Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

Accurate localization for mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. Also the proportion factor of distance is proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. And the normalized nearness degrees are considered as the weighted standards to calculate coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can timely localize the mobile node. The average localization error of PCFL can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table

Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks

International audienceLocalization is a fundamental issue for many applications in wireless sensor networks. Without the need of additional ranging devices, the range-free localization technology is a cost-effective solution for low-cost indoor and outdoor wireless sensor networks. Among range-free algorithms, DV-hop (Distance Vector - hop) has the advantage to localize the mobile nodes which has less than three neighbour anchors. Based on the original DV-hop algorithm, this paper presents two improved algorithms (Checkout DV-hop and Selective 3-Anchor DV-hop). Checkout DV-hop algorithm estimates the mobile node position by using the nearest anchor, while Selective 3-Anchor DV-hop algorithm chooses the best 3 anchors to improve localization accuracy. Then, in order to implement these DV-hop based algorithms in network scenarios, a novel DV-hop localization protocol is proposed. This new protocol is presented in detail in this paper, including the format of data payloads, the improved collision reduction method E-CSMA/CA, as well as parameters used in deciding the end of each DV-hop step. Finally, using our localization protocol, we investigate the performance of typical DV-hop based algorithms in terms of localization accuracy, mobility, synchronization and overhead. Simulation results prove that Selective 3-Anchor DV-hop algorithm offers the best performance compared to Checkout DV-hop and the original DV-hop algorithm

Quarantine region scheme to mitigate spam attacks in wireless sensor networks

The Quarantine Region Scheme (QRS) is introduced to defend against spam attacks in wireless sensor networks where malicious antinodes frequently generate dummy spam messages to be relayed toward the sink. The aim of the attacker is the exhaustion of the sensor node batteries and the extra delay caused by processing the spam messages. Network-wide message authentication may solve this problem with a cost of cryptographic operations to be performed over all messages. QRS is designed to reduce this cost by applying authentication only whenever and wherever necessary. In QRS, the nodes that detect a nearby spam attack assume themselves to be in a quarantine region. This detection is performed by intermittent authentication checks. Once quarantined, a node continuously applies authentication measures until the spam attack ceases. In the QRS scheme, there is a tradeoff between the resilience against spam attacks and the number of authentications. Our experiments show that, in the worst-case scenario that we considered, a not quarantined node catches 80 percent of the spam messages by authenticating only 50 percent of all messages that it processe

A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Data and resource management in wireless networks via data compression, GPS-free dissemination, and learning

“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting the data of interest. As most of the low-cost wireless sensors won’t be equipped with a GPS module, the virtual coordinates are used to estimate the locations. The proposed work utilizes the anchor-based virtual coordinate system and DV-Hop (Distance vector of hops to anchors) to estimate the relative location of nodes to anchors. Also, it uses circle and hyperbola constraints to encode the position of interest (POI) and any user-defined trajectory into a data request message which allows only the sensors in the POI and routing trajectory to collect and route. It also provides location anonymity by avoiding using and transmitting GPS location information. This has been extended also for heterogeneous WSNs and refined the encoding algorithm by replacing the circle constraints with the ellipse constraints. Last, it proposes a framework that predicts the trajectory of the moving object using a Sequence-to-Sequence learning (Seq2Seq) model and only wakes-up the sensors that fall within the predicted trajectory of the moving object with a specially designed control packet. It reduces the computation time of encoding geospatial trajectory by more than 90% and preserves the location anonymity for the local edge servers”--Abstract, page iv

Efficient Data Collection in IoT Networks using Trajectory Encoded with Geometric Shapes

The mobile edge computing (MEC) paradigm changes the role of edge devices from data producers and requesters to data consumers and processors. MEC mitigates the bandwidth limitation between the edge server and the remote cloud by directly processing the large amount of data locally generated by the network of the internet of things (IoT) at the edge. An efficient data-gathering scheme is crucial for providing quality of service (QoS) within MEC. To reduce redundant data transmission, this paper proposes a data collection scheme that only gathers the necessary data from IoT devices (like wireless sensors) along a trajectory. Instead of using and transmitting location information (which may leak the location anonymity), a virtual coordinate system called \u27distance vector of hops to anchors\u27 (DV-Hop) is used. The proposed trajectory encoding algorithm uses ellipse and hyperbola constraints to encode the position of interest (POI) and the trajectory route to the POI. Sensors make routing decisions only based on the geometric constraints and the DV-Hop information, both of which are stored in their memory. Also, the proposed scheme can work in heterogeneous networks (with different radio ranges) where each sensor can calculate the average one-hop distance within the POI dynamically. The proposed DV-Hop updating algorithm enables the users to collect data in an IoT network with mobile nodes. The experiments show that in heterogeneous IoT networks, the proposed data collection scheme outperforms two other state-of-the-art topology-based routing protocols, called ring routing, and nested ring. The results also show that the proposed scheme has better latency, reliability, coverage, energy usage, and provide location privacy compared to state-of-the-art schemes

A GPS-Less Localization and Mobility Modelling (LMM) System for Wildlife Tracking

Existing wildlife tracking solutions typically use sensor nodes with specialised facilities, such as long-range radio, solar array of cells and Global Positioning System (GPS). This introduces additional manufacturing cost, increased energy and memory consumptions and increased sensor node weight. This paper proposes a novel Localization and Mobility Modelling (LMM) system, that can carry out wildlife tracking by merely using low-cost, lightweight sensor nodes and using short-range peer-to-peer communication facilities only, i.e. without the need for any specialised facilities. This is done by using two computationally simple operations, which are: (i) aggregated data collections from sensor nodes via peer-to-peer communications in a distributed manner, and (ii) estimation of sensor nodes' movement traces using trilateration. The computational load placed on each sensor node is just that of data collection and aggregation, whereas movement traces estimation is carried out on a backend server, separated from the sensor nodes. In the design of the LMM system, we have: (i) carried out an empirical evaluation of different parameter value settings for data collection to develop a Multi-Zone Multi-Hierarchy (MZMH) communication structure, (ii) demonstrated a novel use of an Aggregation based Topology Learning (ATL) protocol for collecting sensor nodes' topology data using peer-to-peer multi-hop communications, and (iii) used a novel Location Estimation (LE) method for estimating sensor nodes' movement traces from the collected topology data. The evaluation results show that the LMM system can accurately estimate sensor nodes' movement traces but with significantly less energy and memory costs, demonstrating its cost-efficiency as compared to the related wildlife tracking solutions. © 2020 IEEE

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Tactical approach to identify and quarantine spurious node participation request in sensory application

Securing Wireless Sensor Network (WSN) from variable forms of adversary is still an open end challenge. Review of diversified security apprroaches towards such problems that they are highly symptomatic with respect to resiliency strength against attack. Therefore, the proposed system highlights a novel and effective solution that is capable of identify the spurios request for participating in teh network building process from attacker and in return could deviate the route of attacker to some virtual nodes and links. A simple trust based mechanism is constructed for validating the legitimacy of such request generated from adversary node. The proposed system not only presents a security solution but also assists in enhancing the routing process significantly. The simulated outcome of the study shows that proposed system offers significantly good energy conservation, satisfactory data forwarding performance, reduced processing time in contrast to existing standard security practices