Abstract:The fifth generation (5G) wireless network technology is to be standardized by 2020, where main goals are to improve capacity, reliability, and energy efficiency, while reducing latency and massively increasing connection density. An integral part of 5G is the capability to transmit touch perception type real-time communication empowered by applicable robotics and haptics equipment at the network edge. In this regard, we need drastic changes in network architecture including core and radio access network (RAN)… Show more
“…Despite the presented latency degradations with respect to SPR, the solution performances observed in Figure 9a,c are suitable for supporting latency critical services in 5G networks demanding end-to-end delays lower than 10 ms [40], such as robotics and telepresence, virtual reality, health care, among others. Likewise, less demanding applications and use case scenarios to be addressed in 5G networks, such as intelligent transport systems and smart grid, with latency requirements up to 100 ms [40], could be conceived of and deployed in Geant-like environments.…”
Section: Traffic Latencymentioning
confidence: 99%
“…Likewise, less demanding applications and use case scenarios to be addressed in 5G networks, such as intelligent transport systems and smart grid, with latency requirements up to 100 ms [40], could be conceived of and deployed in Geant-like environments.…”
Abstract:The increasing power consumption and related environmental implications currently generated by large data networks have become a major concern over the last decade. Given the drastic traffic increase expected in 5G dense environments, the energy consumption problem becomes even more concerning and challenging. In this context, Software-Defined Networks (SDN), a key technology enabler for 5G systems, can be seen as an attractive solution. In these programmable networks, an energy-aware solution could be easily implemented leveraging the capabilities provided by control and data plane separation. This paper investigates the impact of energy-aware routing on network performance. To that end, we propose a novel energy-aware mechanism that reduces the number of active links in SDN with multiple controllers, considering in-band control traffic. The proposed strategy exploits knowledge of the network topology combined with traffic engineering techniques to reduce the overall power consumption. Therefore, two heuristic algorithms are designed: a static network configuration and a dynamic energy-aware routing. Significant values of switched-off links are reached in the simulations where real topologies and demands data are used. Moreover, the obtained results confirm that crucial network parameters such as control traffic delay, data path latency, link utilization and Ternary Content Addressable Memory (TCAM) occupation are affected by the performance-agnostic energy-aware model.
“…Despite the presented latency degradations with respect to SPR, the solution performances observed in Figure 9a,c are suitable for supporting latency critical services in 5G networks demanding end-to-end delays lower than 10 ms [40], such as robotics and telepresence, virtual reality, health care, among others. Likewise, less demanding applications and use case scenarios to be addressed in 5G networks, such as intelligent transport systems and smart grid, with latency requirements up to 100 ms [40], could be conceived of and deployed in Geant-like environments.…”
Section: Traffic Latencymentioning
confidence: 99%
“…Likewise, less demanding applications and use case scenarios to be addressed in 5G networks, such as intelligent transport systems and smart grid, with latency requirements up to 100 ms [40], could be conceived of and deployed in Geant-like environments.…”
Abstract:The increasing power consumption and related environmental implications currently generated by large data networks have become a major concern over the last decade. Given the drastic traffic increase expected in 5G dense environments, the energy consumption problem becomes even more concerning and challenging. In this context, Software-Defined Networks (SDN), a key technology enabler for 5G systems, can be seen as an attractive solution. In these programmable networks, an energy-aware solution could be easily implemented leveraging the capabilities provided by control and data plane separation. This paper investigates the impact of energy-aware routing on network performance. To that end, we propose a novel energy-aware mechanism that reduces the number of active links in SDN with multiple controllers, considering in-band control traffic. The proposed strategy exploits knowledge of the network topology combined with traffic engineering techniques to reduce the overall power consumption. Therefore, two heuristic algorithms are designed: a static network configuration and a dynamic energy-aware routing. Significant values of switched-off links are reached in the simulations where real topologies and demands data are used. Moreover, the obtained results confirm that crucial network parameters such as control traffic delay, data path latency, link utilization and Ternary Content Addressable Memory (TCAM) occupation are affected by the performance-agnostic energy-aware model.
“…CSI measurement is critically challenging in unlicensed URLLC because of the strictly limited delay budget. Recently, some typical codes are redesigned and optimized for short packet transmissions in MTC, such as low-density parity check, turbo, extended Bose-Chaudhuri-Hocquenghem, polar, convolutional, and analog fountain codes [2], [3].…”
Section: Phy Layer Advances and Intrinsic Limitationmentioning
confidence: 99%
“…Other enabling technologies include designing a frame structure to meet 1 ms user plane latency [3]; wideband spectrum sensing techniques [7]; and allowing grant-free access [2]. Recent improvements in self-interference suppression (or in-band full-duplex) can be used to reduce the sensing delay for URLLC.…”
Section: Phy Layer Advances and Intrinsic Limitationmentioning
In this article, we aim to address the question of how to exploit the unlicensed spectrum to achieve ultra-reliable, low-latency communications (URLLC). Potential URLLC PHY mechanisms are reviewed and then compared via simulations to demonstrate their potential benefits to URLLC. Although a number of important PHY techniques help with URLLC, the PHY layer exhibits an intrinsic trade-off between latency and reliability, posed by limited and unstable wireless channels. We then explore MAC mechanisms and discuss multi-channel strategies for achieving low-latency LTE unlicensed-band access. We demonstrate, via simulations, that the periods without access to the unlicensed band can be substantially reduced by maintaining channel access processes on multiple unlicensed channels, choosing the channels intelligently, and implementing RTS/CTS.
“…Next generation of cellular networks should be able to face the increasing number of network users and their requisites for the high quality of service (QoS) such as lower delay requirements . Many applications that are uniquely contemplated for the fifth generation (5G) of cellular networks such as autonomous vehicles, factory automation, tactile internet, remote control, and healthcare have strict requirements end‐to‐end (E2E) or round trip delay (say around 1 millisecond) . Furthermore, for popular multimedia services such as seamless lip‐synchronized video conferencing and interactive gaming, providing low E2E delay is essential .…”
This work considers two‐way communication between each pair of users with highly delay‐aware applications. We formulate a joint uplink and downlink resource allocation problem in a cloud radio access network. Assuming average end‐to‐end (E2E) delay of each user pair and practical limitation such as maximum transmit power, we maximize the total throughput of all pair of users in the cloud radio access network. In this setup, we consider that each user can be connected to at most one remote radio head and a limited capacity fronthaul link between each remote radio head and baseband unit. To present the resource allocation problem in a more tractable manner, we replace the E2E delay limitation with its equivalent throughput‐based formulation. Due to inherent NP‐hard and nonconvex nature of the proposed problem, we apply successive convex approximation to reach a two‐step iterative algorithm where, in each step, a specific set of optimization variable derived while other variables are fixed. The problem of each step is transformed into the standard geometric programming via the arithmetic‐geometric mean approximation. Simulation results reveal that our proposed joint uplink‐downlink resource allocation algorithm outperforms a case that uplink and downlink resources are allocated separately in terms of total throughput and outage probability of E2E delay, ie, a chance that E2E delay does not hold.
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