Route Selection Strategy Research Articles

Retraction Note to: Energy aware reliable route selection scheme with clustered RP model for wireless sensor networks to promote interaction between human and sensors

Retraction Note to: Energy aware reliable route selection scheme with clustered RP model for wireless sensor networks to promote interaction between human and sensors

Design and Analysis of an Energy-Efficient Load Balancing and Bandwidth Aware Adaptive Multipath N-Channel Routing Approach in MANET

Mobile Ad Hoc Network (MANET) is a collection of spontaneous nodes that form a dynamic network without any centralized administration. Routing decisions for mobile communication is a challenging task because the continuous movement of nodes increases the routing overhead and energy consumption. Numerous studies have been conducted in the field of MANET to reduce the routing decision overhead and energy consumption. Their concepts are good for improving efficiency in terms of load balancing, congestion control, and energy consumption. This article provides new concepts that are able to give better outcomes. This paper, proposes an adaptive Multipath Multichannel (N-channel) Energy Efficient (MMEE) routing approach in which route selection strategies are dependent on predictive energy consumption per packet (calculated accustomed data delivery), available bandwidth, queue length, and channel utilization. Multipath provides multiple routes and balances network load, whereas multichannel reduces network collisions via a channel ideal assignment mechanism. In the multichannel mechanism, link bandwidth is divided into multiple sub-channels. Multiple source nodes access the channel bandwidth in a simultaneous manner that minimizes the network collision. The collaborative multipath multichannel mechanism provides more than one path between a single source or multiple sources to the destination without collision and congestion. The path selection is based on the MMEE routing approach. In the proposed MMEE, a load and bandwidth aware routing method selects the path, based on node energy and predicts their lifetime, which increases the network reliability. The result shows the comparative analysis between various multichannel medium access techniques such as MMAC, Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning based Multipath Routing (QMR), Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV), and the proposed MMEE method. The outcome concludes that the MMEE method performs better than other schemes. The proposed MMEE protocol provides better performance in terms of percentage of data received, throughput, and minimum energy utilization.

SARSA-based delay-aware route selection for SDN-enabled wireless-PLC power distribution IoT

The integration of power line communications (PLC) and wireless communications in power distribution internet of things (PD-IoT) provides a cost-efficient and easy-to-access solution to solve the problems of limited range of access and signal fading due to the influence of distance and obstacles. The traditional route selection methods are difficult to adapt to uncertain global state information (GSI) under dynamic network environment, the integration of PLC and wireless communications, and strong electromagnetic interference. In this paper, we put forward a state-action-reward-state-action (SARSA)-based Delay-aware Route Selection (SDRS) algorithm, which adopts software-defined networking (SDN) to simplify the network configuration and management in wireless-PLC PD-IoT. The proposed algorithm utilizes SARSA to evaluate and learn the optimal route selection strategy that can reduce transmission delay and improve reliability. Moreover, it can also adapt to the dynamic and complex communication environment. Compared with existing shortest route selection (SRS) algorithm and random route selection (RRS) algorithm, numerical results verify that SDRS has excellent performances in terms of transmission delay and reliability.

E-S-RSM-RSA: A Novel Energy and Spectrum Efficient Regenerator Aware Multipath Based Survivable RSA in Offline EON

This paper proposes the design of energy and spectrum efficient, survivable Routing and Spectrum Allocation (RSA) scheme for regenerator aware Elastic Optical Network (EON) under static environment. Regenerator(s), after being placed at the intermediate site(s) of the EON, helps in reducing the spectrum required for a traffic demand associated with the connection request, at the expense of its huge power consumption. Any effort to ensure survivability also leads to an increase in power consumption due to provisioning redundancy in EON. All these factors imply a trade-off to exist in between total power consumption and spectrum utilization while the placement of regenerator(s) in EON plays a key role. A two step Integer Linear Programming based model has been formulated to design multipath based survivable RSA while optimizing spectrum requirement and energy consumption in regenerator aware offline EON jointly. E-S-RSM-RSA problem is an NP-hard one and hence intractable in nature. A Heuristic algorithm based on the Non-dominated Sorting Genetic Algorithm addressing this objective has been developed. The heuristic performance is compared with that of the ILP model in terms of spectrum utilization and energy consumption. Simulation results of the heuristic tested on two large-sized topologies also confirm the existing trade-off.

Optimal Route Selection Decision-Making Based on Intelligent Network

Modern intelligent network provides a lot of convenience for the development of the society, especially for some practical NP-hard optimal problems. In this paper, we study a game case which is a problem of optimal strategy of desert crossing based on intelligent network and then propose an optimal route selection decision-making. We construct some dynamic multiobjective network problems and use heuristic algorithm to solve the two problems in four levels in the paper. The innovation of this paper lies in the optimal route selection strategy which considers different environment conditions and their own situations. The cross research between the practical engineering problems and mathematics is applied flexibly in this article. Moreover, the strategy given in this paper is a general direction rather than a specific result, which is also in line with the characteristics of diversity of the game optimal results.

REERS: Reliable and energy‐efficient route selection algorithm for heterogeneous Internet of things applications

SummaryMachine‐type communication (MTC) such as device‐to‐device and machine‐to‐machine communication is a technology used to realize the concept of Internet of things (IoT). The fifth generation (5G) IoT is composed of large density of wireless sensor device. The massive roll out of the MTC devices is a serious challenge for wireless communication networks from operational and management perspective, including massive access, route selection, energy efficiency and network congestion. Many proposals have been put forward by the research community to cater to the issues and difficulties of massive MTC (mMTC) access in large density sensor network‐enabled IoT communication environment. Recently, data aggregation with efficient route selection has attracted a lot of research attention owing to its robust ability to resolve the above‐mentioned challenges. Existing data routing and aggregation methodologies are not efficient when adopted to heterogeneous IoT applications as they fail to bring trade‐off between energy efficiency and latency minimization. This research work proposes reliable and energy‐efficient route selection (REERS) scheme to reduce energy dissipation and latency for catering both real‐time and non‐real‐time applications. Experiment outcomes shows the REERS schemes achieves much superior performance than existing routing and aggregation methodologies over latency reduction and energy efficiency.

Study on Passenger Flow Assignment Method of Urban Rail Transit Based on Improved Logit Model

With the advantages of small pollution, punctuality, safety and large capacity, urban rail transportation provides good ideas for solving China’s urban transportation problems and gradually becomes an indispensable part of China’s urban public transportation system. According to the current development of urban rail transportation, the era of networked operation has arrived, and the connectivity between different stations in the metro network and the mobility of operation and management have greatly increased. And for passengers, considering the convenience of seamless transfers, the complexity of the line network structure, and the rapid feedback of real-time passenger flow information on the line, it will cause the passengers’ travel behavior to be highly random. Different passengers are choosing the route selection scheme to reach the target station will also make the spatial and temporal distribution within the rail transit network more diverse and complicated. This paper adopts the method of analyzing the behavior of passenger travel route selection under the established urban rail transit network to establish a generalized cost function and Logit model, and contributes to the planning, design and operation management of urban rail transit.

An Experimental Study on D2D Route Selection Mechanism in 5G Scenarios

This paper demonstrates a route selection mechanism on a testbed with heterogeneous device-to-device (D2D) wireless communication for a 5G network scenario. The source node receives information about the primary users’ (PUs’) (or licensed users’) activities and available routes from the macrocell base station (or a central controller) and makes a decision to select a multihop route to the destination node. The source node from small cells can either choose: (a) a route with direct communication with the macrocell base station to improve the route performance; or (b) a route with D2D communication among nodes in the small cells to offload traffic from the macrocell to improve spectrum efficiency. The selected D2D route has the least PUs’ activities. The route selection mechanism is investigated on our testbed that helps to improve the accuracy of network performance measurement. In traditional testbeds, each node (e.g., Universal Software Radio Peripheral (USRP) that serves as the front-end communication block) is connected to a single processing unit (e.g., a personal computer) via a switch using cables. In our testbed, each USRP node is connected to a separate processing unit, i.e., raspberry Pi3 B+ (or RP3), which offers three main advantages: (a) control messages and data packets are exchanged via the wireless medium; (b) separate processing units make decisions in a distributed and heterogeneous manner; and (c) the nodes are placed further apart from one another. Therefore, in the investigation of our route selection scheme, the response delay of control message exchange and the packet loss caused by the operating environment (e.g., ambient noise) are implied in our end-to-end delay and packet delivery ratio measurement. Our results show an increase of end-to-end delay and a decrease of packet delivery ratio due to the transmission of control messages and data packets in the wireless medium in the presence of the dynamic PUs’ activities. Furthermore, D2D communication can offload 25% to 75% traffic from macrocell base station to small cells.

A secure GA approach in mesh based multicast network

Multicast routing is the process of sending data from one or more sources to many destinations. To achieve high efficiency, it is mandatory to minimize path delay due to blocking, and the cost of the path tree to reach destinations [6]. Evolutionary Algorithms have become more and more popular in the domain of searching, optimization and machine learning. Notwithstanding, a mesh is extremely slight when the nodes support high in topologies. The ODMRP needs control messages initiate at each source node of a multicast group to be flooded all over the networks. To optimize this problem, some heuristic approaches like the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) have been deployed in the route selection strategy [7]. A GA based ODMRP is planned for efficient multicast mesh routing. In this paper, modified genetic operators such as topology encoding, topology crossover and node mutation. The number of senders performing flooding and the issue of restricting the flood of control messages is minimized by reducing the number of forwarding nodes by means of applying the heuristic technique GA. Along with path tree, consistent key chaining and key management is required to execute a standard security framework. This anticipated work will be done using Newton's interpolation technique to implement. It shows efficient encoding scheme of the reconstruction of the multicast mesh topology and the simulation results demonstrate the effectiveness of the sGenODMRP compared to the ODMRP protocol.

Performance analysis of MIEEPB and LEACH protocol on the bases of energy efficiency in wireless sensor network

Wireless sensor network (WSN) consists of a large no of sensor nodes densely deployed over an area sensor node are capable of collaborating with one another and measuring the condition of their surrounding environments (like temperature, light, sound and vibration) the challenges of successful WSN possess limited processing capability, storage and energy resources. Sensor network depends on life of sensor node i.e., ultimately on the energy used during its operation. This work is focusing how a MIEEPB protocol is highly energy efficient compared to the LEACH protocol with the routing selection strategy and the simulating graph of no. Of alive nodes per rounds and no. Of dead nodes per rounds concludes that MIEEPB has the better life span for WSN and shows how energy is saved by using a MATLAB (2020b) software.

Environmental and Social Problems and Countermeasures in Transportation System under Resource Constraints

With the rapid development of urban economy and the acceleration of urbanization, the demand for urban traffic is increasing rapidly. The single traffic-oriented planning does not take into account the requirements of traffic development on resources and the impact on the environment. The traffic construction of most cities can not fully meet the standard of ecotype. In this paper, the vehicle distribution route optimization problem under multiresource constraints such as vehicle energy capacity and vehicle loading capacity is studied, and the static and dynamic models of distribution route optimization under multiresource constraints are established. In the static distribution route optimization model, the distribution route optimization problem with subloops is solved by modifying the network structure and adding virtual resource points. In the dynamic model, the spatiotemporal network model is used to avoid the generation of subloops, and the description of the vehicle distribution route planning problem is more intuitive and accurate. The model enriches the vehicle distribution route selection scheme at the cost of expanding the model scale. And it can solve the time when the vehicle arrives and leaves the customer point. This paper provides a good countermeasure for solving the environmental and social problems in the transportation system under the condition of resource constraints.

Multi-objective cost optimization for geological risk oriented rail transit route selection

China’s rail transit has entered a period of rapid development, but related safety and risk management fail to match with high-speed construction. The complex and uncertain underground space leads to frequent risk accidents of urban rail transit. As the primary task of rail transit development, the reasonable route selection can not only avoid a lot of geological risks, but also greatly save the duration and cost. In order to guide the rail transit route selection work scientifically and reasonably, the cost problems related to geological risk factors by constructing the objective function of risk assessment, section construction cost and duration are analyzed in this study. Combining with heuristic algorithms such as ant algorithm and particle swarm optimization algorithm, an evaluation method of cost optimization of rail transit route selection for the geological risk are put forward. Taking the geological data of a certain section of a proposed rail transit route in Guangzhou as an example, based on this proposed method, the optimal route selection scheme with relatively low risk, short construction duration and low cost is found, which provides theoretical basis and guidance for the route selection and construction of rail transit, and also verifies the rationality of the application of the cost optimization method for the geological risk to multi-objective engineering management.

Capacitated Refuge Assignment for Speedy and Reliable Evacuation

When a large-scale disaster occurs, each evacuee should move to an appropriate refuge in a speedy and safe manner. Most of the existing studies on the refuge assignment consider the speediness of evacuation and refuge capacity while the safety of evacuation is not taken into account. In this paper, we propose a refuge assignment scheme that considers both the speediness and safety of evacuation under the refuge capacity constraint. We first formulate the refuge assignment problem as a two-step integer linear program (ILP). Since the two-step ILP requires route candidates between evacuees and their possible refuges, we further propose a speedy and reliable route selection scheme as an extension of the existing route selection scheme. Through numerical results using the actual data of Arako district of Nagoya city in Japan, we show that the proposed scheme can improve the average route reliability among evacuees by 13.6% while suppressing the increase of the average route length among evacuees by 7.3%, compared with the distance-based route selection and refuge assignment. In addition, we also reveal that the current refuge capacity is not enough to support speedy and reliable evacuation for the residents.

RETRACTED ARTICLE: Energy aware reliable route selection scheme with clustered RP model for wireless sensor networks to promote interaction between human and sensors

Wireless sensor network (WSN) is one of the significant flourishing areas of research, due to its controllability, accessibility and adaptability. WSN is deployed for better control and track of the industrial equipments, which paves way for the proposals of numerous real-time applications out of it. The primary goal of a WSN is to promote communication between the industrial sensor nodes, such that the information is shared and decisions can be made. However, communication works out at the cost of energy, which is considerably scarce in WSN. Thus, energy efficient routing is necessary for a network to work for a reasonable time. This work presents an energy efficient route selection scheme, which selects the reliable route out of all possible routes. The reliable route is selected by considering the trust level of the sensor nodes, which results in faster and reliable data transmission. The performance of the proposed work is tested and compared with the existing approaches in terms of packet delivery rate, latency, energy efficiency and network lifetime.

Multiparameter Fusion Decision Routing Algorithm for Energy-Constrained Wireless Sensor Networks

For energy-limited wireless sensor networks (WSNs), we propose a multiparameter fusion decision routing (MPFDR) algorithm in this study. This algorithm gives a comprehensive account of the residual energy and forward distance, single-hop transmission ratio, cache queue, and energy equilibrium degree. It calculates the routing evaluation parameters of the forward neighbors, realizing a multidirectional reflection of the network status. Simultaneously, combined with the defined routing selection strategy based on the parameter contribution degree and fuzzy contribution degree, the fusion contribution degree of each forward neighbor is obtained. Then, the node with the most considerable fusion contribution degree is selected as the next hop. Finally, the performance of the MPFDR algorithm is simulated and compared with other algorithms. Simulation results indicate that our algorithm has good congestion control ability in energy-limited wireless sensor networks and can significantly reduce the packet loss rate and average hops.

Interference-Aware Multisource Transmission in Multiradio and Multichannel Wireless Network

A node can provide a file to other nodes after downloading the file or data from the Internet. When more than one node have obtained the same file, this is considered a multisource transmission, in which all these nodes can act as candidate providers (sources) and transmit the file to a new request node (destination) together. In cases where there is negligible or no interference, multisource transmission can improve the download throughput because of parallel transmissions through multiple paths. However, this improvement is not guaranteed due to wireless interference among different paths. Wireless interference can be alleviated by the multiradio and multichannel technique. Because the source and multipath routing selections interact with channel assignment, the multisource transmission problem with multiradio and multichannel presents a significant challenge. In this paper, we propose a distributed joint source, routing, and channel selection scheme. The source selection issue can be concurrently solved via multipath finding. There are three sub-algorithms in our scheme, namely, interference-aware routing algorithm, channel assignment algorithm, and local routing adjustment algorithm. The interference-aware routing algorithm is used to find paths sequentially and is jointly executed with the channel assignment algorithm. After finding a new path, the local routing adjustment algorithm may be executed to locally adjust the selected paths so as to further reduce wireless interference. Extensive simulations have been conducted to demonstrate that our algorithms can effectively improve the network aggregate throughput, as well as reduce delay and packet loss probability.

A Vehicle Route Planning Method of Two-Phase Large-Scale Crowd Evacuation in Typhoon Relief Activities

Large-scale crowd evacuation is an important measure guaranteeing the safety of disaster-stricken victims in typhoon relief activities. Decision-making related to antityphoon crowd evacuation must take full consideration of the destructive effect of typhoons and their secondary disasters, time urgency, and resource limitation. To give full play to limited vehicle resources, the influence of a typhoon and its secondary disasters on antityphoon evacuation are mainly manifested during the execution of evacuation tasks in this article. The shortest time spent in completing all evacuation tasks was taken as the objective. Then, a vehicle route selection model for two-phase large-scale antityphoon crowd evacuation was built under an uncertain environment, and a matrix encoding–based genetic algorithm was designed to solve the model. Under the background of Super Typhoon Meranti in 2016, the model and algorithm were applied to crowd evacuation in a typhoon in Xiamen for a simulated analysis. Results indicate that in typhoon relief activities, emergency decision makers can use the proposed method to acquire a scientific and reasonable route selection scheme for antityphoon crowd evacuation according to related typhoon disaster data.

SeC‐SDWSN: Secure cluster‐based SDWSN environment for QoS guaranteed routing in three‐tier architecture

SummarySoftware defined wireless sensor network (SDWSN) is a recent evolution in networking that improves network performance and scalability. However, Quality of Service (QoS) and security are major the issues in SDWSN due to inefficient route selection (traffic load minimization algorithm) and insecure cryptography scheme (homomorphic algorithm). This paper proposes novel three‐tier architecture for secure cluster‐based SDWSN (SeC‐SDWSN) environment to ensure QoS and security for WSN using SDN. In the first tier, sensor nodes are segregated into multiple clusters by secure hash tree‐based clustering (SHTC) algorithm. Within each secure cluster, data transmission is performed through optimal route selected by adaptive spider monkey optimization (ASMO) algorithm in which two new fitness factors (F1, F2) are formulated by multiple QoS metrics. For data security, parallel advanced encryption standard with cipher block chaining (PAES‐CBC) algorithm is proposed. Aggregated ciphertext is transmitted to optimal switch in the second tier by using fuzzy weighted technique for order preference by similarity to ideal solution (FW‐TOPSIS) algorithm according to selection criteria. Switches forward the data to sink node based on flow rules deployed by SDN controllers in the third tier. SDN controllers provide global view on the entire network and deploy flow rules on switches in accordance to network status and security level. Extensive simulation in ns‐3 shows that the proposed three‐tier architecture achieves 5% throughput improvement, 7.8% PDR improvement, and 16% energy consumption improvement.

Delay-Constrained Routing via Heterogeneous Vehicular Communications in Software Defined BusNet

As a critical part of public transportation systems, buses driving routinely in urban areas naturally form a bus ad-hoc network (BusNet). Different from conventional vehicular ad-hoc networks, the sparse distribution of buses magnifies the problem of intermittent network connectivity, making it more challenging for real-time routing. In this paper, we first present a novel architecture called software-defined BusNet, where the distributed controllers (i.e., base stations) collect traffic information and real-time requests from buses via vehicle-to-cellular communication. The collected information enables the logically centralized controller to make routing decisions with global traffic information. Then, the routing decisions are returned to roadside units (RSUs) and buses, which will instruct the data broadcast from RSUs to buses via vehicle-to-roadside (V2R) communication, and data forwarding among the buses through vehicle-to-vehicle (V2V) communication. On this basis, we formulate the problem of delay-constrained routing for BusNet (DCRB) which aims to maximize both the delivery ratio and the bandwidth efficiency. We build a probabilistic model to analyze the encounter probability and encounter delay between the relay buses based on the predicable bus traces. Further, we derive the expected reachability and expected delivery delay of the multi-hop routing path. The routing graph is constructed for searching the feasible routing paths via the modified Dijkstra algorithm. Four routing selection strategies are proposed based on different metrics: HRF (highest reachability first), SDF (shortest delivery delay first), MHF (minimum number of hops first), and RDH (combination of reachability, delay, and hop). Finally, we build the simulation model and implement the proposed routing algorithms for performance evaluation. The comprehensive simulation results demonstrate that RDH achieves the best overall performance on improving system delivery ratio and enhancing bandwidth efficiency.

Terminal Vitalization Strategy through Optimal Route Selection Adopting CFPR Methodology

Container shipping route selection strategy has become an important component in attracting additional cargo volumes and increasing terminal competitiveness of small and medium ports (SMPs). Shipping route selection relies upon decisions based on real industry data and expert judgments. There is scant research that places emphasis on container shipping route selection as a vital aspect of SMPs. This paper bridges the gap by utilizing Consistent Fuzzy Preference Relations (CFPR) methodology, which handles both qualitative and quantitative factors in order to select optimal routes for SMPs. Donghae port, which is located on the east coast of South Korea, is analyzed as a case study. The results illustrate that volume commitment ranks first among the 19 established selection factors, followed by incentive system risk and head-haul ratio. This study also reveals that Donghae-Hochiminh is the optimal route for the Donghae port, while the container shipping route of Donghae-Port Kelang is ranked in the middle, and Donghae-Jakarta is considered to be the least optimal route amongst the three alternatives.