Rendezvous Point Research Articles

RBDMS: Rate-Adaptation and Buffer-Awareness Data Gathering for Mobile Sink Scheduling in WSNs

Employing a mobile sink (MS) to act as a relay node in wireless sensor network (WSN) applications is a promising solution for efficient power saving and data collection. However, establishing long-distance traveling leads to larger latency or inefficient buffer management at rendezvous points (RPs), e.g., flying UAVs in disaster management. Moreover, there is no efficient solution to guarantee the completeness of data gathering by considering the waiting time (sojourn) of the MS to receive packets from RPs in addition to the MS moving time among RPs. This work presents a rate-adaptation and buffer-awareness data gathering for MS scheduling (RBDMS) by constructing grid cells in the monitoring area. In fact, it establishes the shortest path by passing within the communication range of the sensors based on data volume. RBDMS not only has a mechanism for handling emergency packets with low latency but also benefits from stochastic integer programming (SIP) for scheduling the MS sojourn time with lower computational time using Lagrangian relaxation. Simulation results confirm that the proposed RBDMS outperforms comparable state-of-the-art works in terms of the MS path length, network lifetime, the energy consumption of sensors, and MS, as well as buffering performance.

A Novel Clustering Strategy-Based Sink Path Optimization for Wireless Sensor Network

To optimize the path of mobile sinks in the wireless sensor network (WSN) and use of 5G signals to transmit information, a new clustering strategy is proposed, which not only balances the number of cluster nodes but also shortens the path of mobile sinks. By moving rendezvous points (RPs) to change the cluster position, we first propose a metaheuristics clustering algorithm named the dynamic clustering-based rectangular evolutionary algorithm (DCREA). The algorithm adjusts the clustering structure of the network by limiting the cluster movement range; then, it is optimized in combination with the greedy algorithm. Extensive experimental results show that this method can significantly shorten the path of the mobile sink, increase the efficiency of the mobile sink, and improve the quality of signal transmission while maintaining the balance of the cluster structure. The experimental results show that the DCREA is the most effective and indicate the effectiveness of the algorithm by comparing it with related recent algorithms.

On the Scheduling of Conflictual Deliveries in a last-mile delivery scenario with truck-carried drones

In this paper, we investigate the symbiosis between a truck and multiple drones in a last-mile package delivery scenario, introducing the Scheduling Conflictual Deliveries Problem (SCDP). From the main depot, a truck takes care of transporting a fleet of drones that will be used to deliver packages to customers. The route of the truck is predefined. Each delivery is associated with the energy cost of a drone, a reward that characterizes the priority of the delivery, and an interval between two points of the truck’s route: the point from which the drone departs (launch point) and the point at which the drone returns to the truck (rendezvous point). The objective of the SCDP is to find a scheduling for the drones that maximizes the overall reward subject to the drone’s battery capacity while ensuring that the same drone performs deliveries whose delivery intervals do not intersect. After showing that SCDP is an NP-hard problem, we devise an Integer Linear Programming (ILP) formulation for it. Furthermore, we devise a pseudo-polynomial time optimal algorithm for the single drone case and additional approximation algorithms for both the single and multiple drones case. Finally, we thoroughly compare the performances of our presented algorithms on different synthetic datasets.

EE-MSWSN: Energy-Efficient Mobile Sink Scheduling in Wireless Sensor Networks

Data gathering using mobile sink (MS) based on rendezvous points (RPs) is a need in several Internet of Things (IoT) applications. However, devising energy-efficient and reliable tour planning strategies for MS is a challenging issue, considering that sensors have finite buffer space and disparate sensing rates. This is even more challenging in delay-tolerant networks, where it is more desirable to select the shortest traveling path. There exist several algorithms on MS scheduling, which are based on hierarchical protocols for data forwarding and data collection. These algorithms are lacking efficient tradeoff between the Quality-of-Service (QoS) requirements in terms of energy efficiency, reliability, and computational cost. Besides, these algorithms have shown high packet losses while jointly performing MS tour planning and buffer overflow management. To address these limitations, we propose EE-MSWSN, an energy-efficient MS wireless sensor network that reliably collects data by implementing efficient buffer management. It forms novel clustered tree-based structures to cover all the network, and select each RP based on 1) hop count; 2) number of accumulated data in each clustered tree; and 3) distance to the stationary sink. The extensive simulation results verify that the EE-MSWSN minimizes tour length for various network configurations and incurs less energy consumption while reliably gathering data without packet losses as compared with existing protocols.

Introduction of a Method Using GIS to Generate Rendezvous Areas for Mobile Sinks in WSNs

This paper proposes an algorithm to change the concept of rendezvous points (RPs), which have been commonly used in mobile sink routing problem of wireless sensor networks (WSNs) to rendezvous areas (RAs) and to generate RAs by using geographic information system (GIS) tools. With the traditional RPs, a mobile sink must have visited the points, and possible deviations from the points would cause the mobile sink difficulty finding exact locations to collect data. However, with suggested RAs, the mobile sink is capable of receiving data from sensor nodes in an RA by visiting any points within the RA. It also reduces the traveling distance of the mobile sink, thereby prolonging its lifetime. With appropriate extensions with GIS tools, the algorithm can generate 3D RAs, which can be simulated in more realistic environments.

An efficient data collection algorithm for partitioned wireless sensor networks

Data collection with mobile agent (MA) can balance the energy consumption of nodes in partitioned wireless sensor networks. However, the existing data collection algorithms for partitioned WSNs do not formalize the problem systematically. These algorithms are not efficient and difficult to meet the timeliness requirement. In order to solve the above shortcomings, we first formalize the Data Collection Problem (DCP). Then, it is transformed into a Generalized Traveling Salesman Problem (GTSP), and we propose a GTSP-Based data collection Algorithm (GBA) to calculate the rendezvous points (RPs) and the moving path of MA. GBA selects RPs by solving the GTSP problem. Furthermore, based on GBA, we take advantage of constructing convex hull to plan a more efficient moving path for MA. In addition, in order to reduce the energy burden on the RPs, we design an Improved Shortest Path tree (ISP tree) to aggregate data from nodes to RPs in partitioned WSNs. Finally, extensive simulations demonstrate the effectiveness and advantages of our algorithm in terms of the length of MA’s moving path and the amount of data collection per unit time.

Analysis rendezvous-based techniques relate to power conservation

Power conservation is a vibrant area of research on wireless sensor networks. Several research papers have shown that using mobile sync in the sensor field, which collects data from sensor nodes via single or multi-hop communication, can save significant energy. However, sinks move slowly, which increases sensor network delays, especially in delay-sensitive applications. To address this issue, various rendezvous-based techniques are described in which a subset of sensor nodes are selected from the field as rendezvous points (RPs). The remaining nodes transfer the captured data to the next RP, where the data is buffered. The RP is then used to build a path for the mobile sink to tour and collect the buffered data. This article describes various rendezvous-based techniques and analyzes their strengths and weaknesses in terms of energy savings.

Dual-target Signal Simulation of Very Long baseline Interferometry for Chang’E-5

Very long baseline interferometry (VLBI) is an important deep-space tracking technology from radio astronomy. A mission that uses VLBI, China’s lunar sample-return mission Chang’E-5 (CE-5) collects soil samples on the lunar surface, arrives at a rendezvous point, and docks in the lunar orbit through cooperation of the Orbiter and the Ascender. During rendezvous and docking, the Chinese VLBI network (CVN) used same beam VLBI (SBI) to observe two high-velocity probes simultaneously. However, before the launching of the CE-5, CVN lacked the capability to examine dynamic dual-target tracking ability of SBI mode because there were no similar space probes can be used in tests of upgraded VLBI data-processing system. This study proposes a method to simulate VLBI signals and acquire relevant data from the dual-target probe and calibration quasar signals recorded by each station according to the orbits and beacons of probes, station coordinates, etc. The real-time data-processing capability of the system is verified by processing the simulated data during rendezvous and docking. The consistency between simulation and VLBI data-processing was consistent to better than 0.05 ns. This method is universal and can also be used in VLBI simulation and orbital analysis of other deep-space probes.

ANALYSIS RENDEZVOUS-BASED TECHNIQUES RELATE TO POWER CONSERVATION

Power conservation is a vibrant area of research on wireless sensor networks. Several research papers have shown that using mobile sync in the sensor field, which collects data from sensor nodes via single or multi-hop communication, can save significant energy. However, sinks move slowly, which increases sensor network delays, especially in delay-sensitive applications. To address this issue, various rendezvous-based techniques are described in which a subset of sensor nodes are selected from the field as rendezvous points (RPs). The remaining nodes transfer the captured data to the next RP, where the data is buffered. The RP is then used to build a path for the mobile sink to tour and collect the buffered data. This article describes various rendezvous-based techniques and analyzes their strengths and weaknesses in terms of energy savings.

Analysis rendezvous-based techniques relate to power conservation

Power conservation is a vibrant area of research on wireless sensor networks. Several research papers have shown that using mobile sync in the sensor field, which collects data from sensor nodes via single or multi-hop communication, can save significant energy. However, sinks move slowly, which increases sensor network delays, especially in delay-sensitive applications. To address this issue, various rendezvous-based techniques are described in which a subset of sensor nodes are selected from the field as rendezvous points (RPs). The remaining nodes transfer the captured data to the next RP, where the data is buffered. The RP is then used to build a path for the mobile sink to tour and collect the buffered data. This article describes various rendezvous-based techniques and analyzes their strengths and weaknesses in terms of energy savings.

Linear optimization model for mobile cluster heads to improve the lifetime of sensor network

Mobile elements are used in wireless sensor network to increase the longevity of network by minimizing the overloading of one hop sensors. Mobility has proven very useful in reducing the formation of energy holes by balancing the load among all the sensor nodes. The paper proposes exploiting mobile cluster heads to move along a predetermined trajectory to collect data. As autonomous moving strategies impose heavy overhead and data latency issues, predetermined trajectories have proven successful in improvising the lifespan of network. The contributions of the paper are twofold. First we have proposed a predetermined trajectory model along with a cluster formation procedure for the cluster heads to involve in data collection. The cluster heads stop for a fixed time duration “t” at each rendezvous point for data collection. Second, we have proposed a mathematical formulation to optimize the sojourn time duration of thecluster head based on the one hop residual energy of the sensornodes.

Minimum disturbance control based on synchronous and adaptive acceleration planning of dual-arm space robot to capture a rotating target

PurposeThis study aims to design a controller which can improve the end-effector low-frequency chattering resulting from the measurement noise and the time delay in the on-orbit tasks. The rendezvous point will move along the rendezvous ring owing to the error of the camera, and the manipulators’ collision need be avoided. In addition, owing to the dynamics coupling, the manipulators’ motion will disturb the spacecraft, and the low tracking accuracy of the end-effector needs to be improved.Design/methodology/approachThis paper proposes a minimum disturbance controller based on the synchronous and adaptive acceleration planning to improve the tracking error and the disturbance energy. The synchronous and adaptive acceleration planning method plans the optimal rendezvous point and designs synchronous approaching method and provides an estimation method of the rendezvous point acceleration. A minimum disturbance controller is designed based on the energy conservation to optimize the disturbance resulting from the manipulator’s motion.FindingsThe acceleration planning method avoids the collision of two end-effectors and reduces the error caused by the low-frequency chattering. The minimum disturbance controller minimizes the disturbance energy of the manipulators’ motion transferred to the spacecraft. Experiment results show that the proposed method improves the low-frequency chattering, and the average position tracking error reduces by 30%, and disturbance energy reduces by 30% at least. In addition, it has good performances in the synchronous motion and adaptive tracking.Originality/valueGiven the immeasurability of the target satellite acceleration in space, this paper proposes an estimation method of the acceleration. This paper proposes a synchronous and adaptive acceleration planning method. In addition, the rendezvous points are optimized to avoid the two end-effectors collisions. By the energy conservation, the minimum disturbance controller is designed to ensure a satisfying tracking error and reduce the disturbance energy resulting from the manipulators’ motion.

An Enhanced Sparrow Search Based Adaptive and Robust Data Gathering Scheme for WSNs

Wireless Sensor Networks based on Mobile Sinks (MS) are becoming more popular because of their benefits in enhancing performance and minimizing unequal energy usage of the nodes. While several MS data gathering methods have been proposed, most of them are less adaptive to changes in network topology and fails to modify the MS path suitably in response to node failures. Also, it is difficult to plan an efficient path for data gathering by MS using a set of Rendezvous Points (RPs) that could reduce the MS travel time while reducing the WSN energy usage. In this paper, we propose an Enhanced Sparrow Search based Adaptive and Robust Data Gathering Scheme for WSNs (ESRP-MP) to create shorter travel route for MS and minimize data gathering latency. For effective utilization of RPs, the best RP locations that maximize the coverage of nodes and minimize the overlap in coverage with adjacent RPs are considered. Also, the algorithm is adaptive to node failures by updating the RPs and refining the planned MS path when necessary. In the first phase, we introduce an enhanced Sparrow Search based algorithm to select a set of RPs that maximizes the coverage of nodes and minimizes the overlap in RP coverage. Then, the shortest tour through the RPs is obtained using Ant Colony Optimization (ACO). The results reveal the effectiveness of ESRP-MP against other related approaches in terms of number of RPs, data gathering time, MS path, energy utilization and network lifetime.

An Improved Approach for Wireless Sensor Networks With Mobile Sink Using Dynamic Minimum Spanning Tree

In wireless sensor networks (WSNs), finding the best transmission route from each node to the mobile sink is not a simple task because of the dynamic characteristics of sink node and cluster transmission. In order to balance energy consumption and reduce collisions in wireless transmissions, this paper proposes a Dynamic Spanning Tree with Mobile Sink (DSTMS) routing algorithm. Firstly, based on the Low Energy Adaptive Clustering Hierarchy Protocol (LEACH), a multi-layer transmission framework with dynamic minimum spanning tree (MST) is constructed to optimize data transmission route. In this framework, the selected rendezvous points, according to the motion parameters of mobile sink, build the dynamic rendezvous layer to constraint the hierarchical transmission of DSTMS. In addition, considering some factors of transmission energy consumption and residual energy distribution,the weight factor based on energy efficient function is introduced to evaluate the cost of transmission path within the MST. Moreover, the proposed algorithm not only reduces network energy consumption caused by frequent location updates of mobile sink, but also reduces data transmission congestion by constructing dynamic hierarchical transmission strategy. The simulation results show that the DSTMS algorithm can effectively prolong the network life, balance the network load and reduce collisions in wireless transmissions.

Bogor Message and Wasatiyyat Islam: Reviving Islamic Diplomacy and Constituting the Transnationalism of Islam

Bogor Message is constituting the transnationalism of Islam and reviving the importance of diplomacy based on religious consultation or even multilateralism, that concluded by prominent Islamic scholars (ulama) in the world through High-Level Constitution of World Muslim Scholars in 2018. Thus, Bogor Message is considered a form of ijma’ ulama (consensus among Islamic scholars) which will be useful for Muslim ummah (Islamic society) as a common ground depicting universal norm in regulating the attitude toward international relations (IR). Wasatiyyat Islam summed up in the Bogor Message, is the embodiment of Islamic tradition in the multi-track diplomacy where interactions between state-actors and non-state actors and utilization of tracks in diplomacy resulted in an understanding to solve ummah fundamental problems in Islamicate world through the normative religious approach. The Bogor Message is rendezvous point and unified the differences of Wasatiyyat Islam conception aimed to unite ummah in the framework of transnational Islam, taken from Al-Qur’an and Sunnah. This research article examines the principle of Wasatiyyat Islam inside Bogor Message and its functionality as soft power by using diplomacy theories. The lack of concern from ummah in other countries due to the outbreak of COVID-19 pandemic hampered the progress of Wasatiyyat Islam dissemination and remained exclusive for certain bastions of ‘moderate Islam’ countries. Though the potencies for developing and globalizing Wasatiyyat Islam could gain momentum in the post-COVID-19 world.

Energy-Efficient Mobile Sink-Based Intelligent Data Routing Scheme for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have become an indistinguishable part of any Internet of Things (IoT) based system. In an IoT-based system, WSN monitors different physical objects and forwards the collected data to the base station or gateway node for further processing. Existing routing protocols designed for WSNs are not suitable for IoT-based systems. An intelligent and high-performance routing protocol is essential for real-time data analysis and decision-making. Therefore, this paper proposes a mobile sink-based intelligent data routing scheme for WSNs. Initially, Particle Swarm Optimization is used for optimal cluster formation. After cluster formation, the optimal number of rendezvous points are selected, and a data-gathering tour is planned for the mobile sink. Furthermore, a mobile sink-based intelligent data gathering scheme is proposed to collect the data from the cluster heads. Extensive simulations and mathematical analysis are performed to verify the effectiveness of the proposed scheme. The simulation results are compared with state-of-the-art algorithms in terms of stability period, network lifetime, throughput, average energy consumption, fairness index, data transmission latency, and message overhead.

Uninterrupted path planning system for Multi-USV sampling mission in a cluttered ocean environment

This paper presents an uninterrupted collision-free path planning system that facilitates the operational performance of multiple unmanned surface vehicles (USVs) in an ocean sampling mission. The proposed uninterrupted path planning system is developed based on the integration of a novel B-Spline data frame and particle swarm optimization (PSO)-based solver engine. The new B-spline data framing structure provides smart sampling of the candidate spots without needing full stop for completing the sampling tasks. This enables the USVs to encircle the area smoothly while simultaneously correcting the heading angle toward the next spot and preventing sharp changes in the vehicle's heading. Then, the optimization engine generates optimal, smooth, and constraint-aware path curves for multiple USVs to conduct the sampling mission from start point to the rendezvous point. The path generated incorporates controllability over the vehicles' velocity profile to prevent experiencing zero velocity and frequent stop/start switching of the controller. To achieve faster convergence of the optimization routine, a suitable search space decomposition scheme is proposed. Extensive simulation studies emulating a realistic ocean sampling mission are conducted to examine the feasibility and effectiveness of the proposed path planning system. This encapsulates modelling a realistic maritime environment of Indonesian Archipelago in Banda Sea including ocean waves, obstacles, and no-fly zones and introducing several performance indices to benchmark the path planning system performance. This process is accompanied by a comparative study of the proposed path planning system with a well-known state-of-the art piecewise, rapidly exploring random tree (RRT), and differential evolution-based path planning algorithms. The results of the simulation confirm the suitability and robustness of the proposed path planning system for the uninterrupted ocean sampling missions.

Security enhanced optimal trajectory selection for mobile sink using reinforcement learning

Wireless visual sensor networks (WVSNs) have emerged as a strategic inter disciplinary category of WSN with its visual sensor based intelligence that has garnered considerable attention. The growing demand for energy efficient and maximized life time networks in highly critical applications like surveillance, military and medicine has opened up more prospects as well as challenges in the deployment of WVSNs. Multi-hop communication in WVSN results in overloading of intermediate sensor nodes due to its dual function in the network which results in hotspot effect. This can be mitigated with the help of mobile sinks and rendezvous points based route design. But mobile sinks has to visit every cluster head to gather data which results in longer traversal path and higher latency and power consumption related issues if not addressed properly will impact the performance of the network. Our objective is to analyze and determine the optimal trajectory for mobile sink node traversal with the help of a high quality transmission architecture integrated with reinforcement learning and isolation forest based anomaly detection to propose an energy efficient meta-heuristic approach to enhance the performance of network by reducing the latency and securing the network against possible attacks.

A Novel Efficient Data Gathering Algorithm for Disconnected Sensor Networks Based on Mobile Edge Computing

Employing mobile elements is an efficient solution to the performance improvement of wireless sensor networks (WSNs). We propose an efficient data gathering mechanism for disconnected WSNs with rendezvous points (DGM-RPs). The mobile sink traverses the entire network and stops only at the rendezvous points (RPs) while gathers the data from sensors in every disconnected segment. In this paper, mobile sinks perform the task of edge computing and alleviate the load of upper cloud. We measure the shape of disconnected segments, layering them by use of the convex hull, and then design the travelling path of the mobile sink to minimize the travel latency to visit all disconnected segments. At least one RPs will be selected in a segment firstly, and then, on this basis, we consider the distribution density of sensor nodes and the location of the RPs already exist to adding new RPs, which make good use of the margin to reducing the energy consumption and prolong the network lifetime.

M-Emu: A Platform for Multicast Emulation

Network layer multicast research is an important field of network research that requires simulators or emulators to support Software-Defined Networking (SDN) as well as to provide a specific structure at the network layer to facilitate packet forwarding, such as a multicast tree. The existing emulation platforms cannot effectively support the emulation of certain key multicast technologies, such as the Grafting Point (GP)-selection method and Rendezvous Point (RP)-selection method, for the following reasons: First, the programmable data plane of the existing emulation platform has many defects, such as the inability to process packet scheduling tasks, the prohibition of dynamic memory allocation and loops with unknown iteration counts, which make it difficult to deploy complex multicast protocols and algorithms. Secondly, at present, no emulation platform integrates network layer multicast emulation functions. As a result, users need to develop the multicast tree construction and maintenance mechanism in advance, which makes experiments laborious. To solve the above problems, based on NS4, we designed a multicast emulation platform, M-Emu. M-Emu presents a Service-Forwarding Architecture, which enables the data plane to deploy arbitrary complex protocols and algorithms. Based on the Service-Forwarding Architecture, M-Emu integrates a Multicast-Emulation Framework, which has a complete multicast tree construction and maintenance mechanism. We explain in detail how the various parts of M-Emu cooperate to complete the multicast emulation with an example and prove that M-Emu is efficient in CPU and memory consumption, etc., through a large number of experiments.