More Like this

1. DeResolver: A Decentralized Conflict Resolution Framework with Autonomous Negotiation for Smart City Services

   https://doi.org/10.1145/3529096  

   Yuan, Yukun ; Ma, Meiyi ; Han, Songyang ; Zhang, Desheng ; Miao, Fei ; Stankovic, John A. ; Lin, Shan ( October 2022 , ACM Transactions on Cyber-Physical Systems)

   As various smart services are increasingly deployed in modern cities, many unexpected conflicts arise due to various physical world couplings. Existing solutions for conflict resolution often rely on centralized control to enforce predetermined and fixed priorities of different services, which is challenging due to the inconsistent and private objectives of the services. Also, the centralized solutions miss opportunities to more effectively resolve conflicts according to their spatiotemporal locality of the conflicts. To address this issue, we design a decentralized negotiation and conflict resolution framework named DeResolver, which allows services to resolve conflicts by communicating and negotiating with each other to reach a Pareto-optimal agreement autonomously and efficiently. Our design features a two-step self-supervised learning-based algorithm to predict acceptable proposals and their rankings of each opponent through the negotiation. Our design is evaluated with a smart city case study of three services: intelligent traffic light control, pedestrian service, and environmental control. In this case study, a data-driven evaluation is conducted using a large dataset consisting of the GPS locations of 246 surveillance cameras and an automatic traffic monitoring system with more than 3 million records per day to extract real-world vehicle routes. The evaluation results show that our solution achieves much more balanced results, i.e., only increasing the average waiting time of vehicles, the measurement metric of intelligent traffic light control service, by 6.8% while reducing the weighted sum of air pollutant emission, measured for environment control service, by 12.1%, and the pedestrian waiting time, the measurement metric of pedestrian service, by 33.1%, compared to priority-based solution. 

   more » « less
2. Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks

   https://doi.org/1801.01108v2  

   Tingjun Chen, Jelena Diakonikolas ( January 2018 , ArXiv.org)

   Full-duplex (FD) wireless is an attractive communication paradigm with high potential for improving network capacity and reducing delay in wireless networks. Despite significant progress on the physical layer development, the challenges associated with developing medium access control (MAC) protocols for heterogeneous networks composed of both legacy half-duplex (HD) and emerging FD devices have not been fully addressed. Therefore, we focus on the design and performance evaluation of scheduling algorithms for infrastructure-based heterogeneous HD-FD networks (composed of HD and FD users). We first show that centralized GreedyMaximal Scheduling (GMS) is throughput-optimal in heterogeneous HD-FD networks. We propose the Hybrid-GMS (H-GMS) algorithm, a distributed implementation of GMS that combines GMS and a queue-based random-access mechanism. We prove that H-GMS is throughputoptimal. Moreover, we analyze the delay performance of H-GMS by deriving lower bounds on the average queue length. We further demonstrate the benefits of upgrading HD nodes to FD nodes in terms of throughput gains for individual nodes and the whole network. Finally, we evaluate the performance of HGMS and its variants in terms of throughput, delay, and fairness between FD and HD users via extensive simulations. We show that in heterogeneous HD-FD networks, H-GMS achieves 16–30× better delay performance and improves fairness between HD and FD users by up to 50% compared with the fully decentralized Q-CSMA algorithm. 

   more » « less
3. Hybrid scheduling in heterogeneous half- and full-duplex wireless networks

   Chen, T. ; Diakonikolas, J. ; Ghaderi, J. ; Zussman, G. ( January 2020 , IEEE/ACM Transactions on Networking)

   Abstract—Full-duplex (FD) wireless is an attractive communication paradigm with high potential for improving network capacity and reducing delay in wireless networks. Despite significant progress on the physical layer development, the challenges associated with developing medium access control (MAC) protocols for heterogeneous networks composed of both legacy half-duplex (HD) and emerging FD devices have not been fully addressed. Therefore, we focus on the design and performance evaluation of scheduling algorithms for infrastructure-based heterogeneous HD-FD networks (composed of HD and FD users). We first show that centralized Greedy Maximal Scheduling (GMS) is throughput-optimal in heterogeneous HD-FD networks. We propose the Hybrid-GMS (H-GMS) algorithm, a distributed implementation of GMS that combines GMS and a queue-based random-access mechanism. We prove that H-GMS is throughputoptimal. Moreover, we analyze the delay performance of H-GMS by deriving lower bounds on the average queue length. We further demonstrate the benefits of upgrading HD nodes to FD nodes in terms of throughput gains for individual nodes and the whole network. Finally, we evaluate the performance of HGMS and its variants in terms of throughput, delay, and fairness between FD and HD users via extensive simulations. We show that in heterogeneous HD-FD networks, H-GMS achieves 16–30× better delay performance and improves fairness between HD and FD users by up to 50% compared with the fully decentralized Q-CSMA algorithm. 

   more » « less
4. Fairness and Delay in Heterogeneous Half- and Full-Duplex Wireless Networks

   https://doi.org/10.1109/ACSSC.2018.8645117  

   Chen, Tingjun ; Diakonikolas, Jelena ; Ghaderi, Javad ; Zussman, Gil ( October 2018 , Conference record - Asilomar Conference on Signals, Systems, & Computers)

   Full-duplex (FD) wireless is an attractive communication paradigm with high potential for improving network capacity and reducing delay in wireless networks. Despite significant progress on the physical layer development, the challenges associated with developing medium access control (MAC) protocols for heterogeneous networks composed of both legacy half-duplex (HD) and emerging FD devices have not been fully addressed. In [1], we focused on the design and performance evaluation of scheduling algorithms for heterogeneous HD-FD networks and presented the distributed Hybrid-Greedy Maximal Scheduling (H-GMS) algorithm. H-GMS combines the centralized Greedy Maximal Scheduling (GMS) and a distributed queue-based random-access mechanism, and is throughput-optimal. In this paper, we analyze the delay performance of H-GMS by deriving two lower bounds on the average queue length. We also evaluate the fairness and delay performance of H-GMS via extensive simulations. We show that in heterogeneous HD-FD networks, H-GMS achieves$16-30\times$ better delay performance and improves fairness between FD and HD users by up to 50% compared with the fully decentralized Q-CSMA algorithm. 

   more » « less
5. Age-based Scheduling: Improving Data Freshness for Wireless Real-Time Traffic

   https://doi.org/10.1145/3209582.3209602  

   Lu, Ning ; Ji, Bo ; Li, Bin ( June 2018 , Mobihoc '18 Proceedings of the Eighteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing)

   We consider the problem of scheduling real-time traffic with hard deadlines in a wireless ad hoc network. In contrast to existing real-time scheduling policies that merely ensure a minimal timely throughput, our design goal is to provide guarantees on both the timely throughput and data freshness in terms of age-of-information (AoI), which is a newly proposed metric that captures the "age" of the most recently received information at the destination of a link. The main idea is to introduce the AoI as one of the driving factors in making scheduling decisions. We first prove that the proposed scheduling policy is feasibility-optimal, i.e., satisfying the per-traffic timely throughput requirement. Then, we derive an upper bound on a considered data freshness metric in terms of AoI, demonstrating that the network-wide data freshness is guaranteed and can be tuned under the proposed scheduling policy. Interestingly, we reveal that the improvement of network data freshness is at the cost of slowing down the convergence of the timely throughput. Extensive simulations are performed to validate our analytical results. Both analytical and simulation results confirm the capability of the proposed scheduling policy to improve the data freshness without sacrificing the feasibility optimality. 

   more » « less