Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

An effective data-collection scheme with AUV path planning in underwater wireless sensor networks

Data collection in underwater wireless sensor networks (UWSNs) using autonomous underwater vehicles (AUVs) is a more robust solution than traditional approaches, instead of transmitting data from each node to a destination node. However, the design of delay-aware and energy-efficient path planning for AUVs is one of the most crucial problems in collecting data for UWSNs. To reduce network delay and increase network lifetime, we proposed a novel reliable AUV-based data-collection routing protocol for UWSNs. The proposed protocol employs a route planning mechanism to collect data using AUVs. The sink node directs AUVs for data collection from sensor nodes to reduce energy consumption. First, sensor nodes are organized into clusters for better scalability, and then, these clusters are arranged into groups to assign an AUV to each group. Second, the traveling path for each AUV is crafted based on the Markov decision process (MDP) for the reliable collection of data. The simulation results affirm the effectiveness and efficiency of the proposed technique in terms of throughput, energy efficiency, delay, and reliability. © 2022 Wahab Khan et al

Exploring Cross-Layer Dependencies in Congested Wireless Ad Hoc Networks

Steen, M.R. van [Promotor]Voulgaris, S. [Copromotor

Probabilistic route discovery for Wireless Mobile Ad Hoc Networks (MANETs)

Mobile wireless ad hoc networks (MANETs) have become of increasing interest in view of their promise to extend connectivity beyond traditional fixed infrastructure networks. In MANETs, the task of routing is distributed among network nodes which act as both end points and routers in a wireless multi-hop network environment. To discover a route to a specific destination node, existing on-demand routing protocols employ a broadcast scheme referred to as simple flooding whereby a route request packet (RREQ) originating from a source node is blindly disseminated to the rest of the network nodes. This can lead to excessive redundant retransmissions, causing high channel contention and packet collisions in the network, a phenomenon called a broadcast storm. To reduce the deleterious impact of flooding RREQ packets, a number of route discovery algorithms have been suggested over the past few years based on, for example, location, zoning or clustering. Most such approaches however involve considerably increased complexity requiring additional hardware or the maintenance of complex state information. This research argues that such requirements can be largely alleviated without sacrificing performance gains through the use of probabilistic broadcast methods, where an intermediate node rebroadcasts RREQ packets based on some suitable forwarding probability rather than in the traditional deterministic manner. Although several probabilistic broadcast algorithms have been suggested for MANETs in the past, most of these have focused on “pure” broadcast scenarios with relatively little investigation of the performance impact on specific applications such as route discovery. As a consequence, there has been so far very little study of the performance of probabilistic route discovery applied to the well-established MANET routing protocols. In an effort to fill this gap, the first part of this thesis evaluates the performance of the routing protocols Ad hoc On demand Distance Vector (AODV) and Dynamic Source Routing (DSR) augmented with probabilistic route discovery, taking into account parameters such as network density, traffic density and nodal mobility. The results reveal encouraging benefits in overall routing control overhead but also show that network operating conditions have a critical impact on the optimality of the forwarding probabilities. In most existing probabilistic broadcast algorithms, including the one used here for preliminary investigations, each forwarding node is allowed to rebroadcast a received packet with a fixed forwarding probability regardless of its relative location with respect to the locations of the source and destination pairs. However, in a route discovery operation, if the location of the destination node is known, the dissemination of the RREQ packets can be directed towards this location. Motivated by this, the second part of the research proposes a probabilistic route discovery approach that aims to reduce further the routing overhead by limiting the dissemination of the RREQ packets towards the anticipated location of the destination. This approach combines elements of the fixed probabilistic and flooding-based route discovery approaches. The results indicate that in a relatively dense network, these combined effects can reduce the routing overhead very significantly when compared with that of the fixed probabilistic route discovery. Typically in a MANET there are regions of varying node density. Under such conditions, fixed probabilistic route discovery can suffer from a degree of inflexibility, since every node is assigned the same forwarding probability regardless of local conditions. Ideally, the forwarding probability should be high for a node located in a sparse region of the network while relatively lower for a node located in a denser region of the network. As a result, it can be helpful to identify and categorise mobile nodes in the various regions of the network and appropriately adjust their forwarding probabilities. To this end the research examines probabilistic route discovery methods that dynamically adjust the forwarding probability at a node, based on local node density, which is estimated using number of neighbours as a parameter. Results from this study return significantly superior performance measures compared with fixed probabilistic variants. Although the probabilistic route discovery methods suggested above can significantly reduce the routing control overhead without degrading the overall network throughput, there remains the problem of how to select efficiently forwarding probabilities that will optimize the performance of a broadcast under any given conditions. In an attempt to address this issue, the final part of this thesis proposes and evaluates the feasibility of a node estimating its own forwarding probability dynamically based on locally collected information. The technique examined involves each node piggybacking a list of its 1-hop neighbours in its transmitted RREQ packets. Based on this list, relay nodes can determine the number of neighbours that have been already covered by a broadcast and thus compute the forwarding probabilities most suited to individual circumstances

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs