Improving the connectivity of heterogeneous multi-hop wireless networks

Heterogeneous conditions can occur in multi-hop wireless networks due to a variety of factors such as variations in transmission power and signal propagation environments. Directed links can occur when the environment and/or the nodes are heterogeneous. In this paper, we examine the network connectivity for heterogeneous multi-hop wireless networks and propose an algorithm to identify the connectivity of the network. We follow this with a numerical study of the connectivity in random topologies. Lastly, we propose two schemes for constructing additional links to enhance the connectivity of the network. Our proposed schemes identify the links to be improved or created via a cluster based approach. © 2011 IEEE

Towards Augmenting Federated Wireless Sensor Networks

AbstractEnvironmental Monitoring (EM) has witnessed significant improvements in recent years due to the great utility of Wireless Sensor Networks (WSNs). Nevertheless, due to harsh operational conditions in such applications, WSNs often suffer large scale damage in which nodes fail concurrently and the network gets partitioned into disjoint sectors. Thus, reestablishing connectivity between the sectors, via their remaining functional nodes, is of utmost importance in EM; especially in forestry. In this regard, considerable work has been proposed in the literature tackling this problem by deploying Relay Nodes (RNs) aimed at re-establishing connectivity. Although finding the minimum relay count and positions is NP-Hard, efficient heuristic approaches have been anticipated. However, the majority of these approaches ignore the surrounding environment characteristics and the infinite 3-Dimensional (3-D) search space which significantly degrades network performance in practice. Therefore, we propose a 3-D grid-based deployment for relay nodes in which the relays are efficiently placed on grid vertices. We present a novel approach, named FADI, based on a minimum spanning tree construction to re-connect the disjointed WSN sectors. The performance of the proposed approach is validated and assessed through extensive simulations, and comparisons with two main stream approaches are presented. Our protocol outperforms the related work in terms of the average relay node count and distribution, the scalability of the federated WSNs in large scale applications, and the robustness of the topologies formed

Swarm Intelligence-based Partitioned Recovery in Wireless Sensor Networks, Journal of Telecommunications and Information Technology, 2018, nr 3

The failure rate of sensor nodes in Heterogeneous Wireless Sensor Networks is high due to the use of low battery-powered sensor nodes in a hostile environment. Networks of this kind become non-operational and turn into disjoint segmented networks due to large-scale failures of sensor nodes. This may require the placement of additional highpower relay nodes. In this paper, we propose a network partition recovery solution called Grey Wolf, which is an optimizer algorithm for repairing segmented heterogeneous wireless sensor networks. The proposed solution provides not only strong bi-connectivity in the damaged area, but also distributes traffic load among the multiple deployed nodes to enhance the repaired network’s lifetime. The experiment results show that the Grey Wolf algorithm offers a considerable performance advantage over other state-of-the-art approaches

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.https://doi.org/10.3390/s1704085

Efficient Actor Recovery Paradigm For Wireless Sensor And Actor Networks

Wireless sensor networks (WSNs) are becoming widely used worldwide. Wireless Sensor and Actor Networks (WSANs) represent a special category of WSNs wherein actors and sensors collaborate to perform specific tasks. WSANs have become one of the most preeminent emerging type of WSNs. Sensors with nodes having limited power resources are responsible for sensing and transmitting events to actor nodes. Actors are high-performance nodes equipped with rich resources that have the ability to collect, process, transmit data and perform various actions. WSANs have a unique architecture that distinguishes them from WSNs. Due to the characteristics of WSANs, numerous challenges arise. Determining the importance of factors usually depends on the application requirements. The actor nodes are the spine of WSANs that collaborate to perform the specific tasks in an unsubstantiated and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power fatigue of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. It is essential to keep inter-actor connectivity in order to insure network connectivity. Thus, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). For network recovery process from actor node failure, optimal re-localization and coordination techniques should take place. In this work, we propose an efficient actor recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balances the network performance. The packet is handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets (Either from actor or sensor). This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, we compare the performance of our proposed work with state-of the art localization algorithms. Our experimental results show superior performance in regards to network life, residual energy, reliability, sensor/ actor recovery time and data recovery

Cluster based jamming and countermeasures for wireless sensor network MAC protocols

A wireless sensor network (WSN) is a collection of wireless nodes, usually with limited computing resources and available energy. The medium access control layer (MAC layer) directly guides the radio hardware and manages access to the radio spectrum in controlled way. A top priority for a WSN MAC protocol is to conserve energy, however tailoring the algorithm for this purpose can create or expose a number of security vulnerabilities. In particular, a regular duty cycle makes a node vulnerable to periodic jamming attacks. This vulnerability limits the use of use of a WSN in applications requiring high levels of security. We present a new WSN MAC protocol, RSMAC (Random Sleep MAC) that is designed to provide resistance to periodic jamming attacks while maintaining elements that are essential to WSN functionality. CPU, memory and especially radio usage are kept to a minimum to conserve energy while maintaining an acceptable level of network performance so that applications can be run transparently on top of the secure MAC layer. We use a coordinated yet pseudo-random duty cycle that is loosely synchronized across the entire network via a distributed algorithm. This thwarts an attacker\u27s ability to predict when nodes will be awake and likewise thwarts energy efficient intelligent jamming attacks by reducing their effectiveness and energy-efficiency to that of non-intelligent attacks. Implementing the random duty cycle requires additional energy usage, but also offers an opportunity to reduce asymmetric energy use and eliminate energy use lost to explicit neighbor discovery. We perform testing of RSMAC against non-secure protocols in a novel simulator that we designed to make prototyping new WSN algorithms efficient, informative and consistent. First we perform tests of the existing SMAC protocol to demonstrate the relevance of the novel simulation for estimating energy usage, data transmission rates, MAC timing and other relevant macro characteristics of wireless sensor networks. Second, we use the simulation to perform detailed testing of RSMAC that demonstrates its performance characteristics with different configurations and its effectiveness in confounding intelligent jammers

Cross-Layer Resilience Based On Critical Points in MANETs

A fundamental problem in mobile ad hoc and unstructured sensor networks is maintaining connectivity. A network is connected if all nodes have a communication route (typically multi-hop) to each other. Maintaining connectivity is a challenge due to the unstructured nature of the network topology and the frequent occurrence of link and node failures due to interference, mobility, radio channel effects and battery limitations. In order to effectively deploy techniques to improve the resilience of sensor and mobile ad hoc networks against failures or attacks one must be able to identify all the weak points of a network topology. Here we define the weak or critical points of the topology as those links and nodes whose failure results in partitioning of the network. In this dissertation, we propose a set of algorithms to identify the critical points of a network topology. Utilizing these algorithms we study the behavior of critical points and the effect of using only local information in identifying global critical points. Then, we propose both local and global based resilient techniques that can improve the wireless network connectivity around critical points to lessen their importance and improve the network resilience. Next we extend the work to examine the network connectivity for heterogeneous wireless networks that can be result due to factors such as variations in transmission power and signal propagation environments and propose an algorithm to identify the connectivity of the network. We also propose two schemes for constructing additional links to enhance the connectivity of the network and evaluate the network performance of when a random interference factor occurs. Lastly, we implement our resilience techniques to improve the performance