Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

Hierarchical routing protocols for wireless sensor network: a compressive survey

Wireless Sensor Networks (WSNs) are one of the key enabling technologies for the Internet of Things (IoT). WSNs play a major role in data communications in applications such as home, health care, environmental monitoring, smart grids, and transportation. WSNs are used in IoT applications and should be secured and energy efficient in order to provide highly reliable data communications. Because of the constraints of energy, memory and computational power of the WSN nodes, clustering algorithms are considered as energy efficient approaches for resource-constrained WSNs. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first present the most relevant previous work in routing protocols surveys then highlight our contribution. Next, we outline the background, robustness criteria, and constraints of WSNs. This is followed by a survey of different WSN routing techniques. Routing techniques are generally classified as flat, hierarchical, and location-based routing. This survey focuses on the deep analysis of WSN hierarchical routing protocols. We further classify hierarchical protocols based on their routing techniques. We carefully choose the most relevant state-of-the-art protocols in order to compare and highlight the advantages, disadvantage and performance issues of each routing technique. Finally, we conclude this survey by presenting a comprehensive survey of the recent improvements of Low-Energy Adaptive Clustering Hierarchy (LEACH) routing protocols and a comparison of the different versions presented in the literature

Enhanced VGDRA for Dynamic WSN

Sensor Nodes are fundamental blocks of Wireless Sensor Networks. The focus of researchers is still on reducing the energy dissipation by the sensor nodes over time. Sensor nodes once deployed have a fixed amount of energy available to them. In order to use the energy efficiently the sensor nodes are grouped together based on the tasks performed by them. These groups of sensor nodes are known as clusters. Each cluster is headed by a cluster head connecting the cluster with the base station. Energy consumption is directly proportional to the distance from the base station. The concept of network lifetime is closely related to the energy consumption and area coverage in wireless sensor network. The main aim of the proposed technique is to select cluster heads in such a way that they extend the network lifetime and increase throughput of the network. The efficiency of the proposed cluster head selection technique is that it covers energy consumption and routes selection for data delivery from sensor node to the base station. In this paper an Enhanced Virtual Grid-based Dynamic Routes Adjustment Scheme is proposed presenting a set of rules for the selection of cluster heads in such a way that the energy consumption by the cluster heads is balanced throughout the network and it does not get over exploited

Approach to minimizing consumption of energy in wireless sensor networks

The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime

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

Energy-efficient region shift scheme to support mobile sink group in wireless sensor networks

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. Mobile sink groups play crucial roles to perform their own missions in many wireless sensor network (WSN) applications. In order to support mobility of such sink groups, it is important to design a mechanism for effective discovery of the group in motion. However, earlier studies obtain group region information by periodic query. For that reason, the mechanism leads to significant signaling overhead due to frequent flooding for the query regardless of the group movement. Furthermore, the mechanism worsens the problem by the flooding in the whole expected area. To deal with this problem, we propose a novel mobile sink group support scheme with low communication cost, called Region-Shift-based Mobile Geocasting Protocol (RSMGP). In this study, we utilize the group mobility feature for which members of a group have joint motion patterns. Thus, we could trace group movement by shifting the region as much as partial members move out of the previous region. Furthermore, the region acquisition is only performed at the moment by just deviated members without collaboration of all members. Experimental results validate the improved signaling overhead of our study compared to the previous studies