Load balancing-based routing optimization mechanism for power communication networks

2016 ◽  
Vol 13 (8) ◽  
pp. 169-176 ◽  
Author(s):  
Ningzhe Xing ◽  
Siya Xu ◽  
Sidong Zhang ◽  
Shaoyong Guo
Keyword(s):  
Load Balancing ◽  
Communication Networks ◽  
Routing Optimization ◽  
Optimization Mechanism

PQROM: To optimize software defined network QoS-aware routing with proximal policy optimization

2021 ◽  
pp. 1-10
Author(s):  
Wei Zhou ◽  
Xing Jiang ◽  
Bingli Guo (Member, IEEE) ◽  
Lingyu Meng
Keyword(s):  
Software Defined Network ◽  
Training Time ◽  
Good Convergence ◽  
Reward Function ◽  
Routing Optimization ◽  
Policy Gradient ◽  
Discrete Action ◽  
Policy Optimization ◽  
Optimization Mechanism ◽  
Network Pattern

Currently, Quality-of-Service (QoS)-aware routing is one of the crucial challenges in Software Defined Network (SDN). The QoS performances, e.g. latency, packet loss ratio and throughput, must be optimized to improve the performance of network. Traditional static routing algorithms based on Open Shortest Path First (OSPF) could not adapt to traffic fluctuation, which may cause severe network congestion and service degradation. Central intelligence of SDN controller and recent breakthroughs of Deep Reinforcement Learning (DRL) pose a promising solution to tackle this challenge. Thus, we propose an on-policy DRL mechanism, namely the PPO-based (Proximal Policy Optimization) QoS-aware Routing Optimization Mechanism (PQROM), to achieve a general and re-customizable routing optimization. PQROM can dynamically update the routing calculation by adjusting the reward function according to different optimization objectives, and it is independent of any specific network pattern. Additionally, as a black-box one-step optimization, PQROM is qualified for both continuous and discrete action space with high-dimensional input and output. The OMNeT ++ simulation experiment results show that PQROM not only has good convergence, but also has better stability compared with OSPF, less training time and simpler hyper-parameters adjustment than Deep Deterministic Policy Gradient (DDPG) and less hardware consumption than Asynchronous Advantage Actor-Critic (A3C).

A Routing Protocol for Emergency Communication Based on Load Balancing

2015 ◽  
Vol 719-720 ◽  
pp. 744-749
Author(s):  
Hui Han ◽  
Hong De Zhang ◽  
Yang Wang
Keyword(s):  
Load Balancing ◽  
Communication Networks ◽  
Routing Protocol ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Network Routing ◽  
Packet Transmission ◽  
Emergency Communication ◽  
Network Load

Ad-hoc communications is a mobile communication networks and computer networks combine with no infrastructure support, and network survivability and flexibility is strong, especially suitable for emergency communication. As the existing mobile ad hoc network routing protocols lack of network load balancing capabilities, this paper proposed a routing protocol based on load balancing LBBR (Load Balancing Based Routing). Simulation results shows that, LBBR can improve the success rate of packet transmission, reducing the average end to end delay, thus effectively improving network performance.

scholarly journals Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Dawei Shen ◽  
Wei Yan ◽  
Yuhuai Peng ◽  
Yanhua Fu ◽  
Qingxu Deng
Keyword(s):  
Wireless Networks ◽  
Load Balancing ◽  
Congestion Control ◽  
Communication Networks ◽  
Mobile Networks ◽  
Scheduling Algorithm ◽  
Mobile Wireless Networks ◽  
Traffic Scheduling ◽  
Mobile Wireless ◽  
Artificial Fish Swarm Algorithm

Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT), targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN). This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA) is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.

Adaptive Agent-Driven Routing and Load Balancing in Communication Networks

1998 ◽  
Vol 01 (02n03) ◽  
pp. 237-254 ◽  
Author(s):  
Martin Heusse ◽  
Dominique Snyers ◽  
Sylvain Guérin ◽  
Pascale Kuntz
Keyword(s):  
Load Balancing ◽  
Communication Networks ◽  
Traffic Condition ◽  
Link State ◽  
New Family ◽  
Traffic Loads ◽  
Adaptive Agent ◽  
Simulated Network ◽  
Routing Tables ◽  
New Algorithms

This paper presents an unified overview of a new family of distributed algortithms for routing and load balancing in dynamic communication networks. These new algorithms are described as an extension to the classical routing algorithms: they combine the ideas of online asynchronous distance vector routing with adaptive link state routing. Estimates of the current traffic condition and link costs are measured by sending routing agents in the network that mix with the regular information packets and keep track of the costs (e.g. delay) encountered during their journey. The routing tables are then regularly updated based on that information without any central control nor complete knowledge of the network topology. Two new algorithms are proposed here. The first one is based on round trip routing agents that update the routing tables by backtracking their way after having reached the destination. The second one relies on forward agents that update the routing tables directly as they move toward their destination. An efficient co-operative scheme is proposed to deal with asymmetric connections. All these methods are compared on a simulated network with various traffic loads; the robustness of the new algorithms to network changes is proved on various dynamic scenarii.

scholarly journals Interference Minimization Resource Allocation for V2X Communication Underlaying 5G Cellular Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaoqin Song ◽  
Kuiyu Wang ◽  
Lei Lei ◽  
Liping Zhao ◽  
Yong Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Communication Networks ◽  
Transmission Rate ◽  
Transmission Power ◽  
Interference Minimization ◽  
Initial Power ◽  
Cellular Mobile ◽  
Optimization Mechanism

In this paper, the resource allocation for vehicle-to-everything (V2X) underlaying 5G cellular mobile communication networks is considered. The optimization problem is modeled as a mixed binary integer nonlinear programming (MBINP), which minimizes the interference to 5G cellular users (CUs) subject to the quality of service (QoS), the total available power, the interference threshold, and the minimal transmission rate. To achieve that, the original MBINP is decomposed into three steps: transmission power initialization, subchannel assignment, and power allocation. Firstly, the minimum transmission power required by the V2X users (VUs) is set as the initial power value. Secondly, the Hungarian algorithm is used to obtain the appropriate subchannel. Finally, an optimization mechanism is proposed to the power allocation. Simulation results show that the proposed algorithm can not only ensure the minimal transmission rate of VUs but also further improve the CUs’ channel capacity under the premise of guaranteeing the QoS of the CUs.

Adaptive agent driven routing in communication networks: comparison with a classical approach

1999 ◽  
Vol 02 (03) ◽  
pp. 209-219 ◽  
Author(s):  
Martin Heusse ◽  
Dominique Snyers ◽  
Yvon Kermarrec
Keyword(s):  
Load Balancing ◽  
Complex Systems ◽  
Communication Networks ◽  
Classical Approach ◽  
New Approach ◽  
Adaptive Agent ◽  
Quality Of Delivery

This paper follows an earlier publication in the Advances in Complex Systems journal (Heusse et al., 1998) where we presented a new algorithm based on collaborative agents for routing in communication networks. In this document, we shall investigate its load-balancing capability. This capability is required as a first step to achieve quality of delivery and service. We also compare our new approach to the classical ones and discuss their respective benefits.

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