolerability. We introduce SubScatter, the first subcarrier-level frequency-modulated OFDM backscatter which is able to tolerate bigger synchronization errors, STO, and CFO. The unique feature that sets SubScatter apart from the other backscatter systems is our subcarrier shift keying (SSK) modulation. This method pushes the modulation granularity to the subcarrier by encoding and mapping tag data into different subcarrier patterns. We also design a tandem frequency shift (TFS) scheme that enables SSK with low cost and low power. For decoding, we propose a correlation-based method that decodes tag data from the correlation between the original and backscatter OFDM symbols. We prototype and test SubScatter under 802.11g OFDM WiFi signals. Comprehensive evaluations show that our SubScatter outstands prior works in terms of effectiveness and robustness. Specifically, SubScatter has 743kbps throughput, 3.1× and 14.9× higher than RapidRider and MOXcatter, respectively. It also has a much lower BER under noise and interferences, which is over 6× better than RapidRider or MOXcatter.
{"title":"SubScatter: Subcarrier-Level OFDM Backscatter","authors":"Jihong Yu, Caihui Du, Jiahao Liu, Rongrong Zhang, Shuai Wang","doi":"10.1109/INFOCOM53939.2023.10228918","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228918","url":null,"abstract":"OFDM backscatter is crucial in passive IoT. Most of the existing works adopt phase-modulated schemes to embed tag data, which suffer from three drawbacks: symbol-level modulation limitation, heavy synchronization accuracy reliance, and small symbol time offset (STO) / carrier frequency (CFO) offset tolerability. We introduce SubScatter, the first subcarrier-level frequency-modulated OFDM backscatter which is able to tolerate bigger synchronization errors, STO, and CFO. The unique feature that sets SubScatter apart from the other backscatter systems is our subcarrier shift keying (SSK) modulation. This method pushes the modulation granularity to the subcarrier by encoding and mapping tag data into different subcarrier patterns. We also design a tandem frequency shift (TFS) scheme that enables SSK with low cost and low power. For decoding, we propose a correlation-based method that decodes tag data from the correlation between the original and backscatter OFDM symbols. We prototype and test SubScatter under 802.11g OFDM WiFi signals. Comprehensive evaluations show that our SubScatter outstands prior works in terms of effectiveness and robustness. Specifically, SubScatter has 743kbps throughput, 3.1× and 14.9× higher than RapidRider and MOXcatter, respectively. It also has a much lower BER under noise and interferences, which is over 6× better than RapidRider or MOXcatter.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121266223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1109/INFOCOM53939.2023.10229060
Tao Wu, Yuben Qu, Chunsheng Liu, Yuqian Jing, Feiyu Wu, Haipeng Dai, Chaoyu Dong, Jiannong Cao
Federated learning (FL) has been proposed as a promising distributed learning paradigm to realize edge artificial intelligence (AI) without revealing the raw data. Nevertheless, it would incur inevitable costs in terms of training latency and energy consumption, due to periodical communication between user equipments (UEs) and the geographically remote central parameter server. Thus motivated, we study the joint edge aggregation and association problem to minimize the total cost, where the model aggregation over multiple cells just happens at the network edge. After proving its hardness with complex coupled variables, we transform it into a set function optimization problem and prove the objective function is neither submodular nor supermodular, which further complicates the problem. To tackle this difficulty, we first split it into multiple edge association subproblems, where the optimal solution to the computation resource allocation can be efficiently obtained in the closed form. We then construct a substitute function with the supermodularity and provable upper bound. On this basis, we reformulate an equivalent set function minimization problem under a matroid base constraint. We then propose an approximation algorithm to the original problem based on the two-stage search strategy with theoretical performance guarantee. Both extensive simulations and field experiments are conducted to validate the effectiveness of our proposed solution.
{"title":"Joint Edge Aggregation and Association for Cost-Efficient Multi-Cell Federated Learning","authors":"Tao Wu, Yuben Qu, Chunsheng Liu, Yuqian Jing, Feiyu Wu, Haipeng Dai, Chaoyu Dong, Jiannong Cao","doi":"10.1109/INFOCOM53939.2023.10229060","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229060","url":null,"abstract":"Federated learning (FL) has been proposed as a promising distributed learning paradigm to realize edge artificial intelligence (AI) without revealing the raw data. Nevertheless, it would incur inevitable costs in terms of training latency and energy consumption, due to periodical communication between user equipments (UEs) and the geographically remote central parameter server. Thus motivated, we study the joint edge aggregation and association problem to minimize the total cost, where the model aggregation over multiple cells just happens at the network edge. After proving its hardness with complex coupled variables, we transform it into a set function optimization problem and prove the objective function is neither submodular nor supermodular, which further complicates the problem. To tackle this difficulty, we first split it into multiple edge association subproblems, where the optimal solution to the computation resource allocation can be efficiently obtained in the closed form. We then construct a substitute function with the supermodularity and provable upper bound. On this basis, we reformulate an equivalent set function minimization problem under a matroid base constraint. We then propose an approximation algorithm to the original problem based on the two-stage search strategy with theoretical performance guarantee. Both extensive simulations and field experiments are conducted to validate the effectiveness of our proposed solution.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124122561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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