Path Selection Algorithm Research Articles

Optimal path selection algorithm for mobile beacons in sensor network under non-dense distribution

Abstract When the traditional anchor aided location algorithm is used to select the mobile beacon path in the sensor network, there is no analysis of the energy imbalance of nodes in non-dense conditions, the optimal network node cannot be selected, and the selection error of the optimal path of the beacon is larger. A path selection algorithm for mobile beacons in a sensor network under non-dense distribution is proposed. Using the mobile beacon based wireless sensor network location algorithm, the weighted centroid algorithm and the extended Kalman filter (EKF) are used to obtain the accurate location results of the unknown nodes around the mobile beacon in the sensor network under non-dense distribution condition. The optimal node energy partition of the unknown node is obtained by the chaotic differential evolution method, and the optimal location of the optimal energy node in the wireless sensor network is calculated using the dynamic escape particle swarm optimization method, and the optimal beacon path is extracted. The experimental results show that the proposed algorithm can enhance the clustering performance of the optimal node in the wireless sensor network and has a better performance of dynamic node selection in wireless sensor network, and the convergence speed is faster and the operation time is shorter.

VR-CPES: A Novel Cyber-Physical Education Systems for Interactive VR Services Based on a Mobile Platform

The evolution of virtual reality technology allows users to immerse themselves into virtual environments, providing a new experience that is impossible in the real world. The appearance of cyber-physical systems and the Internet of things makes humans to understand and control the real world in detail. The integration of virtual reality into cyber-physical systems and the Internet of things may induce innovative education services in the near future. In this paper, we propose a novel, a virtual reality-based cyber-physical education system for efficient education in a virtual reality on a mobile platform, called VR-CPES. VR-CPES can integrate the real world into virtual reality using cyber-physical systems technology, especially using digital twin. We extract essential service requirements of VR-CPES in terms of delay time in the virtual reality service layer. In order to satisfy the requirements of the network layer, we design a new, real-time network technology interworking software, defined as network and time-sensitive network. A gateway function for the interworking is developed to make protocol level transparency. In addition, a path selection algorithm is proposed to make flexible flow between physical things and cyber things. Finally, a simulation study will be conducted to validate the functionalities and performance in terms of packet loss and delay as defined in the requirements.

Ant colony optimization algorithm with Internet of Vehicles for intelligent traffic control system

Vehicles present on the Internet of Vehicles (IoV) can communicate with each other in order to determine the status of the road and vehicle in real time. These parameters are used to estimate the average speed and identify the optimal route to reach the destination. However, the government traffic departments are unable to use these valuable traffic data and thus more traffic jam, congestion and road accident occurs. In order to overcome this issue, this paper proposes an effective traffic control system with the help of IoV technology. The proposed method is demonstrated in the study are of Vellore district, Tamil Nadu, India. The street maps are segmented into number small number of distinct maps. Ant colony algorithm is applied to each map in order to find the optimal route. In addition, Fuzzy logic based traffic intensity calculation function is proposed in this paper to model the heavy traffic. The proposed IoV based route selection method is compared with the existing shortest path selection algorithms such as Dijikstra algorithm, Kruskal's algorithm and Prim's algorithm. The experimental results proved the good performance of the proposed IoV based route selection method.

Path selection algorithm with minimal delay in wireless sensor networks

With the rapid popularization and development of Internet, global researchers are increasingly paying more and more attention to anonymity and privacy security. Anonymous communication technology has gradually become people’s focus. Attacks against sensors may appear in different layers, so anonymity at network layer should therefore be envisioned. Tor, as one of the anonymous communication systems which implements multi-hop to protect user’s identity privacy on the Internet, is currently the most popular anonymous privacy solution, but the concept of Tor has not applied to wireless sensor networks. Therefore, in this article, we think the mix structure of Tor which is crucial to its anonymity can be applied to wireless sensor networks; what’s more, an improved path selecting algorithm according to round trip time we propose can boost some degree of performance. First, we make a summary of current typical path selection algorithms and analyze the performance and anonymity problems of these algorithms in network congestion. Then, in order to improve the performance of the algorithm in congestion, a routing improvement scheme based on round trip time is proposed.

무선 애드혹 네트워크 에서 강화학습을 이용한 동적 라우팅 경로 선택 알고리즘

본 논문은 애드혹 네트워크에서 동적으로 변화하는 무선통신환경을 지원하기 위해 강화학습을 이용한 라우팅 프로토콜에 대해 제안한다. 제안된 방법의 목적은 전송률, 잔여 에너지, 그리고 종단간 지연과 관련한 라우팅 경로의 유틸리티 함수를 최대화하는 것이다. Q-learning 기반의 라우팅 경로 선택 알고리즘은 패킷 전송 성공률을 고려하여 제안되었다. Q-learning을 적용하는데 있어 각 노드를 상태로 정의하고 노드간의 링크를 행동으로 정의하였다. 패킷전송 및 에너지 소비의 신뢰성을 기반으로 패킷이 목적지에 도착하면 방문된 경로에 보상이 주어진다. 시뮬레이션 결과를 통해 제안된 방법이 다양한 통신상황에서 동적으로 환경에 적응하고 높은 유틸리티를 얻을 수 있음을 보인다.

Joint Energy Supply and Routing Path Selection for Rechargeable Wireless Sensor Networks.

The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a joint energy supply and routing path selection algorithm to extend the network lifetime based on an initiative power supply. We develop a two-stage energy replenishment strategy to supplement the energy consumption of nodes as much as possible. Furthermore, the influence of charging factors on the selection of next-hop nodes in data routing is considered. The simulation results show that our algorithm effectively prolong the network lifetime, and different demands of network delay and energy consumption can be obtained by dynamically adjusting parameters.

Shedding Light on the Dark Corners of the Internet: A Survey of Tor Research

Anonymity services have seen high growth rates with increased usage in the past few years. Among various services, Tor is one of the most popular peer-to-peer anonymizing service. In this survey paper, we summarize, analyze, classify and quantify 26 years of research on the Tor network. Our research shows that ‘security’ and ‘anonymity’ are the most frequent keywords associated with Tor research studies. Quantitative analysis shows that the majority of research studies on Tor focus on ‘deanonymization’ the design of a breaching strategy. The second most frequent topic is analysis of path selection algorithms to select more resilient paths. Analysis shows that the majority of experimental studies derived their results by deploying private testbeds while others performed simulations by developing custom simulators. No consistent parameters have been used for Tor performance analysis. The majority of authors performed throughput and latency analysis.

Link-Quality Aware Path Selection in the Presence of Proactive Jamming in Fallible Wireless Sensor Networks

In this paper, we propose a mechanism to ensure the proper functioning of a wireless sensor network (WSN) in the presence of static and proactive jammer within the network. Existing research works have primarily focused on the detection of jammer node within the network and ameliorating its consequent effects on the network. However, these countermeasures to mitigate the effect of the jammer suffer from certain limitations as WSNs are primarily resource constrained and most of the countermeasures are computationally intensive. The objective of this paper is to prevent the disruption of the network in the presence of jamming by bypassing the jammed zone and setting up alternative paths. The alternative paths are chosen with the maximum link quality in order to maintain the quality of service of the network even after jamming. This paper proposes Link-quality Aware Path SElection ( LAPSE ) algorithm that chooses alternative paths based on the optimal link quality. LAPSE is based on optimal decision rule and its design considers the fallible nature of the nodes while choosing/rejecting a particular link. Finally, the performance of the proposed algorithm, LAPSE, is evaluated in terms of the network parameters—packet delivery rate, network throughput, transmission energy, node lifetime, and network lifetime. Results indicate that the performance of LAPSE is significantly better than the existing jamming avoidance algorithms.

Utilization of compact genetic algorithm for optimal shortest path selection to improve the throughput in mobile Ad-Hoc networks

In MANET, throughput of the network depends on the route selected between the source node and the destination node with the minimum distance. In the existing research work TSS algorithm is proposed for secured energy efficient data transmission in WSN. But it is not efficient in delay. In order to increase the efficiency in delay, compact genetic algorithm based shortest path selection is applied. The internal operations of the compact genetic algorithm improve the shortest path computation and selection. This is a probabilistic model called compact GA that receives learning models has input and provides new solution. The simulation results are compared with the existing approaches like TSS, dijkstra’s and optimal cost weight algorithm to evaluate the performance of the proposed approach in terms of objective function values, population size, path cost, computation time, throughput,and packet delivery ratio.

PSA-HD: Path Selection Algorithm based on Hamming Distance to Enhance the Link Stability in Mobile Ad-hoc Networks

PSA-HD: Path Selection Algorithm based on Hamming Distance to Enhance the Link Stability in Mobile Ad-hoc Networks

Intelligent Path Selection in Wireless Networks using Jaya Optimization

In this work, routing and mobility problems are addressed using a new Jaya Optimization Algorithm for Intelligent path selection in networks. In general, mobile nodes (MNs) are connected via wired mode or wireless mode. But in Mobile ad hoc network (MANET) MNs connected through wireless mode because nodes do not have an access point. Devices can be connected each other called as infrastructure less network whereas infrastructure based network devices can be connected through without any access point. The prevalent challenge of this network is mobility and routing. Mobility is processes of nodes are moving from one location to another location. A new Jaya Optimization algorithm is compared with other well-known mobility models like Random Waypoint, Random Direction, and Random Walk model. Also, in this study routing protocols were examined here. Furthermore, the performance results reveal that Jaya algorithm gives better results when compared with others in terms of Packet Delivery Ratio, Average Delay, Throughput and Routing Overhead.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols.

The strategy of path determination and traffic scheduling in private campus networks based on SDN

Important businesses in private campus networks need sufficient bandwidth to guarantee their quality of service. Setting port queues ignores the possibility of total bandwidth requirement exceeding the link capacity while OpenFlow-based path-planning with bandwidth guarantee (OPPBG) algorithm cannot guarantee bandwidth for multiple businesses with different requirements. We propose an improved path determination and traffic scheduling strategy based on Software Defined Networking (SDN). This method firstly obtains an ideal path for each flow by optimizing the path selection algorithm, and then sets port queues on switches along the path. The experiment compares the proposed algorithm with queue-setting method and OPPBG algorithm using four scenarios respectively. The results show that our strategy can meet the bandwidth requirements of each business, prevent them from interrupting others and improve the network’s performance and robustness.

Learning automata-based trust model for user recommendations in online social networks

Nowadays, most of the online social media websites provide recommendations as service for selective decision making. Determining a recommended trust path based on the consumer’s non-functional requirements, such as availability of the products, delay for computing recommendations and response time for a good recommendation is one of the challenging issues in online social networks. In this paper, we first design a recommendation-based online social network architecture by incorporating trust information (namely, direct trust and indirect trust), relevance degree and recommended influence value. We propose a high quality of social trust associated model for evaluating a recommended trust path. The proposed model estimates utility values with associated weights based on Shannon entropy information gain. Further, for best recommended trust path selection, we propose a Learning Automata based Recommended Trust Path Selection (LA-RTPS) algorithm to identify multiple recommended trust paths and to determine an aggregate path. The experimentation using real time datasets illustrates the efficacy of the proposed algorithm.

A multi-hop relay path selection algorithm considering path channel quality and coordinating with bandwidth allocation

A multi-hop relay path selection algorithm considering path channel quality and coordinating with bandwidth allocation

A multi-hop relay path selection algorithm considering path channel quality and coordinating with bandwidth allocation

Many multi-hop relay path selection algorithms were proposed. However, these algorithms do not consider the channel condition of the overall path and coordinate with the bandwidth allocation algorithm. In this paper, we proposed a greedy based multi-hop relay path selection algorithm considering channel quality and available bandwidth of overall path to provide high throughput in varying channel conditions. From the simulation results, our proposed algorithm actually provides higher throughput and outperforms the previous works.

A HEURISTIC APPROACH TO SECURE MOBILE AD-HOC NETWORK

An Ad Hoc[1] network is a gathering of wireless mobile nodes framing a transitory network without the aid of any centralized administration or standard support services. The topology of the ad hoc network may change rapidly and unexpectedly. One of the most problems encountered in these networks, is finding the optimization path between source and destination nodes within a specified time with minimum energy consumption. As energy and bandwidth is the main constrains in MANET so there is no requirement to pass the information through all nodes. Only the required nodes take part in communication. In this paper a swarm algorithm to find the optimal route is presented which automatically makes the network secure and more efficient. The proposed work is inspired by the path selection algorithm. The proposed work considers various parameters such as Distance, consumed energy, delay, time etc to solve routing problem. Simulation results are carried out for both algorithms using MATLAB. The results are shows in the graphical as well as in tabular forms.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors.

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs’ traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs’ paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay.

An adaptive and diversified vehicle routing approach to reducing the security risk of cash‐in‐transit operations

We consider the route optimization problem of transporting valuables in cash‐in‐transit (CIT) operations. The problem arises as a rich variant of the capacitated vehicle routing problem (CVRP) with time windows and pickup and deliveries. Due to the high‐risk nature of this operation (e.g., robberies) we consider a bi‐objective function where we attempt to minimize the total transportation cost and the security risk of transporting valuables along the designed routes. For risk minimization, we propose a composite risk measure that is a weighted sum of two risk components: (i) following the same or very similar routes, and (ii) visiting neighborhoods with low socio‐economic status along the routes. We also consider vehicle capacities in terms of monetary value carried as per insurance regulations. We develop an adaptive randomized bi‐objective path selection algorithm that uses the composite risk measure in choosing alternative paths between origin‐destination pairs over a sequence of days. We solve the rich CVRP approximately for each day with updated costs. We test our solution approach on a data set from a CIT delivery service provider and provide insights on how the routes diversify daily. Our approach generates a spectrum of solutions with cost‐risk trade‐off to support decision making. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 69(3), 256–269 2017

Cross-layer energy efficient protocol for QoS provisioning in wireless sensor network

Ensuring (QoS) in wireless sensor networks (WSNs) is a challenging issue due to the lack of resources and energy exhausting of sensor nodes. In this paper we propose a new QoS aware routing protocol for multi-hop wireless sensor networks based on cross-layer interaction between the network, MAC and physical layers. At physical layer, a link quality estimator is studied for the purpose of evaluating link quality. At MAC layer, a differentiated services mechanism is used to distinguish between real time and non-real time packets and to allocate more channel resources for real time traffic; TDMA slots also have been modified to allocate more and earlier slots to real time packets. At network layer, a routing path selection algorithm is introduced for QoS optimisation. Simulation results show that our proposed protocol improves network's performances in terms of energy efficiency and QoS.