Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0

Intelligent resource allocation management for vehicles network: An A3C learning approach

Vehicular ad hoc network is a collection of vehicles and associated road-side infrastructure, which is able to provide mobile wireless communication services. This highly dynamic topology structure is still open to many routing and message forwarding challenges. This paper addresses the issue of message delivery from vehicle to a fixed destination, by hopping over neighboring vehicles. We propose a reinforcement-learning-based hierarchical protocol called QGrid to improve the message deliver ratio with minimum possible delay and hops. The protocol works at two levels. First, it divides the geographical area into smaller grids and finds the next optimal grid toward the destination. Second, it discovers a vehicle inside or moving toward the next optimal grid for message relaying. There is no need of routing tables as the protocol builds a Q-value table based on the traffic flow in neighbor grids, which is then used for the grid selection. The vehicle selection process can employ different strategies, like, greedy selection of nearest neighbor, or solution based on the two-order Markov chain prediction of neighbor movement. This combination makes QGrid an offline and online solution. QGrid is further improved giving higher priority to vehicles with fixed routes and better communication capabilities, like buses, when making the vehicle selection. We have carried out extensive simulation evaluation by using real-world vehicular traces to measure the performance of our proposed schemes. The simulation comparisons among QGrid with/without bus aid, and existing position-based routing protocols, show the great improvement in the delivery percentage by our proposed routing protocol.

Hierarchical Routing for Vehicular Ad Hoc Networks via Reinforcement Learning

The future wireless networks need to improve spectrum and energy efficiency to satisfy the increasing demand for high data rate. Device-to device (D2D) communications have the ability to address this problem. This paper focuses on the underlay D2D relay function to improve cellular coverage quality. Although there are a few relevant works in this aspect, there is room for further improvement. For example, there is the constraint on the number of relays in a transmission path, which hardly meets the requirement of the cell-edge devices to fully improve their cellular throughput. Also, there is little energy constraint for underlay D2D relay selection, which is difficult to guarantee the service life of underlay D2D relaying links. Furthermore, without careful regulation of transmission power in terms of cellular coverage improvement, it is not conducive to the improvement of spectrum and energy efficiency in this aspect. Therefore, this paper proposes the improved scheme to deal with these problems, which can: 1) improve spectrum efficiency by using underlay spectrum sharing mode and alleviating its weakness (e.g., co-channel interference); 2) enhance comprehensive performance of underlay D2D relaying links by jointly considering multiple Quality-of-Service (QoS) metrics; 3) reduce overhead of relay selection by proposing a greedy algorithm based on a distributed local search; and 4) improve both energy efficiency and convergence time by designing a new power adjustment scheme based on the improved potential game decision algorithm. The theoretical analysis proves the existence of Nash equilibrium, and the simulation results show that the proposed game decision algorithm accelerates convergence and the proposed whole scheme improves cellular coverage quality.

Multi-Hop Relay-Aided Underlay D2D Communications for Improving Cellular Coverage Quality

Matrix completion has emerged very recently and provides a new venue for low cost data gathering in Wireless Sensor Networks (WSNs). Existing schemes often assume that the data matrix has a known and fixed low-rank, which is unlikely to hold in a practical system for environment monitoring. Environmental data vary in temporal and spatial domains. By analyzing a large set of weather data collected from 196 sensors in ZhuZhou, China, we reveal that weather data have the features of low-rank, temporal stability, and relative rank stability. Taking advantage of these features, we propose an on-line data gathering scheme based on matrix completion theory, named MC-Weather, to adaptively sample different locations according to environmental and weather conditions. To better schedule sampling process while satisfying the required reconstruction accuracy, we propose several novel techniques, including three sample learning principles, an adaptive sampling algorithm based on matrix completion, and a uniform time slot and cross sample model. With these techniques, our MC-Weather scheme can collect the sensory data at required accuracy while largely reducing the cost for sensing, communication, and computation. We perform extensive simulations based on the data traces from weather monitoring and the simulation results validate the efficiency and efficacy of the proposed scheme.

Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion

Cooperative channel allocation and scheduling are key issues in wireless mesh networks with multiple interfaces and multiple channels. In this paper, we propose a load balance link layer protocol (LBLP) aiming to cooperatively manage the interfaces and channels to improve network throughput. In LBLP, an interface can work in a sending or receiving mode. For the receiving interfaces, the channel assignment is proposed considering the number, position and status of the interfaces, and a task allocation algorithm based on the Huffman tree is developed to minimize the mutual interference. A dynamic link scheduling algorithm is designed for the sending interfaces, making the tradeoff between the end-to-end delay and the interface utilization. A portion of the interfaces can adjust their modes for load balancing according to the link status and the interface load. Simulation results show that the proposed LBLP can work with the existing routing protocols to improve the network throughput substantially and balance the load even when the switching delay is large.

Cooperative channel allocation and scheduling in multi-interface wireless mesh networks

A reliable bi-directional communication network is one of the key factors in smart grid (SG) to meet application requirements and improve energy efficiency. As a promising communication infrastructure, wireless mesh network (WMN) can provide high speed and cost-effect communication for SG. However, challenges remain to maintain high reliability and quality of service (QoS) when applying WMNs to SG. In this paper, we first propose a hybrid wireless mesh protocol (HWMP) based neighbor area network (NAN) QoS-aware routing scheme, named HWMP-NQ, to meet the QoS requirements by applying an integrated routing metric to route decision with effective link condition probing and queue optimization. To further improve the reliability of the proposed HWMP-NQ, we present a multi-gateway backup routing scheme along with a routing reliability correction factor to mitigate the impact of routing oscillations. Finally, we evaluate the performances of the proposed schemes on NS3 simulator. Extensive simulations demonstrate that HWMP-NQ can distinguish different applications and satisfy the QoS requirements respectively, and also improve the average packet delivery ratio and throughput with a reduced routing overhead, even with a high failure rate of mesh nodes.

A reliable QoS-aware routing scheme for neighbor area network in smart grid

For effective routing in wireless mesh networks, we proposed a routing metric, expected path throughput (EPT), and a routing protocol, expected path throughput routing protocol (EPTR), to maximize the network throughput . The routing metric EPT is based on the estimated available bandwidth of the routing path, considering the link quality, the inter- and intra-flow interference and the path length. To calculate the EPT of a routing path, we first calculate the expected bandwidth of the link and the clique, and then consider the decay caused by the path length. Based on EPT, a distributed routing protocol EPTR is proposed, aiming to balance the network load and maximize the network throughput. Extensive simulations are conducted to evaluate the performance of the proposed solution. The results show that the proposed EPTR can effectively balance the network load, achieve high network throughput, and out-perform the existing routing protocols with the routing metrics previously proposed for wireless mesh networks.

EPTR: expected path throughput based routing protocol for wireless mesh network

Optimal routing in wireless mesh networks is a challenging problem considering inter- and intra-flow interference. To solve the problem, first, we define a new routing metric, expected path bandwidth (EPBW), where the varying link rate (due to wireless channel quality) and the dynamic link load (considering the inter- and intra-flow interference) have been considered to estimate EPBW accurately. Second, based on the proposed EPBW, we propose a distributed routing protocol for WMNs, aiming to maximize network throughput. We implement the proposed protocol and the routing metric EPBW in NS-2. We then design various scenarios to evaluate the protocol performance extensively using NS-2 simulation. Simulation results show that the proposed protocol and metric can substantially out-perform the state-of-the-art routing metrics, such as expected transmission count (ETX) and expected transmission time (ETT), and previous routing protocols including AODV, DSDV, and DSR.

Channel quality and load aware routing in wireless mesh network

Channel assignment and link scheduling are the key issues in wireless mesh networks with multiple interfaces and multiple channels. In this paper, we proposed a load balance link layer protocol, LBLP, which focuses on these issues aiming to improve the network capacity. The protocol, LBLP, classifies interfaces into three categories: static ones, dynamic ones and adaptive ones, with the following three main contributions. First, to minimize the interference among interfaces, a channel assignment for static interfaces is proposed by considering not only the number and positions of the channels but also the active status of the interfaces, Second, the link scheduler seeks a mechanism to map channel queues with the dynamic interfaces aiming to reduce the negative impacts of the interface switching delay, Third, according to the load, we adjust the status of the adaptive interfaces to avoid bottleneck so as to balance the load among interfaces. Simulation results show that LBLP improve the network throughput significantly despite the large switching delay and limited interfaces.

Qiang Liu

Papers

Cooperative channel allocation and scheduling in multi-interface wireless mesh networks

A reliable QoS-aware routing scheme for neighbor area network in smart grid

EPTR: expected path throughput based routing protocol for wireless mesh network

Channel quality and load aware routing in wireless mesh network

A Load Balance Link Layer Protocol for Multi-channel Multi-interface Wireless Mesh Networks