AUTOMATIC - ArtículosAUTOMATIC - Artículoshttp://hdl.handle.net/10017/1502024-03-28T09:13:16Z2024-03-28T09:13:16ZImpact of static urban traffic flow-based traffic weighted multi-maps routing strategies on pollutant emissionsParicio García, ÁlvaroLópez Carmona, Miguel Ángelhttp://hdl.handle.net/10017/610482024-03-13T01:17:35Z2024-03-12T00:00:00ZImpact of static urban traffic flow-based traffic weighted multi-maps routing strategies on pollutant emissions
Paricio García, Álvaro; López Carmona, Miguel Ángel
Addressing urban traffic congestion is a pressing issue requiring efficient solutions that need to be analyzed regarding travel time and pollutant emissions. The traffic weighted multi-maps (TWM) method has been proposed as an efficient mechanism for congestion mitigation that enables differential traffic routing and path diversity by strategically distributing different network views (maps) to the drivers. Previous works have focused on TWM generation by creating optimal edge weights, but the complexity exponentially increases with the network size and traffic group diversity. This work describes how congestion and emissions can be addressed using TWM maps based on the k-shortest paths for the traffic flows (instead of individuals) that are optimally assigned and distributed to the components of the traffic flow. The map allocation strategies optimal TWM (OTV), optimal TWM per path flow with linear constraints (LCTV), and its variant unconstrained optimal TWM per path flow (UCTV) are described. They use maps generated from the k-shortest paths of the traffic flows (kSP-TWM). The heuristic solution obtained is compared with the theoretical static traffic assignment estimation baseline with different configurations, regarding congestion reduction, total travel time enhancement, and pollutant emissions. Experiments are developed using a synthetic traffic grid network scenario with a mesoscopic simulation. They show that the solution provided is adequate for its proximity to the theoretical equilibrium solutions and can generate minimum emissions patterns. The presented solution opens new possibilities for further congestion and pollutant management studies and seamless integration with existing traffic management frameworks.
2024-03-12T00:00:00ZA comprehensive latency profiling study of the Tofino P4 programmable ASIC-based hardwareFranco, DavidOllora Zaballa, EderZang, MingyuanAtutxa, AsierSasiain, JorgePruski, AleksanderRojas Sánchez, ElisaHiguero, MariviJacob, Eduardohttp://hdl.handle.net/10017/608892024-02-27T01:17:28Z2024-03-15T00:00:00ZA comprehensive latency profiling study of the Tofino P4 programmable ASIC-based hardware
Franco, David; Ollora Zaballa, Eder; Zang, Mingyuan; Atutxa, Asier; Sasiain, Jorge; Pruski, Aleksander; Rojas Sánchez, Elisa; Higuero, Marivi; Jacob, Eduardo
Network softwarization has significantly evolved since programmable data planes became topical in academia and industry. Programming Protocol-Independent Packet Processors (P4) is a language to define packet forwarding behavior. Forwarding devices that are programmed with the P4 language support a flexible way to define headers, parse graphs, and data plane logic. However, extending the data plane with additional functionalities has an impact on packet data plane latency. For this reason, this paper analyzes the key factors that affect data pane latency to packets processed by the Tofino-based target (Tofino Native Architecture (TNA)), which can be considered the de facto production-ready and P4-programmable Application-Specific Integrated Circuit (ASIC). Our work first provides an extensive set of latency measurements and, afterwards, it includes a set of data plane latency predictions using the model derived from the latency results and machine learning (ML) algorithms. We demonstrate that the PCA-lasso polynomial (PLP) obtains the best results among the algorithms tested. The best-case results show that PLP obtained an accuracy of 98.22% prediction accuracy when considering the parser, deparser, and the control block for traffic running at 10 G/s (SFP+) and 100 G/s (QSFP28). To the best of our knowledge, this is the first work that provides such a comprehensive profiling, including a method to predict data plane latency in production-grade Tofino ASIC-based switching hardware, which could be leveraged to yield accurate latency values prior to investment and deployment.
2024-03-15T00:00:00ZMuHoW: distributed protocol for resource sharing in collaborative edge-computing networksÁlvarez Horcajo, JoaquínMartinez Yelmo, IsaiasRojas Sánchez, ElisaCarral Pelayo, Juan AntonioNoci Luna, Victoriahttp://hdl.handle.net/10017/608122024-03-01T17:14:09Z2024-02-10T00:00:00ZMuHoW: distributed protocol for resource sharing in collaborative edge-computing networks
Álvarez Horcajo, Joaquín; Martinez Yelmo, Isaias; Rojas Sánchez, Elisa; Carral Pelayo, Juan Antonio; Noci Luna, Victoria
The incorporation of end devices in the edge-to-cloud continuum yields substantial benefits to conventional cloud computing frameworks, expediting communication between end devices and computational resources, and resulting in new use cases, particularly in the field of mobile networks. However, few related works leverage the full potential of resource sharing at the far edge, as most proposals require that end nodes rely on a higher-capacity computational node. This manuscript presents Multi-Hop Wireless Resource Sharing Protocol (MuHoW), a lightweight protocol tailored for multi-hop wireless networks. MuHoW enables resource sharing within collaborative edge-computing networks by facilitating the discovery of wireless neighbours and subsequently establishing a confluence tree directed towards the edge/fog infrastructure. This tree serves as a conduit for aggregating essential resource sharing information, ensuring the establishment of a seamless collaborative edge/fog environment. The empirical findings highlight the scalability of MuHoW, due to its linear control message growth with network size. Moreover, the efficiency of the protocol is very high even in lossy environments as evidenced by the fact that most resource sharing messages are successfully delivered as expected.
2024-02-10T00:00:00ZUrban traffic routing using weighted multi-map strategiesParicio García, ÁlvaroLópez Carmona, Miguel Ángelhttp://hdl.handle.net/10017/605952024-02-09T01:16:50Z2019-10-31T00:00:00ZUrban traffic routing using weighted multi-map strategies
Paricio García, Álvaro; López Carmona, Miguel Ángel
Urban traffic routing has to deal with individual mobility and collective wellness considering citizens, multi-modal transport, and fleet traffic with conflicting interests such as electric vehicles, local distribution, public transport, and private vehicles. Different interests, goals, and regulations, suggest the development of new multi-objective routing mechanisms which may improve traffic flow. In this work, Traffic Weighted Multi-Maps (TWM) is presented as a novel traffic routing mechanism based on the strategical generation and distribution of complementary cost maps for traffic fleets, oriented towards the application of differentiated traffic planning and control policies. TWM is built upon a centralized control architecture, where a Traffic Management Center generates and distributes customized cost maps of the road network. These maps are used individually to calculate routes. In this research, we present the TWM theoretical model and experimental results based on microscopic simulations over a real city traffic network under multiple scenarios, including traffic incidents management. Experimental evaluation takes into account driver?s adherence to the system and considers a multi-objective analysis both for the global network parameters (congestion, travel time, and route length) and for the subjective driving experience. Experimental results deliver performance improvements from 20% to 50%. TWM is fully compatible with existing traffic routing systems and has promising future evolution applying new algorithms, policies and network profiles.
2019-10-31T00:00:00Z