Autoregressive Integrated Model for Time Synchronization in Wireless Sensor Networks

Most wireless sensor networks (WSNs) employ a sleep clock to enable sensor on-off mode to save energy. Since the sleep clock usually works at a relatively low frequency, it is important to correct the long-term synchronization error caused by instability and nonlinearity. In this paper, the time synchronization issue in a WSN is formulated as a closed-loop control problem. Using the proportional-integral (PI) control principle, we propose a feedback-based synchronization (FBS) scheme to compensate the clock drift caused by both internal perturbation and external disturbance. Synchronization accuracy and FBS dynamics are analyzed in terms of response time and overshoot. We also derive a formula to determine the controller parameters for different synchronization accuracy and response-time requirements. Extensive experiments have been conducted to evaluate this synchronization scheme. The results indicate that FBS is much more robust than the delay measurement time-synchronization (DMTS) protocol in different synchronization durations and sensor node configurations. It is shown that FBS achieves almost the same accuracy as the flooding time-synchronization protocol (FTSP) when synchronization period P is less than 60 s, and it outperforms FTSP when P is longer than 60 s. Furthermore, the experimental results reveal that FBS's response to an external disturbance is faster than that of FTSP in one- or two-hop WSN scenarios. In addition, FBS consumes fewer resources than FTSP.

Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.

This research focuses on the implementation and evaluation of the Flooding Time Synchronization Protocol (FTSP) in a Wireless Sensor Network (WSN) using a Star topology based on the ESP-NOW communication protocol. The study aims to assess the protocol's ability to achieve accurate time synchronization while considering the impact of clock drift. Five NodeMCU ESP8266 devices were employed, with one node as the root and four nodes as receivers. The protocol's performance was evaluated in terms of offset values between receiver local time and root time, both before and after considering clock drift, with measurements conducted in microseconds. The results highlight a consistent reduction in offsets post-synchronization, showcasing the protocol's efficiency in aligning local times. Statistical measures further confirm the protocol's reliability, as offset values converge around calculated averages. The research findings suggest the efficacy of FTSP in maintaining synchronization accuracy within WSNs, motivating further real-world evaluations and investigations into resource optimization.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

A wireless sensor network is a special kind of ad-hoc network with distributed sensing and processing capability that can be used in a wide range of applications, such as environmental monitoring, industrial applications and precision agriculture. Despite their potential applications, such networks have particular features imposed by resource restrictions, such as low computational power, reduced bandwidth and specially limited power source. In case of a network with a high density of sensor nodes, some problems may arise such as the intersection of sensing area, redundant data, communication interference, and energy waste. A management application is necessary to make the most of network resources. On the other hand, a high-density network can introduce a fault-tolerant mechanism, increase precision, and provide multi-resolution data. The network density control depends on the application. In this paper, we propose a method to set up which nodes should be turned off or on. The management may take the sensor node out of service temporally. Our design uses a Voronoi diagram, which decomposes the space into regions around each node. That schema could be used in management architecture for a wireless sensor network.

Wireless sensor network WSN consists of small sensor nodes with limited resources, which are sensing,
 gathering and transmitting data to base station. Sensors of various types are deployed ubiquitously and widely in varied
 environments for instance, wildlife reserves, battlefields, mobile networks and office building. Sensor nodes are having
 restricted and non replenishable power resources and this is regarded as one of the main of their critical limits. All
 applied techniques and protocols on sensor nodes must take into consideration their power limitation. Data aggregation
 techniques are used by sensor nodes in order to minimize the power consumption by organizing the communication
 among sensor nodes and eliminating the redundant of sensed data. This paper proposed lightweight modification on data
 aggregation technique named Energy Aware Distributed Aggregation Tree EADAT. The main principle of this
 development is using the available information in sensor nodes to pass the role of parent node among sensor nodes in
 each cluster. The process of passing parent node role is based on nominating the sensor nodes which have higher power
 on regular bases. A model based on tree network architecture is designed for validation purpose and is used with NS2
 simulator to test the proposed development. EADAT and EADAT with proposed development are applied on the designed
 model and the results were promising

Wireless Sensor Network (WSN) is a wireless network that involves sensors in the network. The sensor node on the WSN will collect data information from the environment around the sensor. However, each sensor node has storage capacity, processing power, communication range, and battery life limitations. The use of energy consumption from these factors is the main problem because each sensor node uses its power consumption from the battery. Stable Election Protocol (SEP) is a type of routing protocol on WSN that uses the clustering method. SEP has a function to extend the time interval before the first node dies. This research was carried out on the SEP protocol with alive node parameters, total initial energy, and stability. This study indicates that on a network that uses 100 nodes with sink positions (0, 100), two nodes are still alive and several nodes that are still alive in several sink positions that use 200 nodes. For networks where there is still a lot of energy remaining in the sink position (0, 100) with the network using 100 nodes and for networks using 200 nodes, the remaining energy is mainly in the sink position (100, 100). The highest stability period is in the sink position (50, 50) for networks using 100 nodes, and for networks using 200 nodes, the highest stability period is in the sink position (100, 50).

Wireless networks play a crucial role in the communication systems nowadays. Wireless networks are being increasingly used in the communication among devices of the most varied types and sizes. User mobility, affordability, flexibility and ease of use are few of many reasons for making them very appealing to new applications and more users everyday. A Wireless Sensor Network (WSN) is composed of sensor nodes spread over the field to sense the data. The sensed data must be gathered & transmitted to Base Station (BS) for end user queries. The used sensor nodes being in- expensive having low computation power & limited energy so are not as much reliable as their expensive macro sensor counter parts but their size and cost enable hundred to thousand of micro sensors to achieve high quality fault tolerant system. In an environment where in each round all sensor nodes have to send data to base station; it is required to effectively utilize energy of sensor nodes so as to increase the life- time of the system. The use of data aggregation & fusion as proposed in LEACH increases system lifetime by a factor of 8 as compared to conventional routing protocols. In this work, our main focus is the static sensors are randomly selected and the base stations have their information all a priori. Basically, the sensors are in direct communication range of each other and can transmit to and receive from the base station. The nodes periodically sense the environment and have always data to send in each round of communication. The nodes fuse/ aggregate the data they receive from the others with their own data, and produce only one packet regardless of how many packets they receive. The problem is to find a routing scheme or an efficient protocol to deliver data packets collected from sensor nodes to the base station. It maximizes the lifetime of the sensor network under the system model given above. However, the definition of quality of service of the sensor network provides is not specified. Secondly, where the nodes are densely deployed, the quality of the system is affected as soon as a significant amount of nodes die, since adjacent nodes record identical or related data. In this case, the lifetime of the network is the time elapsed until half of the nodes or some specified portion of the nodes die. In general terms, the time in rounds where the last node depletes all of its energy defines the lifetime of the overall sensor network. Taking these different possible requirements under consideration, our work provides a proper timing of all deaths for all algorithms in detail as well as chooses the shortest possible path for communication with better memory management scheme and leaves the decision which one to choose to system designers.

Time synchronization for wireless sensor networks (WSNs) has been studied in recent years as a fundamental and significant research issue. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. Time synchronization in a WSN is critical for accurate time stamping of events and fine-tuned coordination among the sensor nodes to reduce power consumption. This paper proposes a bidirectional, reference based, tree structured time synchronization service for WSNs along with network evaluation phase. This offers a push mechanism for (i) accurate and (ii) low overhead for global time synchronization. Analysis study of proposed approach shows that it is lightweight as the number of required broadcasting messages is constant in one broadcasting domain.

Synchronization of tiny sensor nodes forming Wireless Sensor Networks (WSNs) is a challenging problem due to frequent topological changes, node failures and power, memory and computation constraints. These difficulties promote a self-organizing solution for the problem of time synchronization in WSNs to be quite desirable. Current self-organizing time synchronization protocols in WSNs have drawbacks: They either provide synchronicity but not a common notion of time for the nodes in the network or they demand keeping track of the time information of the neighboring nodes. The latter drawback becomes quite crucial especially on dense WSNs, which makes available self-organizing time synchronization protocols impractical. This paper provides a novel self-organizing time synchronization protocol for WSNs which does not require keeping track of the neighboring nodes. The main component of our protocol is a computationally light "adaptive-value tracking" algorithm which synchronizes the rate of each sensor node to that of all its neighboring nodes through successive feedbacks. We show by simulations that the proposed protocol achieves a tight synchronization which results in the desired property of global time notion after a finite amount of time on dense networks. Although there is no formal proof yet of the protocol's convergence, we anticipate this protocol could be used as a practical time synchronization approach.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Impact of time synchronization error on the mode-shape identification and damage detection/localization in WSNs for structural health monitoring

Time synchronization and node localization over a wireless sensor network (WSN) is a vital problem in applications such as Internet of Things (IoT) and context-aware pervasive systems. Addressing this problem leads to an efficient data fusion, power scheduling, bandwidth utilization, geographic routing, time-based channel sharing, and clustering among sensor nodes. In a WSN, sensor nodes utilize multi-hop data transmission model towards the data transfer. Utilization of large number of hops for the data transfer leads to poor time synchronization resulting in erroneous node location estimates. In this letter, we make use of a recent development in social networks termed as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">small world characteristics</i> and propose a novel method of time synchronized node localization over a small world WSN (SW-WSN). The results are obtained via simulations over a medium scale WSN. The performance of the proposed method is evaluated by conducting detailed analysis of time synchronization and node localization errors over the SW-WSN. The results obtained illustrate that the proposed small world model yields improved localization results when compared to results obtained over a regular WSN.

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.