IEEE INFOCOM 2023

Program at a Glance

IEEE INFOCOM 2023

Session Break-1-Day2: Coffee Break Session Lunch-Day2: Conference Lunch Session Break-2-Day2: Coffee Break Session Dinner-Day2: Conference Dinner

Session A-4: Blockchain Session A-6: Quantum Computing/Networking

Session B-4: Federated Learning 4 Session B-6: Federated Learning 5

Session C-4: UAV Session C-5: Optical and Mobile Session C-6: Programmable Switches

Session D-4: Fingerprinting and Classification Session D-5: Internet Measurement/Monitoring Session D-6: Age of Information

Session E-4: Optimization Session E-5: Wireless/Mobile Security 1 Session E-6: Wireless/Mobile Security 2

Session F-4: Activity Sensing

Session G-4: Traffic Shaping and Inspection

Session Demo-2: Demo Session 2

Session Panel: Panel - Networking: An Agenda for the Next Decade

Session Award: A Reflection with INFOCOM Achievement Award Winner

Session Poster-1: Poster Session 1

MERCURY: Fast Transaction Broadcast in High Performance Blockchain Systems

Mingxun Zhou (Carnegie Mellon University, USA); Yilin Han (Shanghai Tree-Graph Blockchain Research Institute, China); Liyi Zeng (Tsinghua University, China); Peilun Li (Shanghai Tree-Graph Blockchain Research Institute, China); Fan Long (University of Toronto, Canada); Dong Zhou (IMO Ventures, China); Ivan Beschastnikh (University of British Columbia, Canada); Ming Wu (Shanghai Tree-Graph Blockchain Research Institute, China)

Blockchain systems must be secure and offer high performance. A key mechanism that these systems rely on to provide both of these features is transaction broadcast. Unfortunately, in today's systems, the broadcast protocols are highly inefficient. The wide adoption of public blockchain systems increases the importance of high performance blockchain infrastructure that offers both high throughput and low transaction confirmation latency. Underlying such infrastructures is a fast, efficient, and robust transaction broadcast mechanism.

We present Mercury, a new transaction broadcast protocol designed for high performance blockchains. Mercury shortens the transaction propagation delay using two techniques: a virtual coordinate system (VCS) and an early outburst strategy. Our simulation results show that Mercury outperforms prior propagation schemes and decreases overall propagation latency by up to 44%. When implemented in Conflux, an open-source high-throughput blockchain system, Mercury reduces transaction propagation latency by over 50% with a bandwidth overhead of less than 5%.

Speaker Liyi Zeng (Tsinghua University)

Liyi Zeng is a PhD candidate from IIIS, Tsinghua University, advised by Prof. Wei Xu. Her research areas include Blockchain System, Data Mining and Network Security.

PROPHET: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering

Zicong Hong (The Hong Kong Polytechnic University, China); Song Guo and Enyuan Zhou (The Hong Kong Polytechnic University, Hong Kong); Jianting Zhang (Purdue University, USA); Chen Wuhui (Sun Yat-sen University, China); Jinwen Liang and Jie Zhang (The Hong Kong Polytechnic University, Hong Kong); Albert Zomaya (The University of Sydney, Australia)

Sharding scales throughput by splitting blockchain nodes into parallel groups. However, the independent and random scheduling for cross-shard transactions among different shards results in numerous conflicts and aborts, since cross-shard transactions from different shards may access the same account. Deterministic ordering can eliminate conflicts by predetermining a global order for transactions before processing, as proved in the database. However, due to the intertwining of the Byzantine environment and shard isolation, there is no trusted party able to predetermine such an order for cross-shard transactions. Therefore, this paper proposes Prophet, a conflict-free sharding blockchain with a new idea of Byzantine deterministic ordering. It first depends on untrusted self-organizing coalitions of nodes from different shards to pre-execute cross-shard transactions for prerequisite information about ordering. Then, it proposes a trusted global order for transactions by performing a stateless ordering in one of the shards and post-verifying pre-executed results through shard cooperation. Based on the order, the shards thus orderly commit the transactions without conflicts. We rigorously prove the determinism and serializability of transactions under the Byzantine and sharded environment. An evaluation shows that Prophet improves the throughput by 3.11X and achieves nearly no aborts on 1 million Ethereum transactions compared with state-of-the-art sharding.

Speaker Zicong Hong (The Hong Kong Polytechnic University)

Zicong Hong is pursuing his Ph.D. degree in the Department of Computing at Hong Kong Polytechnic University, Hong Kong SAR, China. Before that, in 2020, he received B.E. degree in software engineering from Sun Yat-sen University, Guangzhou, China. Now, he is a visiting student of Distributed Computing Group at ETH Zurich, Switzerland. His research interest broadly lies in the areas of blockchain, edge computing and incentive mechanism.

A Decentralized Truth Discovery Approach to the Blockchain Oracle Problem

Yang Xiao (University of Kentucky, USA); Ning Zhang (Washington University in St. Louis, USA); Wenjing Lou and Thomas Hou (Virginia Tech, USA)

Blockchain applications enable distrustful parties to execute business logic without relying on a trusted intermediary. When a blockchain application runs on data from the real world, it relies on an oracle mechanism that transports data from external sources to the blockchain. The blockchain oracle problem arises around the need to procure trustworthy data from external sources without introducing a central point of trust. The truthful data challenge, which emerges when legitimate external sources submit fraudulent or deceitful data, remains unsolved. In this paper, we introduce a new decentralized truth discovering oracle architecture called DecenTruth to address the truthful data challenge using a data-centric approach. DecenTruth aims to enable decentralized oracle nodes to discover and reach consensus on truthful values of common data objects from multi-sourced inputs in an off-chain manner. It harmonizes techniques in both the data plane and consensus plane---truth discovery (TD) and asynchronous BFT consensus---and enables nodes to finalize the same estimated truths on data objects with high accuracy, amid the harsh asynchronous network condition and presence of Byzantine sources and nodes. We implemented DecenTruth and the evaluation results demonstrate DecenTruth's significantly higher Byzantine resilience and long-term data feed accuracy compared to existing median-based aggregation methods.

Speaker Yang Xiao (University of Kentucky)

Yang Xiao is an Assistant Professor of Computer Science at the University of Kentucky. His research interests lie in network security, distributed systems, blockchain and decentralized systems, and mobile network security. He received his Ph.D. degree from Virginia Tech in 2022.

CoChain: High Concurrency Blockchain Sharding via Consensus on Consensus

Mingzhe Li (Hong Kong University of Science and Technology, Hong Kong); You Lin (Southern University of Science and Technology, China); Jin Zhang (Southern University of Science and Technology, USA); Wei Wang (Hong Kong University of Science and Technology, Hong Kong)

Sharding is an effective technique to improve the scalability of blockchain. It splits nodes into multiple groups so that they can process transactions in parallel. To achieve higher parallelism and concurrency at large scales, it is desirable to maintain a large number of small shards. However, simply configuring small shards easily results in a higher fraction of malicious nodes inside shards, causing shard corruption and compromising system security. Existing sharding techniques hence demand large shards, at the expense of limited concurrency. To address this limitation, we propose CoChain: a blockchain sharding system that can securely configure small shards for enhanced concurrency. CoChain allows some shards to be corrupted. For security, each shard is monitored by multiple other shards. The latter reach a cross-shard Consensus on the Consensus results of their monitored shard. Once a corrupted shard is found, its subsequent consensus will be taken over by another shard, hence recovering the system. Via Consensus on Consensus, CoChain allows the existence of shards with more fraction of malicious nodes (<2/3) while securing the system, thus reducing the shard size safely. We implement CoChain based on Harmony and conduct extensive experiments. Compared with Harmony, CoChain achieves 35x throughput gain with 6,000+ nodes.

Speaker **Mingzhe LI (A*STAR)**

Mingzhe Li is currently a Scientist with the Institute of High Performance Computing (IHPC), A*STAR, Singapore, and a Champion of its blockchain group. He received his Ph.D. degree from the Department of Computer Science and Engineering, Hong Kong University of Science and Technology in 2022. Prior to that, he received his B.E. degree from Southern University of Science and Technology. His interests are mainly in scalable and secure blockchain protocols, Web 3.0, privacy-preserving blockchain, network economics, etc.

Session Chair

Ruidong Li

On the Capacity Region of a Quantum Switch with Entanglement Purification

Nitish K. Panigrahy (Yale University, USA); Thirupathaiah Vasantam (Durham University, United Kingdom (Great Britain)); Don Towsley (University of Massachusetts at Amherst, USA); Leandros Tassiulas (Yale University, USA)

Quantum switches are envisioned to be an integral component of future quantum networks. They can provide high quality entanglement distribution service to end-users by performing quantum operations such as entanglement swapping and entanglement purification. In this work, we characterize the capacity region of such a quantum switch under noisy channel transmissions and imperfect quantum operations. These regions describe the set of achievable end-to-end entanglement request rates that the switch can support with finite request backlogs under any entanglement scheduling policy. We express the capacity region as a function of the channel and network parameters, entanglement purification yield and application level parameters. In particular, we provide necessary conditions to verify if a set of request rates belong to the capacity region of the switch. We use these conditions to find the maximum achievable end-to-end user entanglement generation throughput by solving a set of linear optimization problems. We also develop a max-weight scheduling policy and prove that the policy stabilizes the switch for all feasible request arrival rates. From numerical experiments, we discover that performing link-level purification followed by entanglement swaps provides a larger capacity region than doing entanglement swaps followed by purification.

Speaker Nitish Kumar Panigrahy (University of Massachusetts Amherst)

Dr. Nitish Kumar Panigrahy is currently a postdoctoral researcher at NSF ERC Center for Quantum Networks, working jointly with Prof. Leandros Tassiulas (Yale University) and Prof. Don Towsley (University of Massachusetts Amherst). He earned his PhD degree in Computer Science at University of Massachusetts Amherst in 2021. Nitish’s research interests lie in modeling, optimization, and performance evaluation of networked systems with applications to Internet of Things (IoT), cloud computing, content delivery, and quantum information networking.

Qubit Allocation for Distributed Quantum Computing

Yingling Mao, Yu Liu and Yuanyuan Yang (Stony Brook University, USA)

With the advancements in quantum communication, optically connected quantum processors can form a distributed quantum computing system. Distributed quantum computing provides a scalable path to execute more complicated computational tasks that a single quantum processor cannot handle. Yet, distributed quantum computing needs a new compiler to map logical qubits of a quantum circuit to different quantum processors in the system. This paper formulates and studies the qubit allocation problem for distributed quantum computing (QA-DQC). We prove the NP-hardness of the formulated problem. Moreover, we show there is no polynomial-time n^a-approximation algorithm for any a<1 unless P=NP, where n is the number of processors in the quantum network. We first propose a heuristic local search algorithm for QA-DQC. Furthermore, we design a multistage hybrid simulated annealing algorithm (MHSA) by combining the local search algorithm and a simulated annealing meta-heuristic algorithm. Lastly, we perform extensive simulations to evaluate the proposed MHSA algorithm under various real quantum circuits and different network topologies. Results show that MHSA outperforms popular baselines.

Speaker Yingling Mao (Stony Brook University)

Yingling Mao received her B.S. degree in Mathematics and Applied Mathematics in Zhiyuan College from Shanghai Jiao Tong University, Shanghai, China, in 2018. She is currently working toward the Ph.D degree in the Department of Electrical and Computer Engineering, Stony Brook University. Her research interests include network function virtualization, edge computing, cloud computing and quantum networks.

A Quantum Overlay Network for Efficient Entanglement Distribution

Shahrooz Pouryousef (University of Massachusetts Amherst MA, USA); Nitish K. Panigrahy (Yale University, USA); Don Towsley (University of Massachusetts at Amherst, USA)

Distributing quantum entanglements over long distances is essential for the realization of a global scale quantum Internet. Most of the prior work and proposals assume an on-demand distribution of entanglements which may result in significant network resource under-utilization. In this work, we introduce Quantum Overlay Networks (QONs) for efficient entanglement distribution in quantum networks. When the demand to create end-to-end user entanglements is low, QONs can generate and store maximally entangled Bell pairs (EPR pairs) at specific overlay storage nodes of the network. Later, during peak demands, requests can be served by performing entanglement swaps either over a direct path from the network or over a path using the storage nodes. We solve the link entanglement and storage resource allocation problem in such a QON using a centralized optimization framework. We evaluate the performance of our proposed QON architecture over a wide number of network topologies under various settings using extensive simulation experiments. Our results demonstrate that QONs fare well by a factor of 40% with respect to meeting surge and changing demands compared to traditional non-overlay proposals. QONs also show significant improvement in terms of average entanglement request service delay over non-overlay approaches.

Speaker Shahrooz Pouryousef (UMass Amherst)

Shahrooz is a PhD student in the College of Information and Computer Sciences (CICS) at UMass Amherst working with Prof. Don Towsley. His research interests lie in classical and quantum networks.

Asynchronous Entanglement Provisioning and Routing for Distributed Quantum Computing

Lan Yang, Yangming Zhao and Liusheng Huang (University of Science and Technology of China, China); Chunming Qiao (University at Buffalo, USA)

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 established proactively to reduce the time needed to successfully create ELs; 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.

Speaker Lan Yang (University of Science and Technology of China)

Lan Yang is a Master student in the department of Computer Science and Technology, University of Science and Technology of China. She received the bachelor’s degree in University of Science and Technology of China in 2022. Her research interests include network optimization, traffic engineering, and quantum networks. Currently, she is primarily working with Prof. Yangming Zhao on routing protocol design in quantum networks.

Session Chair

Jianqing Liu

Program at a Glance