Data Collection with Multiple Controlled Mobile Nodes in Wireless Sensor Networks

Data collection is a fundamental and important issue in wireless sensor networks (WSNs). Recent research has shown that using mobile nodes to collect and carry data in WSNs has many advantages over static multi-hop routing. In this paper, we focus on the problem of data collection in WSNs with the minimum mobile nodes. A mobile node can pick up the data cached in a sensor node via one-hop wireless communications when it passes by a point that R meters away from this stationary sensor node. Since the storage capability of sensor node is limited, each mobile node must visit the sensor nodes, that assigned to it, every t seconds to avoid the overflow of sensor data. In order to reduce the cost of mobile nodes, we try to minimize the number of mobile nodes. We formally prove that the problem of minimizing the number of mobile nodes required by periodical data collection in WSNs is NP hard. We propose a path planning algorithm to minimize the number of mobile nodes. Our simulation results show that our approach can notably reduce the number of required mobile nodes as much as 55.6%.

Environment physical parameters about the energy efficiency status in building can be monitored with wireless sensor network with mobile node. To reduce the cost and complexity of wireless sensor network, sweep coverage for wireless sensor network with mobile node is defined in this paper. To minimize the number of mobile nodes in desired wireless sensor network, the problem for minimum number of mobile nodes and a fast solution based on MTSP for the problem are presented. In our experiment, the MTSP problem is solved with PSO algorithm. Experimental results show that the fast solution based on MTSP can work correctly and quickly.

Wireless Sensor Networks (WSNs) is one of the most rapidly growing research domain.This is because of the development of sensor nodes with extremely low cost and the applications of such sensor nodes are ever growing.WSNs are group of sensor nodes with a set of processors and limited memory unit.Reliable routing of packets from sensor nodes to its base station is the most important task for these networks.Also mobility of the nodes is considered to be one major criterion for WSNs.In this paper, a dynamic routing algorithm called the Mobility Assisted Dynamic Routing (MADR) algorithm has been proposed for the mobile wireless sensor networking system, where both the base station and the sensor nodes are in moving condition.The cluster head selection is based on three parameters: the energy efficiency of the sensor nodes, the mobility of the sensor nodes and the accessibility to the neighboring sensor nodes.The concept of cluster head panel is applied additionally to minimize the re-clustering time.The proposed algorithm is compared with an existing algorithm Low Energy Adaptive Clustering Hierarchy (LEACH).The simulation results show an excellent prolongation in overall network lifetime.

Ultra-wideband (UWB) communications is receiving significant attention recently due to its high data rates and low power, low interference transmission. This paper considers the issue of utilizing these advantages of UWB to design improved Wireless Sensor Networks (WSNs). In particular, we consider data gathering in wireless sensor networks using a mobile node for data collection. We first propose a network architecture where a mobile node equipped with both a UWB transceiver and a narrowband RF transceiver is used to collect data from sensor nodes. The sensor nodes are equipped with a narrowband RF transceiver and only a UWB transmitter (not receiver). This approach is chosen to strike a balance between cost of each sensor node and speed of data transfer, since a UWB transmitter is much less complex and expensive than a UWB receiver. We then propose a mobile Data Gathering (DGR) algorithm to find a minimal set of points in the sensor network, which will serve as data gathering points for the mobile node. We use a Voronoi diagram of the network as a starting point, considering each sensor node in the network as a site in the Voronoi diagram and finnding points in the network where data from multiple sites (sensor nodes) can be collected. We then use a weight function designed to reduce the number of these data collection points, and generate a new smaller set of points, such that the mobile node can collect data from multiple sites from each such point. With the aid of a discrete-event simulation model, we show significant savings in the total time for data collection while providing a high level of network coverage.

In wireless sensor networks, due to the restricted battery capabilities of sensor nodes, the energy issue plays a critical role in network efficiency and lifespan. In our work, an upgraded long short‐term memory is executed by the base station to frequently predict the forecast positions of the node with the help of load‐adaptive beaconing scheduling algorithm. In recent years, new technologies for wireless charging have offered a feasible technique in overcoming the WSN energy dilemma. Researchers are deploying rechargeable wireless sensor networks that introduce high‐capacity smartphone chargers for sensor nodes for charging. Nearly all R‐WSN research has focused on charging static nodes with relativistic routes or mobile nodes. In this work, it is analysed how to charge nondeterministic mobility nodes in this work. In this scenario, a new mechanism is recommended, called predicting‐based scheduling algorithm, to implement charging activities. In the suggested technique, it directs them to pursue the mobile charger and recharge the sensor, which is unique for the present work. The mobile charger will then choose a suitable node, utilizing a scheduling algorithm, as the charging object. A tracking algorithm based on the Kalman filter is preferred during energy transfer to determine the distance needed for charging between the destination node & mobile charger. Here, the collecting & processing of data are performed through the big data collection in WSNs. The R‐WSN charging operations of nondeterministic mobility nodes will be accomplished using the proposed charging strategy.

Location-aided routing protocol (LAR) utilizes the position information for routing. This system is simulated position information in specific areas by using mobile nodes. Movement of hosts results in routes, requiring some mechanism for determining new routes. This system finds position information using Location aided routing algorithm between each nodes. In real application, mobile nodes can apply without time consuming and saving cost to get location information using wireless sensor network. Each of the nodes is involved with calculating its position. If the position information is searched in the routing protocol, then position-based routing protocol is used. After creating the position table, all mobile nodes can transmit 64B data within active mobile nodes via Base station. The algorithm is determined locations of nodes based on the connectivity for every node in specific area. This system is demonstrated location information by using Location-Aided Routing (LAR) protocol for route discovery. This system can assist to detect location of the specific areas using mobiles nodes. Simulation results are used to draw conclusions regarding to the proposed routing algorithm. The simulation of system is implemented mobile nodes and node movement function by using C# programming language.

Unnamed aerial vehicle (UAV) can be employed to collect sensed data from sensor nodes (SNs) in wireless sensor networks, thanks to its high mobility and great maneuverability. However, it is very challenging for one single UAV with limited energy storage to complete the data collection task while guaranteeing the information freshness of the SNs. In this work, we investigate the AoI-optimal data collection problem in multi-UAV-aided wireless sensor networks, where the SNs may be densely located and multiple UAVs with limited energy supply perform data collection collaboratively. In a dense network, the communication ranges of the SNs might overlap with each other, and there is no need for the UAVs to fly over the SNs one by one and collect their sensing data sequentially. Instead, some points can be selected as data collection points (CPs) at which the UAVs collect data from multiple SNs simultaneously. Accordingly, the multi-UAV-aided data collection problem can be decomposed into three parts. Firstly, the positions of the CPs are determined and the SN-CP association is established based on graph theory. Secondly, the CPs are clustered based on the kernel K-means method with each cluster of CPs being visited by one UAV. Thirdly, the optimal flight trajectory of each UAV is found to minimize the the SNs' maximal age of information (AoI) subject to the limited energy capacity. Simulation results validate the effectiveness of our proposed data collection scheme.

Wireless ad hoc networks are an emerging and popular technology to the world; however, the benefits of them are actually their fragility, too. Owing to mobile node movement, the link break problem always occurs in the network. The problem greatly influences the throughput, delay, jitter, and lots of performance issues of a routing protocol. Hence, this article is proposed to evaluate the influence of link break problem on two categories of most popular routing protocols, i.e. table-driven and on-demand routing protocols. This article briefly discusses the main differences, building up mathematical model, setting up simulation environment, running the simulation, and finally presenting the simulation results and analyzing the performance. We found that the update probability of table-driven routing protocols increase exponentially with the number of mobile nodes but linearly with moving speed. On the contrary, the update probability of on-demand routing protocol increase both linearly with the number of mobile nodes and moving speed. We conclude that the effect of link break problem on table-driven routing protocols is much serious than that on on-demand routing protocols since the former has to maintain each link of the network but the latter only the links of a specific route. Table-driven routing protocols are not scalable; however, on-demand routing protocols are.

Wireless sensor networks (WSNs) are used to collect large amounts of data over a wide area. However, the sensor nodes used in WSNs have a short lifespan because they are generally battery-operated. Research is actively underway to increase the lifespan of WSNs via techniques such as energy harvesting and wireless power transfer (WPT). This study proposes a scheme for clustering and adjusting the WSN data collection rate to alleviate the hotspot problem and improve network connectivity. The proposed scheme is targeted at WSNs in which the sensor nodes harvest solar energy. In addition, an unmanned aerial vehicle (UAV) traverses along a given path and delivers energy to sensor nodes using WPT, while collecting data as a sink node. In this scheme, the number of cluster heads is determined by considering the number of nodes at each hop distance and the maximum amount of data that can be transferred with the available energy. Further, sensor nodes limit the amount of data they collect to reduce the relay load on intermediate nodes. To achieve this, nodes consider the amount of data transferred by parent nodes, especially nodes in the hotspot, and the number of child nodes. The sink node traverses along a given path, and collects the data accumulated in the cluster head while supplying its remaining energy to the cluster head. The amount of energy it transfers is determined by considering the number of cluster heads. Consequently, nodes in the hotspot are prevented from becoming blacked out from a lack of energy, and the energy harvesting efficiency is increased. Simulation results indicate that the proposed scheme reduces the number of blackout nodes in the hotspot areas near cluster heads. Furthermore, the data collection and monitoring performance increases with the increase in network connectivity.

We present Sensei-UU, a testbed that supports mobile sensor nodes. The design objectives are to provide wireless sensor network (WSN) experiments with repeatable mobility and to be able to use the same testbed at different locations, including the target location. The testbed is inexpensive, expandable, relocatable and it is possible to reproduce it by other researchers. Mobile sensor nodes are carried by robots that use floor markings for navigation and localization. The testbed is typically used to evaluate WSN applications when sensor nodes move in meters rather than millimeters, eg. when human carries a mobile data sink (mobile phone) collecting data while passing fixed sensor nodes. To investigate the repeatability of robot movements, we have measured the achieved precision and timing of the robots. This precision is of importance to ensure the same radio link characteristics from one protocol experiment to another. We find that our robot localization is accurate to ±1 cm and variations in link characteristics are acceptably low to capture fading phenomena in IEEE 802.15.4. In the paper we show repeatable experiment results from three environments, two university corridors and from an anechoic chamber. We conclude that the testbed is relocatable between different environments and that the precision is good enough to capture fading effects in a repeatable way.

Mobility of sensor nodes in wireless sensor network (WSN) has posed new challenges particularly in packet delivery ratio and energy consumption. Some real applications impose combined environments of fixed and mobile sensor nodes in the same network, while others demand a complete mobile sensors environment. Packet loss that occurs due to mobility of the sensor nodes is one of the main challenges which comes in parallel with energy consumption. In this paper, we use cross layer design between medium access control (MAC) and network layers to overcome these challenges. Thus, a cluster based routing protocol for mobile sensor nodes (CBR-Mobile) is proposed. The CBR-Mobile is mobility and traffic adaptive protocol. The timeslots assigned to the mobile sensor nodes that had moved out of the cluster or have not data to send will be reassigned to incoming sensor nodes within the cluster region. The protocol introduces two simple databases to achieve the mobility and traffic adaptively. The proposed protocol sends data to cluster heads in an efficient manner based on received signal strength. In CBR-Mobile protocol, cluster based routing collaborates with hybrid MAC protocol to support mobility of sensor nodes. Schedule timeslots are used to send the data message while the contention timeslots are used to send join registration messages. The performance of proposed CBR-Mobile protocol is evaluated using MATLAB and was observed that the proposed protocol improves the packet delivery ratio, energy consumption, delay and fairness in mobility environment compared to LEACH-Mobile and AODV protocols.

이동 사용자의 위치 정보를 제공하는 위치인식서비스는 센서네트워크가 제공하는 대표적인 서비스이다. 그동안 이동 사용자의 위치정보를 획득하기 위한 다양한 기법들이 제시되어 왔다. 하지만 대부분의 기법들은 단일 사용자인 경우만 고려하여 연구되어 이를 다중 사용자인 경우로 확장하기에는 문제가 있다. 여러 이동 사용자들이 한 지역에서 동시에 위치인식 작업을 수행하는 경우에 센서노드들이 발생시키는 라디오 주파수나 초음파 등이 서로 간에 간섭을 발생시킬 수 있다. 본 논문에서는 여러 이동 사용자들이 동시 다발적으로 위치확인 작업을 수행하고자 하는 경우에 발생 가능한 간섭을 최소화 하는 적응적 파워 조절에 기반한 위치인식 기법인 APL(Adaptive Power Control based Resource Allocation Technique for Efficient Localization Technique)기법을 제안한다. APL기법은 센서노드가 위치인식 작업을 수행하기 전에 주위에 있는 앵커노드를 선점하여 점유함으로써 노드간의 간섭을 방지한다. 이를 위해 IEEE 802.11에 정의된 RTS(Ready To Send)패킷을 자원 선점을 요청하는데 사용하며 CTS(Clear To Send)패킷을 자원 선점을 확인하는데 사용한다. 반대로 이미 앵커노드가 다른 노드에 의해 선점하여 위치인식 작업을 방해할 가능성이 있는 경우 해당 앵커노드들을 임계영역으로 정의한다. 임계영역 처리를 위한 NTS(Not To Send) 패킷을 새로이 정의하여 노드 간에 간섭이 발생하지 않도록 한다. 추가적으로 거리측정 작업시 앵커노드간 동기화를 위한 STS(Start to Send)패킷을 새로이 정의한다. 최종적으로 센서노드의 전송 파워를 적응적으로 조절하여 작업이 영향을 미치는 영역을 최소화하도록 한다. 실험을 통하여 이동 사용자가 다수일 경우 노드 간에 간섭이 많이 발생함을 보이며 제안하는 APL기법이 위치인식 작업시 간섭을 방지함을 보인다. Given the increased interest in ubiquitous computing, wireless sensor network has been researched widely. The localization service which provides the location information of mobile user, is one of important service provided by sensor network. Many methods to obtain the location information of mobile user have been proposed. However, these methods were developed for only one mobile user so that it is hard to extend for multiple mobile users. If multiple mobile users start the localization process concurrently, there could be interference of beacon or ultrasound that each mobile user transmits. In the paper, we propose APL(Adaptive Power Control based Resource Allocation Technique for Efficient Localization Technique), the localization technique for multiple mobile nodes based on adaptive power control in mobile wireless sensor networks. In APL, collision of localization between sensor nodes is prevented by forcing the mobile node to get the permission of localization from anchor nodes. For this, we use RTS(Ready To Send) packet type for localization initiation by mobile node and CTS(Clear To Send) packet type for localization grant by anchor node. NTS(Not To Send) packet type is used to reject localization by anchor node for interference avoidance and STS(Start To Send) for synchronization between 모anchor nodes. At last, the power level of sensor node is controled adaptively to minimize the affected area. The experimental result shows that the number of interference between nodes are increased in proportion to the number of mobile nodes and APL provides efficient localization.

A wireless sensor network (WSN) consists of thousands of sensors and one base station. Sensors are deployed in the network to monitor target area and sense information according to the applied application then send this information to the base station. Adversary can inject false information in the network or compromise the routing information between nodes or between nodes and base station. Thus make the wireless sensor network secure is considered a very important issue. This paper introduces an authentication protocol and simple key distributed scheme between sensor nodes. Node mobility has been taken into consideration and the work proposes a re-authentication protocol that is very efficient than the initial protocol.

In mobility-centric environments, wireless sensor networks are designed to accommodate energy efficiency, dynamic self-organization and mobility. In typical applications of wireless sensor networks, fixed sensor nodes are mixed with mobile sensor nodes in "hot areas". Also, as they move, network topology needs to be reconstructed by reacting upon the mobility of sensor nodes quickly. In this paper we proposed an improved protocol called "LEACH-Mobile" for mobile nodes to declare the membership of a cluster as they move, and to confirm whether a mobile sensor node is able to communicate with a specific cluster head within a time slot allocated in TDMA schedule. The LEACH-Mobile protocol achieved definite improvement in data transfer success rate as mobile nodes increased compared to the non-mobility centric LEACH protocol

This study presents an energy-efficient location estimation method aimed for mobile nodes in wireless sensor networks. The proposed method is a combination of two operations. Trilateration method is combined with a vector based incremental updates which is implemented by using a digital compass and a speedometer to estimate the location of the mobile node. This combined operation decreases the power consumed from the mobile node trying to locate itself. The proposed method has been implemented on an arduino-based mobile robot with wireless communication peripherals. The implementation shows that the location estimation accuracy is between 0.69-1.97 m from the actual location of the mobile node. The average location estimation error is comparable to other proposed methods for locating mobile sensor nodes. Based on the actual measurement of the test system, the energy consumption of the proposed method is 20% less than the trilateration method alone.